├── Cheminformatics
    ├── RDKit-pandas-integration.ipynb
    ├── markdown-usage.ipynb
    ├── rendering-of-images-in-IPython.ipynb
    ├── scaffold-analysis
    │   ├── Scaffold analysis & Schnellkurs in chemoinformatics.ipynb
    │   ├── biomedx.png
    │   ├── merck.jpeg
    │   ├── pi.gif
    │   └── rdkit.png
    └── somemols.smi
├── Kinase-Inhibitors
    └── approved-or-in-clinical-trials
    │   ├── Kinase inhibitors - approved or in clinical trials.ipynb
    │   ├── chembl_drugs.txt
    │   ├── kin_inh.png
    │   ├── kin_inh.smi
    │   ├── kin_inh_approved.smi
    │   ├── kin_inh_approved_2.smi
    │   ├── kin_inh_approved_3.smi
    │   └── kin_inh_phase4.png
├── LICENSE.md
├── Machine Learning
    ├── Sklearn to ete3 trees.ipynb
    ├── tree.dot
    └── tree.png
├── Presentations and Tutorials
    ├── Molecular Modelling Workshop 2014
    │   ├── Scaffold analysis in Python with RDKit and pandas.ipynb
    │   ├── approved.sdf
    │   ├── biomedx.png
    │   ├── merck.jpeg
    │   └── rdkit.png
    ├── Protvec demo 2017
    │   ├── ProtVec.ipynb
    │   ├── README.md
    │   ├── __init__.py
    │   ├── biovec
    │   │   ├── .gitignore
    │   │   ├── README.md
    │   │   ├── biovec
    │   │   │   ├── __init__.py
    │   │   │   ├── binary_amino.py
    │   │   │   └── models.py
    │   │   ├── setup.py
    │   │   └── trained_models
    │   │   │   └── swissprot_reviewed_protvec
    │   ├── corpus.txt
    │   ├── data
    │   │   ├── family_classification_and_sequence_small.tab
    │   │   └── uniprot_sprot_small.fasta
    │   ├── figures
    │   │   ├── Protein_sentences.png
    │   │   ├── Protein_sentences2.png
    │   │   ├── Skip_gram_cbow.png
    │   │   ├── linear-relationships.png
    │   │   ├── protein_vectors_wlabel.png
    │   │   ├── protein_words.png
    │   │   ├── proteinsequence.png
    │   │   ├── relationships_plus_vectors2.png
    │   │   └── table_overview_vocab2.png
    │   ├── helpers.py
    │   └── trained_models
    │   │   ├── model_SwissProt_small
    │   │   └── swissprot_reviewed_protvec
    └── RDKit UGM 2014
    │   ├── Scaffold analysis of ChEMBL data with pandas and RDKit.ipynb
    │   ├── biomedx.png
    │   ├── hackaton
    │       ├── XLSX export.ipynb
    │       └── drugs.smi
    │   ├── merck.jpeg
    │   └── rdkit.png
├── README.md
└── Virtual-Screening
    ├── filtering
        └── filter_pains.py
    └── ligand-3D-conformations
        ├── prepare_for_docking.py
        ├── test.sdf
        └── test.smi


/Cheminformatics/markdown-usage.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "# BioMed X web page\n",
  8 |     "## Internal presentation on Markdown usage on our web page\n",
  9 |     "###[http://bio.mx/](http://bio.mx/)\n",
 10 |     "\n",
 11 |     "### Team pages\n",
 12 |     "Thank you all for helping. Great thanks to **Marco Tidona** for coding!\n",
 13 |     "\n",
 14 |     "### Notes and missing stuff\n",
 15 |     "- Use Twitter!\n",
 16 |     "- Each group should be able to update their own page\n",
 17 |     "\n",
 18 |     "##### More info on http://192.168.96.60/dokuwiki/doku.php?id=admin:web-page\n",
 19 |     "<br>  \n",
 20 |     "<br>\n",
 21 |     "<br>\n",
 22 |     "<br>\n",
 23 |     "<br>\n",
 24 |     "<br>\n",
 25 |     "<br>\n",
 26 |     "<br>\n",
 27 |     "<br>\n",
 28 |     "<br>\n",
 29 |     "  \n",
 30 |     "  "
 31 |    ]
 32 |   },
 33 |   {
 34 |    "cell_type": "markdown",
 35 |    "metadata": {},
 36 |    "source": [
 37 |     "# Markdown\n",
 38 |     "- Plain text formating syntax\n",
 39 |     "- You can format text without html knowledge\n",
 40 |     "- http://daringfireball.net/projects/markdown/\n",
 41 |     "- http://192.168.96.60/dokuwiki/doku.php?id=admin:web-page\n",
 42 |     "<br>  \n",
 43 |     "<br>\n",
 44 |     "<br>\n",
 45 |     "<br>\n",
 46 |     "<br>\n",
 47 |     "<br>\n",
 48 |     "<br>\n",
 49 |     "<br>"
 50 |    ]
 51 |   },
 52 |   {
 53 |    "cell_type": "markdown",
 54 |    "metadata": {},
 55 |    "source": [
 56 |     "# Headings\n",
 57 |     "\n",
 58 |     "# Header 1\n",
 59 |     "## Header 2\n",
 60 |     "### Header 3 (in our case names)\n",
 61 |     "#### Header 4 (persons position)\n",
 62 |     "##### Header 5 (previous work & contact)"
 63 |    ]
 64 |   },
 65 |   {
 66 |    "cell_type": "markdown",
 67 |    "metadata": {},
 68 |    "source": [
 69 |     "# Lists\n",
 70 |     "- list item 1\n",
 71 |     "- list item 2"
 72 |    ]
 73 |   },
 74 |   {
 75 |    "cell_type": "markdown",
 76 |    "metadata": {},
 77 |    "source": [
 78 |     "# Links\n",
 79 |     "[LINK](www.google.com)  \n",
 80 |     "E-mail: <turk@bio.mx> "
 81 |    ]
 82 |   },
 83 |   {
 84 |    "cell_type": "markdown",
 85 |    "metadata": {},
 86 |    "source": [
 87 |     "# Images\n",
 88 |     "![My Image](http://bio.mx/img/logo-main.png)"
 89 |    ]
 90 |   },
 91 |   {
 92 |    "cell_type": "markdown",
 93 |    "metadata": {},
 94 |    "source": [
 95 |     "# Normal text is easy. You just write\n",
 96 |     "**important** *italic*  \n",
 97 |     "\n",
 98 |     "Two spaces and enter introduce new lines.  \n",
 99 |     "**See new line.**  \n",
100 |     "If you miss spaces and have just enter there will be no new line.\n",
101 |     "**See no new line.**"
102 |    ]
103 |   },
104 |   {
105 |    "cell_type": "code",
106 |    "execution_count": 0,
107 |    "metadata": {
108 |     "collapsed": false
109 |    },
110 |    "outputs": [],
111 |    "source": []
112 |   }
113 |  ],
114 |  "metadata": {
115 |   "kernelspec": {
116 |    "display_name": "Python 2",
117 |    "language": "python",
118 |    "name": "python2"
119 |   },
120 |   "language_info": {
121 |    "codemirror_mode": {
122 |     "name": "ipython",
123 |     "version": 2
124 |    },
125 |    "file_extension": ".py",
126 |    "mimetype": "text/x-python",
127 |    "name": "python",
128 |    "nbconvert_exporter": "python",
129 |    "pygments_lexer": "ipython2",
130 |    "version": "2.7.10"
131 |   }
132 |  },
133 |  "nbformat": 4,
134 |  "nbformat_minor": 0
135 | }
136 | 


--------------------------------------------------------------------------------
/Cheminformatics/rendering-of-images-in-IPython.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "markdown",
  5 |    "metadata": {},
  6 |    "source": [
  7 |     "# Custom objects and their rendering in IPython\n",
  8 |     "### Example of how to use object representations"
  9 |    ]
 10 |   },
 11 |   {
 12 |    "cell_type": "code",
 13 |    "execution_count": 1,
 14 |    "metadata": {
 15 |     "collapsed": false
 16 |    },
 17 |    "outputs": [],
 18 |    "source": [
 19 |     "import rdkit.Chem as Chem\n",
 20 |     "from rdkit.Chem import PandasTools\n",
 21 |     "from rdkit.Chem import Draw\n",
 22 |     "from rdkit.Chem import Descriptors\n",
 23 |     "from rdkit.Chem.Draw import IPythonConsole # Enables RDKit IPython integration"
 24 |    ]
 25 |   },
 26 |   {
 27 |    "cell_type": "markdown",
 28 |    "metadata": {},
 29 |    "source": [
 30 |     "### Lets say you need to create a custom object and you'd like to control the default representation"
 31 |    ]
 32 |   },
 33 |   {
 34 |    "cell_type": "markdown",
 35 |    "metadata": {},
 36 |    "source": [
 37 |     "We'll create an object that can store multiple molecules"
 38 |    ]
 39 |   },
 40 |   {
 41 |    "cell_type": "code",
 42 |    "execution_count": 2,
 43 |    "metadata": {
 44 |     "collapsed": false
 45 |    },
 46 |    "outputs": [],
 47 |    "source": [
 48 |     "class primitiveMolsObject():\n",
 49 |     "    def __init__(self, mols=None):\n",
 50 |     "        self.mols = mols\n",
 51 |     "        self.num = len(mols) # Return number of mols"
 52 |    ]
 53 |   },
 54 |   {
 55 |    "cell_type": "markdown",
 56 |    "metadata": {},
 57 |    "source": [
 58 |     "Get some mols and put them in a list"
 59 |    ]
 60 |   },
 61 |   {
 62 |    "cell_type": "code",
 63 |    "execution_count": 3,
 64 |    "metadata": {
 65 |     "collapsed": false
 66 |    },
 67 |    "outputs": [],
 68 |    "source": [
 69 |     "mol1 = Chem.MolFromSmiles('NC(=O)CS(=O)C(c1ccccc1)c1ccccc1')"
 70 |    ]
 71 |   },
 72 |   {
 73 |    "cell_type": "code",
 74 |    "execution_count": 4,
 75 |    "metadata": {
 76 |     "collapsed": false
 77 |    },
 78 |    "outputs": [],
 79 |    "source": [
 80 |     "mol2 = Chem.MolFromSmiles('CCC(OC(C)=O)C(CC(C)N(C)C)(c1ccccc1)c1ccccc1')"
 81 |    ]
 82 |   },
 83 |   {
 84 |    "cell_type": "code",
 85 |    "execution_count": 5,
 86 |    "metadata": {
 87 |     "collapsed": false
 88 |    },
 89 |    "outputs": [],
 90 |    "source": [
 91 |     "mol3 = Chem.MolFromSmiles(' Cc1ccccc1C(OCCN(C)C)c1ccccc1')"
 92 |    ]
 93 |   },
 94 |   {
 95 |    "cell_type": "code",
 96 |    "execution_count": 6,
 97 |    "metadata": {
 98 |     "collapsed": false
 99 |    },
100 |    "outputs": [],
101 |    "source": [
102 |     "mols = [mol1, mol2, mol3]"
103 |    ]
104 |   },
105 |   {
106 |    "cell_type": "markdown",
107 |    "metadata": {},
108 |    "source": [
109 |     "Create model instance wih your mols"
110 |    ]
111 |   },
112 |   {
113 |    "cell_type": "code",
114 |    "execution_count": 7,
115 |    "metadata": {
116 |     "collapsed": false
117 |    },
118 |    "outputs": [],
119 |    "source": [
120 |     "MyMols = primitiveMolsObject(mols)"
121 |    ]
122 |   },
123 |   {
124 |    "cell_type": "code",
125 |    "execution_count": 8,
126 |    "metadata": {
127 |     "collapsed": false
128 |    },
129 |    "outputs": [
130 |     {
131 |      "data": {
132 |       "text/plain": [
133 |        "<__main__.primitiveMolsObject instance at 0x7f6cd9567908>"
134 |       ]
135 |      },
136 |      "execution_count": 8,
137 |      "metadata": {},
138 |      "output_type": "execute_result"
139 |     }
140 |    ],
141 |    "source": [
142 |     "MyMols"
143 |    ]
144 |   },
145 |   {
146 |    "cell_type": "markdown",
147 |    "metadata": {},
148 |    "source": [
149 |     "Default rendering gives very little info about contents"
150 |    ]
151 |   },
152 |   {
153 |    "cell_type": "code",
154 |    "execution_count": 9,
155 |    "metadata": {
156 |     "collapsed": false
157 |    },
158 |    "outputs": [
159 |     {
160 |      "data": {
161 |       "text/plain": [
162 |        "[<rdkit.Chem.rdchem.Mol at 0x7f6cdfcb8bb0>,\n",
163 |        " <rdkit.Chem.rdchem.Mol at 0x7f6cdfc36d70>,\n",
164 |        " <rdkit.Chem.rdchem.Mol at 0x7f6cdfc36d00>]"
165 |       ]
166 |      },
167 |      "execution_count": 9,
168 |      "metadata": {},
169 |      "output_type": "execute_result"
170 |     }
171 |    ],
172 |    "source": [
173 |     "MyMols.mols"
174 |    ]
175 |   },
176 |   {
177 |    "cell_type": "code",
178 |    "execution_count": 10,
179 |    "metadata": {
180 |     "collapsed": false
181 |    },
182 |    "outputs": [
183 |     {
184 |      "data": {
185 |       "text/plain": [
186 |        "3"
187 |       ]
188 |      },
189 |      "execution_count": 10,
190 |      "metadata": {},
191 |      "output_type": "execute_result"
192 |     }
193 |    ],
194 |    "source": [
195 |     "MyMols.num"
196 |    ]
197 |   },
198 |   {
199 |    "cell_type": "markdown",
200 |    "metadata": {},
201 |    "source": [
202 |     "### Luckily default representations of objects in ipython can be easily controled with \\_repr\\_html\\_"
203 |    ]
204 |   },
205 |   {
206 |    "cell_type": "markdown",
207 |    "metadata": {},
208 |    "source": [
209 |     "Lets define the object again, this time with functions that control representation"
210 |    ]
211 |   },
212 |   {
213 |    "cell_type": "code",
214 |    "execution_count": 11,
215 |    "metadata": {
216 |     "collapsed": false
217 |    },
218 |    "outputs": [],
219 |    "source": [
220 |     "class primitiveMolsObject2():\n",
221 |     "    def __init__(self, mols=None):\n",
222 |     "        self.mols = mols\n",
223 |     "        self.num = len(mols) # Return number of mols\n",
224 |     "    \n",
225 |     "    def _repr_html_(self):\n",
226 |     "        # Default representation in IPython\n",
227 |     "        smilesString = ''\n",
228 |     "        for mol in mols:\n",
229 |     "            smilesString += Chem.MolToSmiles(mol) + \", \" \n",
230 |     "        return smilesString #'<img src=\"data:image/png;base64,%s\" alt=\"Mol\"/>' %s"
231 |    ]
232 |   },
233 |   {
234 |    "cell_type": "code",
235 |    "execution_count": 12,
236 |    "metadata": {
237 |     "collapsed": false
238 |    },
239 |    "outputs": [],
240 |    "source": [
241 |     "MyMols2 = primitiveMolsObject2(mols)"
242 |    ]
243 |   },
244 |   {
245 |    "cell_type": "markdown",
246 |    "metadata": {},
247 |    "source": [
248 |     "Much better! We can acually see what hides behind an object"
249 |    ]
250 |   },
251 |   {
252 |    "cell_type": "code",
253 |    "execution_count": 13,
254 |    "metadata": {
255 |     "collapsed": false
256 |    },
257 |    "outputs": [
258 |     {
259 |      "data": {
260 |       "text/html": [
261 |        "NC(=O)CS(=O)C(c1ccccc1)c1ccccc1, CCC(OC(C)=O)C(CC(C)N(C)C)(c1ccccc1)c1ccccc1, Cc1ccccc1C(OCCN(C)C)c1ccccc1, "
262 |       ],
263 |       "text/plain": [
264 |        "<__main__.primitiveMolsObject2 instance at 0x7f6cd958c050>"
265 |       ]
266 |      },
267 |      "execution_count": 13,
268 |      "metadata": {},
269 |      "output_type": "execute_result"
270 |     }
271 |    ],
272 |    "source": [
273 |     "MyMols2"
274 |    ]
275 |   },
276 |   {
277 |    "cell_type": "markdown",
278 |    "metadata": {},
279 |    "source": [
280 |     "#### Or we can add graphic representation"
281 |    ]
282 |   },
283 |   {
284 |    "cell_type": "code",
285 |    "execution_count": 14,
286 |    "metadata": {
287 |     "collapsed": false
288 |    },
289 |    "outputs": [],
290 |    "source": [
291 |     "from base64 import b64encode\n",
292 |     "from StringIO import StringIO\n",
293 |     "\n",
294 |     "class primitiveMolsObject3():\n",
295 |     "    def __init__(self, mols=None):\n",
296 |     "        self.mols = mols\n",
297 |     "        self.num = len(mols) # Return number of mols\n",
298 |     "    \n",
299 |     "    def _repr_html_(self):\n",
300 |     "        # Default representation in IPython\n",
301 |     "        sio = StringIO()\n",
302 |     "        Draw.MolsToGridImage(self.mols).save(sio,format='PNG')\n",
303 |     "        s = b64encode(sio.getvalue()) # Encode in base64\n",
304 |     "        return '<img src=\"data:image/png;base64,%s\" alt=\"Mol\"/>' %s"
305 |    ]
306 |   },
307 |   {
308 |    "cell_type": "code",
309 |    "execution_count": 15,
310 |    "metadata": {
311 |     "collapsed": false
312 |    },
313 |    "outputs": [],
314 |    "source": [
315 |     "MyOtherMols = primitiveMolsObject3(mols)"
316 |    ]
317 |   },
318 |   {
319 |    "cell_type": "markdown",
320 |    "metadata": {},
321 |    "source": [
322 |     "Much better! We can acually see what hides behind an object"
323 |    ]
324 |   },
325 |   {
326 |    "cell_type": "code",
327 |    "execution_count": 16,
328 |    "metadata": {
329 |     "collapsed": false
330 |    },
331 |    "outputs": [
332 |     {
333 |      "data": {
334 |       "text/html": [
335 |        "<img 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\" alt=\"Mol\"/>"
336 |       ],
337 |       "text/plain": [
338 |        "<__main__.primitiveMolsObject3 instance at 0x7f6cd958cbd8>"
339 |       ]
340 |      },
341 |      "execution_count": 16,
342 |      "metadata": {},
343 |      "output_type": "execute_result"
344 |     }
345 |    ],
346 |    "source": [
347 |     "MyOtherMols"
348 |    ]
349 |   },
350 |   {
351 |    "cell_type": "markdown",
352 |    "metadata": {},
353 |    "source": [
354 |     "Copyright (C) 2014 by Samo Turk, BioMed X GmbH\n",
355 |     "\n",
356 |     "This work is licensed under the Creative Commons Attribution-ShareAlike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.\n"
357 |    ]
358 |   }
359 |  ],
360 |  "metadata": {
361 |   "kernelspec": {
362 |    "display_name": "Python 2",
363 |    "language": "python",
364 |    "name": "python2"
365 |   },
366 |   "language_info": {
367 |    "codemirror_mode": {
368 |     "name": "ipython",
369 |     "version": 2
370 |    },
371 |    "file_extension": ".py",
372 |    "mimetype": "text/x-python",
373 |    "name": "python",
374 |    "nbconvert_exporter": "python",
375 |    "pygments_lexer": "ipython2",
376 |    "version": "2.7.10"
377 |   }
378 |  },
379 |  "nbformat": 4,
380 |  "nbformat_minor": 0
381 | }
382 | 


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/Cheminformatics/somemols.smi:
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1 | SMILES Name 
2 | C[S+](CCC(N)C(=O)O)CC1OC(n2cnc3c2ncnc3N)C(O)C1O DB00118
3 | Nc1ncnc2c1ncn2C1OC(COP(=O)(O)O)C(O)C1O DB00131
4 | Nc1ncnc2c1ncn2C1OC(CO)C(O)C1O DB00194
5 | Nc1nc(Cl)nc2c1ncn2C1CC(O)C(CO)O1 DB00242
6 | Nc1nc(Cl)nc2c1ncn2C1OC(CO)C(O)C1F DB00631
7 | Nc1nc(F)nc2c1ncn2C1OC(COP(=O)(O)O)C(O)C1O DB01073
8 | COc1nc(N)nc2c1ncn2C1OC(CO)C(O)C1O DB01280
9 | 


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/Kinase-Inhibitors/approved-or-in-clinical-trials/kin_inh.smi:
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  1 | SMILES Name 
  2 | Cc1cc2c(F)c(Oc3ncnn4cc(OCC(C)OC(=O)C(C)N)c(C)c34)ccc2[nH]1 Brivanib
  3 | CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)C=CCN(C)C Pelitinib
  4 | COc1cc2c(Oc3ccc(NC(=O)C4(C(=O)Nc5ccc(F)cc5)CC4)cc3F)ccnc2cc1OCCCN1CCOCC1 Foretinib
  5 | COc1cc2nccc(Oc3ccc(NC(=O)Nc4cc(C)on4)c(Cl)c3)c2cc1OC Tivozanib
  6 | COc1cc(Nc2c(C#N)cnc3cc(OCCCN4CCN(C)CC4)c(OC)cc23)c(Cl)cc1Cl Bosutinib
  7 | CC1CCN(C(=O)CC#N)CC1N(C)c1ncnc2[nH]ccc12 Tofacitinib
  8 | Clc1ccc(Nc2nnc(Cc3ccncc3)c3ccccc23)cc1 Vatalanib
  9 | CCc1cc2c(cc1N1CCC(N3CCOCC3)CC1)C(C)(C)c1[nH]c3cc(C#N)ccc3c1C2=O Alectinib
 10 | Cn1ncc(Cl)c1-c1cc(C(=O)NC(CN)Cc2ccc(F)c(F)c2)oc1Cl Uprosertib
 11 | Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1C#Cc1cnc2cccnn12 Ponatinib
 12 | N#CCC(C1CCCC1)n1cc(-c2ncnc3[nH]ccc23)cn1 Ruxolitinib
 13 | C=CC(=O)N1CCCC(n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1 Ibrutinib
 14 | Cn1ncc(Cl)c1-c1cc(C(=O)NC(CN)Cc2cccc(F)c2)sc1Cl Afuresertib
 15 | CCC(CO)Nc1nc(NCc2ccccc2)c2ncn(C(C)C)c2n1 Seliciclib
 16 | O=C(Nc1nc2cccc(-c3ccc(CN4CCS(=O)(=O)CC4)cc3)n2n1)C1CC1 Filgotinib
 17 | CCc1nc(C(N)=O)c(Nc2ccc(N3CCC(N4CCN(C)CC4)CC3)c(OC)c2)nc1NC1CCOCC1 Gilteritinib
 18 | CN(C)C1CCN(C(=O)c2ccc(NC(=O)Nc3ccc(-c4nc(N5CCOCC5)nc(N5CCOCC5)n4)cc3)cc2)CC1 Gedatolisib
 19 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1 Sorafenib
 20 | Cc1nc(Nc2ncc(C(=O)Nc3c(C)cccc3Cl)s2)cc(N2CCN(CCO)CC2)n1 Dasatinib
 21 | COc1cc2c(Oc3ccc4[nH]c(C)cc4c3F)ncnc2cc1OCCCN1CCCC1 Cediranib
 22 | COC(=O)c1ccc2c(c1)NC(=O)C2=C(Nc1ccc(N(C)C(=O)CN2CCN(C)CC2)cc1)c1ccccc1 Nintedanib
 23 | Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(C(=O)NOCCO)cc21 Selumetinib
 24 | CCS(=O)(=O)N1CC(CC#N)(n2cc(-c3ncnc4[nH]ccc34)cn2)C1 Baricitinib
 25 | FC(F)(F)c1ccc(C=Cc2nc(COc3ccc(CCCCn4ccnn4)cc3)co2)cc1 Mubritinib
 26 | Cc1cc2c(F)c(Oc3ncnn4cc(OCC(C)O)c(C)c34)ccc2[nH]1 Brivanib
 27 | COc1cc(OC)c(C=CS(=O)(=O)Cc2ccc(OC)c(OP(=O)(O)O)c2)c(OC)c1 Briciclib
 28 | NC(=O)c1cnc2[nH]ccc2c1NC1C2CC3CC1CC(O)(C3)C2 Peficitinib
 29 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OP(C)(C)=O)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Ridaforolimus
 30 | COc1cc2nccc(Oc3ccc(NC(=O)NC4CC4)c(Cl)c3)c2cc1C(N)=O Lenvatinib
 31 | CCC1C(=O)N(C)c2cnc(Nc3ccc(C(=O)NC4CCC(N5CCN(CC6CC6)CC5)CC4)cc3OC)nc2N1C(C)C Volasertib
 32 | COc1cc2c(N3CCN(C(=O)Nc4ccc(OC(C)C)cc4)CC3)ncnc2cc1OCCCN1CCCCC1 Tandutinib
 33 | Cc1nc(-c2cn3c(n2)-c2ccc(-c4cnn(C(C)(C)C(N)=O)c4)cc2OCC3)n(C(C)C)n1 Taselisib
 34 | Cc1cccc(-c2nn3c(c2-c2ccnc4ccc(C(N)=O)cc24)CCC3)n1 Galunisertib
 35 | COc1ncc(-c2ccc3nccc(-c4ccnnc4)c3c2)cc1NS(=O)(=O)c1ccc(F)cc1F Omipalisib
 36 | OC1CCC(Nc2ncc3nc(Nc4c(F)cc(F)cc4F)n(C4CCOC4)c3n2)CC1 Tanzisertib
 37 | CN1CCN(c2ccc3nc(-c4c(N)c5c(F)cccc5[nH]c4=O)[nH]c3c2)CC1 Dovitinib
 38 | CC(C)(C)c1nc(-c2cccc(NS(=O)(=O)c3c(F)cccc3F)c2F)c(-c2ccnc(N)n2)s1 Dabrafenib
 39 | Cc1cnc(Nc2ccc(OCCN3CCCC3)cc2)nc1Nc1cccc(S(=O)(=O)NC(C)(C)C)c1 Fedratinib
 40 | C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1 Canertinib
 41 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OCCO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Everolimus
 42 | CCN(CC)CCNC(=O)c1c(C)[nH]c(C=C2C(=O)Nc3ccc(F)cc32)c1C Sunitinib
 43 | Cc1c(F)cc(C(=O)NC2CC2)cc1-c1ccc(C(=O)NCC(C)(C)C)cn1 Losmapimod
 44 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(O)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Sirolimus
 45 | CC12OC(CC1(O)CO)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)CNC4=O Lestaurtinib
 46 | COc1cc2nccc(Oc3ccc(NC(=O)C4(C(=O)Nc5ccc(F)cc5)CC4)cc3)c2cc1OC Cabozantinib
 47 | COc1cc2c(Nc3ccc(Sc4nccn4C)c(Cl)c3)c(C#N)cnc2cc1N1CCC(N2CCCC2)CC1 Balamapimod
 48 | CC1(C)CN(C(=O)c2ccc(-c3cccc4nc(NC(=O)C5CC5)nn34)cc2)C1 Solcitinib
 49 | CCN1CCN(Cc2ccc(Nc3ncc(F)c(-c4cc(F)c5nc(C)n(C(C)C)c5c4)n3)nc2)CC1 Abemaciclib
 50 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)c(F)c2)ccn1 Regorafenib
 51 | Cc1ccc(-n2nc(C(C)(C)C)cc2NC(=O)Nc2ccc(OCCN3CCOCC3)c3ccccc23)cc1 Doramapimod
 52 | COc1cc(OC)c(C=CS(=O)(=O)Cc2ccc(OC)c(NCC(=O)O)c2)c(OC)c1 Rigosertib
 53 | COc1cc(Nc2ncc(F)c(Nc3ccc4c(n3)N(COP(=O)(O)O)C(=O)C(C)(C)O4)n2)cc(OC)c1OC Fostamatinib
 54 | Cc1cc(Nc2cc(N3CCN(C)CC3)nc(Sc3ccc(NC(=O)C4CC4)cc3)n2)n[nH]1 Tozasertib
 55 | CC1(O)CC(c2nc(-c3ccc4ccc(-c5ccccc5)nc4c3)c3c(N)nccn23)C1 Linsitinib
 56 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(O)C(OC)C2)CCC(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Olcorolimus
 57 | Cc1cc(C)c(C=C2C(=O)Nc3ccccc32)[nH]1 Semaxanib
 58 | CC1COC(Nc2ccc3ncnc(Nc4ccc(OCc5nccs5)c(Cl)c4)c3c2)=N1 Varlitinib
 59 | CC(C)NCC(C(=O)N1CCN(c2ncnc3c2C(C)CC3O)CC1)c1ccc(Cl)cc1 Ipatasertib
 60 | Cc1ccc(F)c(NC(=O)Nc2ccc(-c3cccc4[nH]nc(N)c34)cc2)c1 Linifanib
 61 | CCOCCOC1CCC(CC(C)C2CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C(C)C(OC)CC3CCC(C)C(O)(O3)C(=O)C(=O)N3CCCCC3C(=O)O2)CC1OC Umirolimus
 62 | CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(C)=CC3CCC(Cl)C(OC)C3)C(C)C(O)CC1=O)C(C)CC2OC Pimecrolimus
 63 | CNC(=O)c1ccc(Nc2ncc(C(F)(F)F)c(NCc3nccnc3N(C)S(C)(=O)=O)n2)cc1 Defactinib
 64 | Cc1ccc(NC(=O)c2ccc(CN3CCC(N(C)C)C3)c(C(F)(F)F)c2)cc1Nc1nccc(-c2cncnc2)n1 Bafetinib
 65 | CC(Oc1cc(-c2cnn(C3CCNCC3)c2)cnc1N)c1c(Cl)ccc(F)c1Cl Crizotinib
 66 | Cc1cn(-c2cc(NC(=O)c3ccc(C)c(Nc4nccc(-c5cccnc5)n4)c3)cc(C(F)(F)F)c2)cn1 Nilotinib
 67 | CCC(Nc1ncnc2[nH]cnc12)c1nc2cccc(F)c2c(=O)n1-c1ccccc1 Idelalisib
 68 | COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1 Vandetanib
 69 | Cc1c(CN2CCN(C(=O)C(C)O)CC2)sc2c(N3CCOCC3)nc(-c3cnc(N)nc3)nc12 Apitolisib
 70 | O=C1NC(=O)C(c2cn3c4c(cccc24)CCC3)C1c1c[nH]c2ccccc12 Tivantinib
 71 | Nc1ncc(-c2cnn(CCO)c2)c2scc(-c3ccc(NC(=O)Nc4cccc(F)c4)cc3)c12 Ilorasertib
 72 | CC1(COc2ccc3c(c2)ncn3-c2ccc3cccc(N4CCC(N)CC4)c3n2)COC1 Crenolanib
 73 | CC(=NNC(=N)N)c1cc(NC(=O)CCCCCCCCC(=O)Nc2cc(C(C)=NNC(=N)N)cc(C(C)=NNC(=N)N)c2)cc(C(C)=NNC(=N)N)c1 Semapimod
 74 | CC(C)(C)Cn1c(N)nc2ccc(-c3[nH]c(C(C)(C)C)nc3-c3ccc(F)cc3)nc21 Ralimetinib
 75 | C=CC(=O)Nc1cccc(Nc2nc(Nc3ccc(OCCOC)cc3)ncc2F)c1 Spebrutinib
 76 | CC1(C)CNc2cc(NC(=O)c3cccnc3NCc3ccncc3)ccc21 Motesanib
 77 | CC1CN(C(=O)c2cc3c(C(=O)C(=O)N(C)C)cn(C)c3cc2Cl)C(C)CN1Cc1ccc(F)cc1 Talmapimod
 78 | C1=CCOCc2cc(ccc2OCCN2CCCC2)Nc2nccc(n2)-c2cccc(c2)COC1 Pacritinib
 79 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(n3cnnn3)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Zotarolimus
 80 | Cc1cnc(NC(=O)Nc2cc(Br)c(C)cc2OCC2CNCCO2)cn1 Rabusertib
 81 | Cc1cc(Nc2ncc(Cl)c(Nc3ccccc3S(=O)(=O)C(C)C)n2)c(OC(C)C)cc1C1CCNCC1 Ceritinib
 82 | CN1CCN(C2CCN(C(=O)Nc3cc(Oc4ccc(NC(=O)C5(C(=O)Nc6ccc(F)cc6)CC5)c(F)c4)ccn3)CC2)CC1 Golvatinib
 83 | CCC(C)(Nc1ccnc(-c2c[nH]c3ncccc23)n1)C(=O)NCC(F)(F)F Decernotinib
 84 | Cc1[nH]c(C=C2C(=O)Nc3ccc(F)cc32)c(C)c1C(=O)NCCN1CCCC1 Toceranib
 85 | CC(C)(C)c1cc(NC(=O)Nc2ccc(-c3cn4c(n3)sc3cc(OCCN5CCOCC5)ccc34)cc2)no1 Quizartinib
 86 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3cc(C(C)(C)C)nn3-c3ccc4ncccc4c3)c(F)c2)ccn1 Rebastinib
 87 | CC(=O)c1c(C)c2cnc(Nc3ccc(N4CCNCC4)cn3)nc2n(C2CCCC2)c1=O Palbociclib
 88 | COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1 Gefitinib
 89 | CNC(=O)c1ccccc1Sc1ccc2c(C=Cc3ccccn3)n[nH]c2c1 Axitinib
 90 | CN1CCN(CCOc2cc(OC3CCOCC3)c3c(Nc4c(Cl)ccc5c4OCO5)ncnc3c2)CC1 Saracatinib
 91 | CC(Nc1ncnc2nc[nH]c12)c1cc2cccc(Cl)c2c(=O)n1-c1ccccc1 Duvelisib
 92 | Cn1cnc2c(F)c(Nc3ccc(Br)cc3F)c(C(=O)NOCCO)cc21 Binimetinib
 93 | Cn1c(=O)n(-c2ccc(C(C)(C)C#N)cc2)c2c3cc(-c4cnc5ccccc5c4)ccc3ncc21 Dactolisib
 94 | CN(C)CC=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC1CCOC1 Afatinib
 95 | Cc1cc(Nc2cc(CN3CCOCC3)c3nc(C)c(Cc4ccc(Cl)cc4F)n3n2)n[nH]1 Gandotinib
 96 | CS(=O)(=O)CCNCc1ccc(-c2ccc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3c2)o1 Lapatinib
 97 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OC(=O)C(C)(CO)CO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Temsirolimus
 98 | CNS(=O)(=O)CC1CCC(N(C)c2[nH]cnc3nccc2-3)CC1 Oclacitinib
 99 | COc1cc(Nc2ncc3c(n2)-c2ccc(Cl)cc2C(c2c(F)cccc2OC)=NC3)ccc1C(=O)O Alisertib
100 | CCc1cnn2c(NCc3ccc[n+]([O-])c3)cc(N3CCCCC3CCO)nc12 Dinaciclib
101 | COC(=O)NC(C)CNc1nccc(-c2cn(C(C)C)nc2-c2cc(Cl)cc(NS(C)(=O)=O)c2F)n1 Encorafenib
102 | Cc1cc(F)ccc1-c1nc(NC(CO)CO)nc2c1ccc(=O)n2-c1c(F)cccc1F Dilmapimod
103 | O=C(c1ccc(F)c(F)c1Nc1ccc(I)cc1F)N1CC(O)(C2CCCCN2)C1 Cobimetinib
104 | COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)C=CCN1CCCCC1 Dacomitinib
105 | Cc1ccc(Nc2nccc(N(C)c3ccc4c(C)n(C)nc4c3)n2)cc1S(N)(=O)=O Pazopanib
106 | CCOc1cc2ncc(C#N)c(Nc3ccc(OCc4ccccn4)c(Cl)c3)c2cc1NC(=O)C=CCN(C)C Neratinib
107 | Cn1c(=O)c(Oc2ccc(F)cc2F)cc2cnc(NC(CCO)CCO)nc21 Pamapimod
108 | CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(-c4ccc(Cl)cc4)cc23)c1F Vemurafenib
109 | C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1 Erlotinib
110 | S=C(NCc1ccc2c(c1)OCO2)N1CCN(c2ncnc3c2oc2ccccc23)CC1 Amuvatinib
111 | O=C(NCC(O)CO)c1ccncc1Nc1ccc(I)cc1F Pimasertib
112 | CC(=O)Nc1cccc(-n2c(=O)n(C3CC3)c(=O)c3c(Nc4ccc(I)cc4F)n(C)c(=O)c(C)c32)c1 Trametinib
113 | C=CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(C)=CC3CCC(O)C(OC)C3)C(C)C(O)CC1=O)C(C)CC2OC Tacrolimus
114 | N#CCNC(=O)c1ccc(-c2ccnc(Nc3ccc(N4CCOCC4)cc3)n2)cc1 Momelotinib
115 | Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1Nc1nccc(-c2cccnc2)n1 Imatinib
116 | 


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/Kinase-Inhibitors/approved-or-in-clinical-trials/kin_inh_approved.smi:
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 1 | SMILES Name 
 2 | COc1cc(Nc2c(C#N)cnc3cc(OCCCN4CCN(C)CC4)c(OC)cc23)c(Cl)cc1Cl Bosutinib
 3 | CC1CCN(C(=O)CC#N)CC1N(C)c1ncnc2[nH]ccc12 Tofacitinib
 4 | Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1C#Cc1cnc2cccnn12 Ponatinib
 5 | N#CCC(C1CCCC1)n1cc(-c2ncnc3[nH]ccc23)cn1 Ruxolitinib
 6 | C=CC(=O)N1CCCC(n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1 Ibrutinib
 7 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1 Sorafenib
 8 | Cc1nc(Nc2ncc(C(=O)Nc3c(C)cccc3Cl)s2)cc(N2CCN(CCO)CC2)n1 Dasatinib
 9 | COC(=O)c1ccc2c(c1)NC(=O)C2=C(Nc1ccc(N(C)C(=O)CN2CCN(C)CC2)cc1)c1ccccc1 Nintedanib
10 | CC(C)(C)c1nc(-c2cccc(NS(=O)(=O)c3c(F)cccc3F)c2F)c(-c2ccnc(N)n2)s1 Dabrafenib
11 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OCCO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Everolimus
12 | CCN(CC)CCNC(=O)c1c(C)[nH]c(C=C2C(=O)Nc3ccc(F)cc32)c1C Sunitinib
13 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(O)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Sirolimus
14 | COc1cc2nccc(Oc3ccc(NC(=O)C4(C(=O)Nc5ccc(F)cc5)CC4)cc3)c2cc1OC Cabozantinib
15 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)c(F)c2)ccn1 Regorafenib
16 | CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(C)=CC3CCC(Cl)C(OC)C3)C(C)C(O)CC1=O)C(C)CC2OC Pimecrolimus
17 | CC(Oc1cc(-c2cnn(C3CCNCC3)c2)cnc1N)c1c(Cl)ccc(F)c1Cl Crizotinib
18 | Cc1cn(-c2cc(NC(=O)c3ccc(C)c(Nc4nccc(-c5cccnc5)n4)c3)cc(C(F)(F)F)c2)cn1 Nilotinib
19 | CCC(Nc1ncnc2[nH]cnc12)c1nc2cccc(F)c2c(=O)n1-c1ccccc1 Idelalisib
20 | COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1 Vandetanib
21 | Cc1cc(Nc2ncc(Cl)c(Nc3ccccc3S(=O)(=O)C(C)C)n2)c(OC(C)C)cc1C1CCNCC1 Ceritinib
22 | COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1 Gefitinib
23 | CNC(=O)c1ccccc1Sc1ccc2c(C=Cc3ccccn3)n[nH]c2c1 Axitinib
24 | CN(C)CC=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC1CCOC1 Afatinib
25 | CS(=O)(=O)CCNCc1ccc(-c2ccc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3c2)o1 Lapatinib
26 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OC(=O)C(C)(CO)CO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Temsirolimus
27 | Cc1ccc(Nc2nccc(N(C)c3ccc4c(C)n(C)nc4c3)n2)cc1S(N)(=O)=O Pazopanib
28 | CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(-c4ccc(Cl)cc4)cc23)c1F Vemurafenib
29 | C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1 Erlotinib
30 | CC(=O)Nc1cccc(-n2c(=O)n(C3CC3)c(=O)c3c(Nc4ccc(I)cc4F)n(C)c(=O)c(C)c32)c1 Trametinib
31 | C=CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(C)=CC3CCC(O)C(OC)C3)C(C)C(O)CC1=O)C(C)CC2OC Tacrolimus
32 | Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1Nc1nccc(-c2cccnc2)n1 Imatinib
33 | 


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/Kinase-Inhibitors/approved-or-in-clinical-trials/kin_inh_approved_2.smi:
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 1 | COc1cc(Nc2c(C#N)cnc3cc(OCCCN4CCN(C)CC4)c(OC)cc23)c(Cl)cc1Cl Bosutinib
 2 | CC1CCN(C(=O)CC#N)CC1N(C)c1ncnc2[nH]ccc12 Tofacitinib
 3 | Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1C#Cc1cnc2cccnn12 Ponatinib
 4 | N#CCC(C1CCCC1)n1cc(-c2ncnc3[nH]ccc23)cn1 Ruxolitinib
 5 | C=CC(=O)N1CCCC(n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1 Ibrutinib
 6 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1 Sorafenib
 7 | Cc1nc(Nc2ncc(C(=O)Nc3c(C)cccc3Cl)s2)cc(N2CCN(CCO)CC2)n1 Dasatinib
 8 | COC(=O)c1ccc2c(c1)NC(=O)C2=C(Nc1ccc(N(C)C(=O)CN2CCN(C)CC2)cc1)c1ccccc1 Nintedanib
 9 | CC(C)(C)c1nc(-c2cccc(NS(=O)(=O)c3c(F)cccc3F)c2F)c(-c2ccnc(N)n2)s1 Dabrafenib
10 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OCCO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Everolimus
11 | CCN(CC)CCNC(=O)c1c(C)[nH]c(C=C2C(=O)Nc3ccc(F)cc32)c1C Sunitinib
12 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(O)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Sirolimus
13 | COc1cc2nccc(Oc3ccc(NC(=O)C4(C(=O)Nc5ccc(F)cc5)CC4)cc3)c2cc1OC Cabozantinib
14 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)c(F)c2)ccn1 Regorafenib
15 | CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(C)=CC3CCC(Cl)C(OC)C3)C(C)C(O)CC1=O)C(C)CC2OC Pimecrolimus
16 | CC(Oc1cc(-c2cnn(C3CCNCC3)c2)cnc1N)c1c(Cl)ccc(F)c1Cl Crizotinib
17 | Cc1cn(-c2cc(NC(=O)c3ccc(C)c(Nc4nccc(-c5cccnc5)n4)c3)cc(C(F)(F)F)c2)cn1 Nilotinib
18 | CCC(Nc1ncnc2[nH]cnc12)c1nc2cccc(F)c2c(=O)n1-c1ccccc1 Idelalisib
19 | COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1 Vandetanib
20 | Cc1cc(Nc2ncc(Cl)c(Nc3ccccc3S(=O)(=O)C(C)C)n2)c(OC(C)C)cc1C1CCNCC1 Ceritinib
21 | COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1 Gefitinib
22 | CNC(=O)c1ccccc1Sc1ccc2c(C=Cc3ccccn3)n[nH]c2c1 Axitinib
23 | CN(C)CC=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC1CCOC1 Afatinib
24 | CS(=O)(=O)CCNCc1ccc(-c2ccc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3c2)o1 Lapatinib
25 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OC(=O)C(C)(CO)CO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C Temsirolimus
26 | Cc1ccc(Nc2nccc(N(C)c3ccc4c(C)n(C)nc4c3)n2)cc1S(N)(=O)=O Pazopanib
27 | CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(-c4ccc(Cl)cc4)cc23)c1F Vemurafenib
28 | C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1 Erlotinib
29 | CC(=O)Nc1cccc(-n2c(=O)n(C3CC3)c(=O)c3c(Nc4ccc(I)cc4F)n(C)c(=O)c(C)c32)c1 Trametinib
30 | C=CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(C)=CC3CCC(O)C(OC)C3)C(C)C(O)CC1=O)C(C)CC2OC Tacrolimus
31 | Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1Nc1nccc(-c2cccnc2)n1 Imatinib
32 | 


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/Kinase-Inhibitors/approved-or-in-clinical-trials/kin_inh_approved_3.smi:
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 1 | COc1cc(Nc2c(C#N)cnc3cc(OCCCN4CCN(C)CC4)c(OC)cc23)c(Cl)cc1Cl	Bosutinib
 2 | CC1CCN(C(=O)CC#N)CC1N(C)c1ncnc2[nH]ccc12	Tofacitinib
 3 | Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1C#Cc1cnc2cccnn12	Ponatinib
 4 | N#CCC(C1CCCC1)n1cc(c2ncnc3[nH]ccc23)cn1	Ruxolitinib
 5 | C=CC(=O)N1CCCC(n2nc(c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc23)C1	Ibrutinib
 6 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1	Sorafenib
 7 | Cc1nc(Nc2ncc(C(=O)Nc3c(C)cccc3Cl)s2)cc(N2CCN(CCO)CC2)n1	Dasatinib
 8 | COC(=O)c1ccc2c(c1)NC(=O)C2=C(Nc1ccc(N(C)C(=O)CN2CCN(C)CC2)cc1)c1ccccc1	Nintedanib
 9 | CC(C)(C)c1nc(c2cccc(NS(=O)(=O)c3c(F)cccc3F)c2F)c(c2ccnc(N)n2)s1	Dabrafenib
10 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OCCO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C	Everolimus
11 | CCN(CC)CCNC(=O)c1c(C)[nH]c(C=C2C(=O)Nc3ccc(F)cc23)c1C	Sunitinib
12 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(O)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C	Sirolimus
13 | COc1cc2nccc(Oc3ccc(NC(=O)C4(C(=O)Nc5ccc(F)cc5)CC4)cc3)c2cc1OC	Cabozantinib
14 | CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)c(F)c2)ccn1	Regorafenib
15 | CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(=CC3CCC(Cl)C(OC)C3)C)C(C)C(O)CC1=O)C(C)CC2OC	Pimecrolimus
16 | CC(Oc1cc(c2cnn(C3CCNCC3)c2)cnc1N)c1c(Cl)ccc(F)c1Cl	Crizotinib
17 | Cc1cn(c2cc(NC(=O)c3ccc(C)c(Nc4nccc(c5cccnc5)n4)c3)cc(C(F)(F)F)c2)cn1	Nilotinib
18 | CCC(Nc1ncnc2[nH]cnc12)c1nc2cccc(F)c2c(=O)n1c1ccccc1	Idelalisib
19 | COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1	Vandetanib
20 | Cc1cc(Nc2ncc(Cl)c(Nc3ccccc3S(=O)(=O)C(C)C)n2)c(OC(C)C)cc1C1CCNCC1	Ceritinib
21 | COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1	Gefitinib
22 | CNC(=O)c1ccccc1Sc1ccc2c(C=Cc3ccccn3)n[nH]c2c1	Axitinib
23 | CN(C)CC=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC1CCOC1	Afatinib
24 | CS(=O)(=O)CCNCc1ccc(c2ccc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3c2)o1	Lapatinib
25 | COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OC(=O)C(C)(CO)CO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C	Temsirolimus
26 | Cc1ccc(Nc2nccc(N(C)c3ccc4c(C)n(C)nc4c3)n2)cc1S(=O)(=O)N	Pazopanib
27 | CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(c4ccc(Cl)cc4)cc23)c1F	Vemurafenib
28 | C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1	Erlotinib
29 | CC(=O)Nc1cccc(n2c(=O)n(C3CC3)c(=O)c3c(Nc4ccc(I)cc4F)n(C)c(=O)c(C)c23)c1	Trametinib
30 | C=CCC1C=C(C)CC(C)CC(OC)C2OC(O)(C(=O)C(=O)N3CCCCC3C(=O)OC(C(=CC3CCC(O)C(OC)C3)C)C(C)C(O)CC1=O)C(C)CC2OC	Tacrolimus
31 | Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1Nc1nccc(c2cccnc2)n1	Imatinib
32 | 


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/LICENSE.md:
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1 | Code in this repository is copyright (C) 2013-2016 by Team SKI @ BioMed X GmbH
2 | 
3 | This work is licensed under the Creative Commons Attribution-ShareAlike 3.0
4 | License. To view a copy of this license, visit
5 | http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to Creative
6 | Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.
7 | 


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 2 | node [shape=box] ;
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 4 | 1 [label="gini = 0.0\nsamples = 50\nvalue = [50, 0, 0]"] ;
 5 | 0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
 6 | 2 [label="X[3] <= 1.75\ngini = 0.5\nsamples = 100\nvalue = [0, 50, 50]"] ;
 7 | 0 -> 2 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
 8 | 3 [label="X[2] <= 4.95\ngini = 0.168\nsamples = 54\nvalue = [0, 49, 5]"] ;
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10 | 4 [label="X[3] <= 1.65\ngini = 0.0408\nsamples = 48\nvalue = [0, 47, 1]"] ;
11 | 3 -> 4 ;
12 | 5 [label="gini = 0.0\nsamples = 47\nvalue = [0, 47, 0]"] ;
13 | 4 -> 5 ;
14 | 6 [label="gini = 0.0\nsamples = 1\nvalue = [0, 0, 1]"] ;
15 | 4 -> 6 ;
16 | 7 [label="X[3] <= 1.55\ngini = 0.4444\nsamples = 6\nvalue = [0, 2, 4]"] ;
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18 | 8 [label="gini = 0.0\nsamples = 3\nvalue = [0, 0, 3]"] ;
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22 | 10 [label="gini = 0.0\nsamples = 2\nvalue = [0, 2, 0]"] ;
23 | 9 -> 10 ;
24 | 11 [label="gini = 0.0\nsamples = 1\nvalue = [0, 0, 1]"] ;
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26 | 12 [label="X[2] <= 4.85\ngini = 0.0425\nsamples = 46\nvalue = [0, 1, 45]"] ;
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30 | 14 [label="gini = 0.0\nsamples = 1\nvalue = [0, 1, 0]"] ;
31 | 13 -> 14 ;
32 | 15 [label="gini = 0.0\nsamples = 2\nvalue = [0, 0, 2]"] ;
33 | 13 -> 15 ;
34 | 16 [label="gini = 0.0\nsamples = 43\nvalue = [0, 0, 43]"] ;
35 | 12 -> 16 ;
36 | }


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/Presentations and Tutorials/Protvec demo 2017/README.md:
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 1 | ## Demonstration of biovec (protein sequence embeddings)
 2 | * Described by Asgari and Mofrat in [A Continuous Distributed Representation of Biological Sequences](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141287).  
 3 | 
 4 | This folder contains a notebook that shows how to use the [biovec](https://github.com/kyu999/biovec) module to generate vectors from protein sequences and how to use those for clustering and protein family classification (with deep learning).
 5 | 
 6 | ### Usage:
 7 | * Clone the repository with `git clone https://github.com/Team-SKI/snippets.git`
 8 | * Change directory to `Presentations and Tutorials/Protvec`
 9 | * Dowload biovec submodule with `git submodule init` followed by `git submodule update`
10 | * Run `jupyter notebook`
11 | 
12 | ### Dependencies:
13 | ```
14 | pandas
15 | numpy
16 | matplotlib
17 | scikit-learn
18 | gensim
19 | keras (with TensorFlow or Theano)
20 | seaborn
21 | ```
22 | 
23 | ##### License and copyright:
24 | 
25 | Copyright (C) 2017 by Sabrina Jaeger and Samo Turk, BioMed X GmbH
26 | 
27 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.
28 | 
29 | 
30 | 
31 | 
32 | 


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/Presentations and Tutorials/Protvec demo 2017/__init__.py:
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/Presentations and Tutorials/Protvec demo 2017/biovec/.gitignore:
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1 | data/
2 | dist/
3 | build/
4 | biovec.egg-info
5 | *__pycache__
6 | *pyc
7 | 


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/Presentations and Tutorials/Protvec demo 2017/biovec/README.md:
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 1 | BioVec
 2 | --------------------------------------
 3 | 
 4 | ### Example
 5 | 
 6 | ```
 7 | import biovec
 8 | 
 9 | pv = biovec.ProtVec("some_fasta_file.fasta", out="output_corpusfile_path.txt")
10 | pv["QAT"]
11 | pv.to_vecs("ATATQSQSMTEEL")
12 | pv.save('model_file_path')
13 | 
14 | pv2 = biovec.models.load_protvec('model_file_path')
15 | ```
16 | 
17 | ### Trained Model
18 | 
19 | This package includes already trained model in '/trained_models'.
20 | swissprot_reviewed_protvec is a protvec model fed all Swiss-Prot reviewed proteins(551,754 proteins as of 14/07/2016) as the training data.
21 | 
22 | # Source
23 | Paper: [ProtVec: A Continuous Distributed Representation of
24 | Biological Sequences](http://arxiv.org/pdf/1503.05140v1.pdf)
25 | 
26 | ### Abstract
27 | 通常生物情報は文字の配列で表現されるが、それをベクトルとして表現することによってより分析しやすく情報を収納することができるのではないかと提案されている。具体的な適用範囲としては、
28 | 
29 | 1. family classification
30 | 2. protein visualization
31 | 3. structure prediction
32 | 4. disordered protein identification
33 | 5. protein-protein interaction prediction.
34 | 
35 | など。
36 | classificationやpredictionはわかりやすい使い方だが、個人的にはprotein visualizationが最も効用が大きいのではないかと感じた。短い配列や、構造が既知の配列でない限り、現状簡単にタンパク質の全容を掴む方法が一般的に普及していないように感じるので、このような表現方法は一定の有用性があると考える。
37 | この考えは一見奇妙に映るが自然言語ではある程度認知されており、word2vecなどは記憶に新しい。
38 | 
39 | ### ProtVec実装
40 | 
41 | [前処理]
42 | * uniprotのswis-protの全データを収集する
43 | * 各配列を3つのn-gramのリストに変換する
44 | 
45 | ```
46 | 'AGAMQSASM' => [['AGA', 'MQS', 'ASM'], ['GAM','QSA'], ['AMQ', 'SAS']]
47 | ```
48 | 
49 | * word2vecに読み込ませるために、変換した配列をテキストファイル形式に書き出す
50 | 
51 | [モデル構築]
52 | 
53 | word2vecのライブラリを用いれば基本大丈夫そう。
54 | いろいろあるけど、gensimをここでは使う。ただしSkip-gramを論文では採用しているので注意。
55 | gensimではsgパラメータを1に設定するとskip-gramになる。
56 | > sg defines the training algorithm. By default (sg=0), CBOW is used. Otherwise (sg=1), skip-gram is employed.
57 | 
58 | 前処理では上記のように単語をn-gramのリストへ変換するが、sequenceをqueryとしてモデルに投げるときは逆に再変換する必要がある。訓練済みモデルにn-gramを指定することで、対応するベクトルを得ることができる。論文ではそのベクトルの和をその配列に対応するベクトルとして扱っている。
59 | 
60 | ```
61 | seq = 'AGAMQSASM'
62 | n_grams = split_to_grams(seq)
63 | gram_vecs = [to_gram_vec(n_gram) for n_gram in n_grams]
64 | seq_vec = sum(gram_vecs)
65 | ```
66 | 
67 | 論文での、ベクトルの次元数は100。
68 | 元の配列に対応するベクトルはn-gramベクトルの和なので次元数は変わらず、100次元。
69 | negative samplingも行っているので忘れずに。
70 | 
71 | ### Visualization of ProtVec
72 | [sklearn.manifold.TSNE](http://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html)
73 | t-SNEによって2次元もしくは3次元に次元圧縮を行った後、可視化している。しかしこの圧縮方法が適しているのか、なぜこの方法を取ったのかは言及されていない。scikit-learnではt-SNEは非推奨されており、密なデータであればPCA、疎なデータであればTruncatedSVDが勧められている。圧縮後の次元数がとても低いためだろうか。
74 | 
75 | > It is highly recommended to use another dimensionality reduction method (e.g. PCA for dense data or TruncatedSVD for sparse data) to reduce the number of dimensions to a reasonable amount (e.g. 50) if the number of features is very high. This will suppress some noise and speed up the computation of pairwise distances between samples. For more tips see Laurens van der Maaten’s FAQ.
76 | 
77 | [Lipschitz continuity](http://izumi-math.jp/F_Wada/fixpoint_theorem.pdf)
78 | 
79 | ### Abstract of the paper
80 | 
81 | > We propose a new approach for representing biological sequences. This method, named protein-vectors or ProtVec for short, can be utilized in bioinformatics applications such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. Using the Skip-gram neural networks, protein sequences are represented with a single dense n-dimensional vector. This method was evaluated by classifying protein sequences obtained from Swiss-Prot belonging to 7,027 protein families where an average family classification accuracy of 94%±0.03% was obtained, outperforming existing family classification methods. In addition, our model was used to predict disordered proteins from structured proteins. Two databases of disordered sequences were used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups). Using support vector machine classifiers, FG-Nup sequences were distinguished from structured Protein Data Bank (PDB) sequences with 99.81\% accuracy, and unstructured DisProt sequences from structured DisProt sequences with 100.0\% accuracy. These results indicate that by only providing sequence data for various proteins into this model, information about protein structure can be determined with high accuracy. This so-called embedding model needs to be trained only once and can then be used to ascertain a diverse set of information regarding the proteins of interest. In addition, this representation can be considered as pre-training for various applications of deep learning in bioinformatics.
82 | 
83 | ### References
84 | 1. [Disordered Proteins](https://en.wikipedia.org/wiki/Intrinsically_disordered_proteins)
85 | 2. [DisProt](http://www.disprot.org/)
86 | 3. [gemsim word2vec](https://radimrehurek.com/gensim/models/word2vec.html)
87 | 4. [NIPS2013読み会: Distributed Representations of Words and Phrases and their Compositionality](http://www.slideshare.net/unnonouno/nips2013-distributed-representations-of-words-and-phrases-and-their-compositionality)
88 | 5. [Skip gram shirakawa_20141121
89 | ](http://www.slideshare.net/nttdata-msi/skip-gram-shirakawa20141121-41833306)
90 | 6. [論文紹介「Distributed Representations of Words and Phrases and their Compositionality」](http://qiita.com/nishio/items/3860fe198d65d173af6b)
91 | 7. [sklearn.manifold.TSNE](http://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html)
92 | 8. [Lipschitz continuity](http://izumi-math.jp/F_Wada/fixpoint_theorem.pdf)
93 | 


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/Presentations and Tutorials/Protvec demo 2017/biovec/biovec/__init__.py:
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1 | from .models import ProtVec
2 | 


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/Presentations and Tutorials/Protvec demo 2017/biovec/biovec/binary_amino.py:
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 1 | '''
 2 | Binary representation of amino acid residue and amino acid sequence
 3 | e.g.
 4 |     'A' => [0, 0, 0, 0, 0]
 5 |     'AGGP' => [[0, 0, 0, 0, 0], [0, 1, 1, 0, 1], [0, 1, 1, 0, 1], [0, 1, 1, 1, 1]]
 6 | '''
 7 | 
 8 | AMINO_ACID_BINARY_TABLE = {
 9 |     'A': [0, 0, 0, 0, 0],
10 |     'C': [0, 0, 0, 0, 1],
11 |     'D': [0, 0, 0, 1, 0],
12 |     'E': [0, 0, 0, 1, 1],
13 |     'F': [0, 0, 1, 0, 0],
14 |     'G': [0, 0, 1, 0, 1],
15 |     'H': [0, 0, 1, 1, 0],
16 |     'I': [0, 0, 1, 1, 1],
17 |     'K': [0, 1, 0, 0, 0],
18 |     'L': [0, 1, 0, 0, 1],
19 |     'M': [0, 1, 0, 1, 0],
20 |     'N': [0, 1, 0, 1, 1],
21 |     'P': [0, 1, 1, 0, 0],
22 |     'Q': [0, 1, 1, 0, 1],
23 |     'R': [0, 1, 1, 1, 1],
24 |     'S': [1, 0, 0, 0, 0],
25 |     'T': [1, 0, 0, 0, 1],
26 |     'V': [1, 0, 0, 1, 0],
27 |     'W': [1, 0, 0, 1, 1],
28 |     'Y': [1, 0, 1, 0, 0]
29 | }
30 | 
31 | 
32 | def convert_amino_to_binary(amino):
33 |     '''
34 |     Convert amino acid to 1-dimentional 5 length binary array
35 |     "A" => [0, 0, 0, 0, 0]
36 |     '''
37 |     if not AMINO_ACID_BINARY_TABLE.has_key(amino):
38 |         return None
39 |     return AMINO_ACID_BINARY_TABLE[amino]
40 | 
41 | 
42 | def convert_amino_acid_sequence_to_vector(sequence):
43 |     '''
44 |     "AGGP" => [[0, 0, 0, 0, 0], [0, 1, 1, 0, 1], [0, 1, 1, 0, 1], [0, 1, 1, 1, 1]]
45 |     '''
46 |     binary_vector = [convert_amino_to_binary(amino) for amino in sequence]
47 |     if None in binary_vector:
48 |         return None
49 |     return binary_vector
50 | 


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/Presentations and Tutorials/Protvec demo 2017/biovec/biovec/models.py:
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 1 | from gensim.models import word2vec
 2 | from Bio import SeqIO
 3 | import sys
 4 | from gensim.models import word2vec
 5 | 
 6 | 
 7 | def split_ngrams(seq, n):
 8 |     """
 9 |     'AGAMQSASM' => [['AGA', 'MQS', 'ASM'], ['GAM','QSA'], ['AMQ', 'SAS']]
10 |     """
11 |     a, b, c = zip(*[iter(seq)]*n), zip(*[iter(seq[1:])]*n), zip(*[iter(seq[2:])]*n)
12 |     str_ngrams = []
13 |     for ngrams in [a,b,c]:
14 |         x = []
15 |         for ngram in ngrams:
16 |             x.append("".join(ngram))
17 |         str_ngrams.append(x)
18 |     return str_ngrams
19 | 
20 | 
21 | def generate_corpusfile(corpus_fname, n, out):
22 |     '''
23 |     Args:
24 |         corpus_fname: corpus file name
25 |         n: the number of chunks to split. In other words, "n" for "n-gram"
26 |         out: output corpus file path
27 |     Description:
28 |         Protvec uses word2vec inside, and it requires to load corpus file
29 |         to generate corpus.
30 |     '''
31 |     f = open(out, "w")
32 |     for r in SeqIO.parse(corpus_fname, "fasta"):
33 |         ngram_patterns = split_ngrams(r.seq, n)
34 |         for ngram_pattern in ngram_patterns:
35 |             f.write(" ".join(ngram_pattern) + "\n")
36 |         sys.stdout.write(".")
37 | 
38 |     f.close()
39 | 
40 | 
41 | def load_protvec(model_fname):
42 |     return word2vec.Word2Vec.load(model_fname)
43 | 
44 | 
45 | class ProtVec(word2vec.Word2Vec):
46 | 
47 |     def __init__(self, corpus_fname=None, corpus=None, n=3, size=100, out="corpus.txt",  sg=1, window=25, min_count=2, workers=3):
48 |         """
49 |         Either fname or corpus is required.
50 | 
51 |         corpus_fname: fasta file for corpus
52 |         corpus: corpus object implemented by gensim
53 |         n: n of n-gram
54 |         out: corpus output file path
55 |         min_count: least appearance count in corpus. if the n-gram appear k times which is below min_count, the model does not remember the n-gram
56 |         """
57 | 
58 |         self.n = n
59 |         self.size = size
60 |         self.corpus_fname = corpus_fname
61 | 
62 |         if corpus is None and corpus_fname is None:
63 |             raise Exception("Either corpus_fname or corpus is needed!")
64 | 
65 |         if corpus_fname is not None:
66 |             print 'Generate Corpus file from fasta file...'
67 |             generate_corpusfile(corpus_fname, n, out)
68 |             corpus = word2vec.Text8Corpus(out)
69 | 
70 |         word2vec.Word2Vec.__init__(self, corpus, size=size, sg=sg, window=window, min_count=min_count, workers=workers)
71 | 
72 |     def to_vecs(self, seq):
73 |         """
74 |         convert sequence to three n-length vectors
75 |         e.g. 'AGAMQSASM' => [ array([  ... * 100 ], array([  ... * 100 ], array([  ... * 100 ] ]
76 |         """
77 |         ngram_patterns = split_ngrams(seq, self.n)
78 | 
79 |         protvecs = []
80 |         for ngrams in ngram_patterns:
81 |             ngram_vecs = []
82 |             for ngram in ngrams:
83 |                 try:
84 |                     ngram_vecs.append(self[ngram])
85 |                 except:
86 |                     raise Exception("Model has never trained this n-gram: " + ngram)
87 |             protvecs.append(sum(ngram_vecs))
88 |         return protvecs
89 | 


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/Presentations and Tutorials/Protvec demo 2017/biovec/setup.py:
--------------------------------------------------------------------------------
 1 | from setuptools import setup
 2 | 
 3 | setup(name='biovec',
 4 |       version='0.1',
 5 |       description='The implementation of biovec',
 6 |       url='https://github.com/kyu999/biovec',
 7 |       author='Takashi Kyue',
 8 |       author_email='kyukokkyou999@gmail.com',
 9 |       license='MIT',
10 |       packages=['biovec'],
11 |       zip_safe=False)
12 | 


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/Presentations and Tutorials/Protvec demo 2017/biovec/trained_models/swissprot_reviewed_protvec:
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https://raw.githubusercontent.com/Team-SKI/snippets/1fc4d05e544c29a7376415a6a7223af302f98788/Presentations and Tutorials/Protvec demo 2017/biovec/trained_models/swissprot_reviewed_protvec


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/Presentations and Tutorials/Protvec demo 2017/data/uniprot_sprot_small.fasta:
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  1 | >sp|Q6GZX4|001R_FRG3G Putative transcription factor 001R OS=Frog virus 3 (isolate Goorha) GN=FV3-001R PE=4 SV=1
  2 | MAFSAEDVLKEYDRRRRMEALLLSLYYPNDRKLLDYKEWSPPRVQVECPKAPVEWNNPPS
  3 | EKGLIVGHFSGIKYKGEKAQASEVDVNKMCCWVSKFKDAMRRYQGIQTCKIPGKVLSDLD
  4 | AKIKAYNLTVEGVEGFVRYSRVTKQHVAAFLKELRHSKQYENVNLIHYILTDKRVDIQHL
  5 | EKDLVKDFKALVESAHRMRQGHMINVKYILYQLLKKHGHGPDGPDILTVKTGSKGVLYDD
  6 | SFRKIYTDLGWKFTPL
  7 | >sp|Q6GZX3|002L_FRG3G Uncharacterized protein 002L OS=Frog virus 3 (isolate Goorha) GN=FV3-002L PE=4 SV=1
  8 | MSIIGATRLQNDKSDTYSAGPCYAGGCSAFTPRGTCGKDWDLGEQTCASGFCTSQPLCAR
  9 | IKKTQVCGLRYSSKGKDPLVSAEWDSRGAPYVRCTYDADLIDTQAQVDQFVSMFGESPSL
 10 | AERYCMRGVKNTAGELVSRVSSDADPAGGWCRKWYSAHRGPDQDAALGSFCIKNPGAADC
 11 | KCINRASDPVYQKVKTLHAYPDQCWYVPCAADVGELKMGTQRDTPTNCPTQVCQIVFNML
 12 | DDGSVTMDDVKNTINCDFSKYVPPPPPPKPTPPTPPTPPTPPTPPTPPTPPTPRPVHNRK
 13 | VMFFVAGAVLVAILISTVRW
 14 | >sp|Q197F8|002R_IIV3 Uncharacterized protein 002R OS=Invertebrate iridescent virus 3 GN=IIV3-002R PE=4 SV=1
 15 | MASNTVSAQGGSNRPVRDFSNIQDVAQFLLFDPIWNEQPGSIVPWKMNREQALAERYPEL
 16 | QTSEPSEDYSGPVESLELLPLEIKLDIMQYLSWEQISWCKHPWLWTRWYKDNVVRVSAIT
 17 | FEDFQREYAFPEKIQEIHFTDTRAEEIKAILETTPNVTRLVIRRIDDMNYNTHGDLGLDD
 18 | LEFLTHLMVEDACGFTDFWAPSLTHLTIKNLDMHPRWFGPVMDGIKSMQSTLKYLYIFET
 19 | YGVNKPFVQWCTDNIETFYCTNSYRYENVPRPIYVWVLFQEDEWHGYRVEDNKFHRRYMY
 20 | STILHKRDTDWVENNPLKTPAQVEMYKFLLRISQLNRDGTGYESDSDPENEHFDDESFSS
 21 | GEEDSSDEDDPTWAPDSDDSDWETETEEEPSVAARILEKGKLTITNLMKSLGFKPKPKKI
 22 | QSIDRYFCSLDSNYNSEDEDFEYDSDSEDDDSDSEDDC
 23 | >sp|Q197F7|003L_IIV3 Uncharacterized protein 003L OS=Invertebrate iridescent virus 3 GN=IIV3-003L PE=4 SV=1
 24 | MYQAINPCPQSWYGSPQLEREIVCKMSGAPHYPNYYPVHPNALGGAWFDTSLNARSLTTT
 25 | PSLTTCTPPSLAACTPPTSLGMVDSPPHINPPRRIGTLCFDFGSAKSPQRCECVASDRPS
 26 | TTSNTAPDTYRLLITNSKTRKNNYGTCRLEPLTYGI
 27 | >sp|Q6GZX2|003R_FRG3G Uncharacterized protein 3R OS=Frog virus 3 (isolate Goorha) GN=FV3-003R PE=3 SV=1
 28 | MARPLLGKTSSVRRRLESLSACSIFFFLRKFCQKMASLVFLNSPVYQMSNILLTERRQVD
 29 | RAMGGSDDDGVMVVALSPSDFKTVLGSALLAVERDMVHVVPKYLQTPGILHDMLVLLTPI
 30 | FGEALSVDMSGATDVMVQQIATAGFVDVDPLHSSVSWKDNVSCPVALLAVSNAVRTMMGQ
 31 | PCQVTLIIDVGTQNILRDLVNLPVEMSGDLQVMAYTKDPLGKVPAVGVSVFDSGSVQKGD
 32 | AHSVGAPDGLVSFHTHPVSSAVELNYHAGWPSNVDMSSLLTMKNLMHVVVAEEGLWTMAR
 33 | TLSMQRLTKVLTDAEKDVMRAAAFNLFLPLNELRVMGTKDSNNKSLKTYFEVFETFTIGA
 34 | LMKHSGVTPTAFVDRRWLDNTIYHMGFIPWGRDMRFVVEYDLDGTNPFLNTVPTLMSVKR
 35 | KAKIQEMFDNMVSRMVTS
 36 | >sp|Q6GZX1|004R_FRG3G Uncharacterized protein 004R OS=Frog virus 3 (isolate Goorha) GN=FV3-004R PE=4 SV=1
 37 | MNAKYDTDQGVGRMLFLGTIGLAVVVGGLMAYGYYYDGKTPSSGTSFHTASPSFSSRYRY
 38 | >sp|Q197F5|005L_IIV3 Uncharacterized protein 005L OS=Invertebrate iridescent virus 3 GN=IIV3-005L PE=3 SV=1
 39 | MRYTVLIALQGALLLLLLIDDGQGQSPYPYPGMPCNSSRQCGLGTCVHSRCAHCSSDGTL
 40 | CSPEDPTMVWPCCPESSCQLVVGLPSLVNHYNCLPNQCTDSSQCPGGFGCMTRRSKCELC
 41 | KADGEACNSPYLDWRKDKECCSGYCHTEARGLEGVCIDPKKIFCTPKNPWQLAPYPPSYH
 42 | QPTTLRPPTSLYDSWLMSGFLVKSTTAPSTQEEEDDY
 43 | >sp|Q6GZX0|005R_FRG3G Uncharacterized protein 005R OS=Frog virus 3 (isolate Goorha) GN=FV3-005R PE=4 SV=1
 44 | MQNPLPEVMSPEHDKRTTTPMSKEANKFIRELDKKPGDLAVVSDFVKRNTGKRLPIGKRS
 45 | NLYVRICDLSGTIYMGETFILESWEELYLPEPTKMEVLGTLESCCGIPPFPEWIVMVGED
 46 | QCVYAYGDEEILLFAYSVKQLVEEGIQETGISYKYPDDISDVDEEVLQQDEEIQKIRKKT
 47 | REFVDKDAQEFQDFLNSLDASLLS
 48 | >sp|Q91G88|006L_IIV6 Putative KilA-N domain-containing protein 006L OS=Invertebrate iridescent virus 6 GN=IIV6-006L PE=3 SV=1
 49 | MDSLNEVCYEQIKGTFYKGLFGDFPLIVDKKTGCFNATKLCVLGGKRFVDWNKTLRSKKL
 50 | IQYYETRCDIKTESLLYEIKGDNNDEITKQITGTYLPKEFILDIASWISVEFYDKCNNII
 51 | INYFVNEYKTMDKKTLQSKINEVEEKMQKLLNEKEEELQEKNDKIDELILFSKRMEEDRK
 52 | KDREMMIKQEKMLRELGIHLEDVSSQNNELIEKVDEQVEQNAVLNFKIDNIQNKLEIAVE
 53 | DRAPQPKQNLKRERFILLKRNDDYYPYYTIRAQDINARSALKRQKNLYNEVSVLLDLTCH
 54 | PNSKTLYVRVKDELKQKGVVFNLCKVSISNSKINEEELIKAMETINDEKRDV
 55 | >sp|Q6GZW9|006R_FRG3G Uncharacterized protein 006R OS=Frog virus 3 (isolate Goorha) GN=FV3-006R PE=4 SV=1
 56 | MYKMYFLKDQKFSLSGTIRINDKTQSEYGSVWCPGLSITGLHHDAIDHNMFEEMETEIIE
 57 | YLGPWVQAEYRRIKG
 58 | >sp|Q6GZW8|007R_FRG3G Uncharacterized protein 007R OS=Frog virus 3 (isolate Goorha) GN=FV3-007R PE=4 SV=1
 59 | MRSIKPLRCCNAHGRHVSQEYGRCTLLLFREKLFLQTGLVCNKQCNAPNNDGAESKHHGI
 60 | HHGSRGALALRGAGVHLLASAALGPRVLAGLVPTGRSVQGSVGQCGRVAQIGRARDVAAR
 61 | KQESYCEK
 62 | >sp|Q197F3|007R_IIV3 Uncharacterized protein 007R OS=Invertebrate iridescent virus 3 GN=IIV3-007R PE=4 SV=1
 63 | MEAKNITIDNTTYNFFKFYNINQPLTNLKYLNSERLCFSNAVMGKIVDDASTITITYHRV
 64 | YFGISGPKPRQVADLGEYYDVNELLNYDTYTKTQEFAQKYNSLVKPTIDAKNWSGNELVL
 65 | LVGNEWYCKTFGKAGSKNVFLYNMIPTIYRDEPQHQEQILKKFMFFNATKNVEQNPNFLD
 66 | NVPEEYYHLLLPKSWVEKNLSDKYRKIMETEHKPLVFSCEPAFSFGLCRNTQDKNESYQL
 67 | SLCLYEREKPRDAEIVWAAKYDELAAMVRDYLKKTPEFKKYRSFISCMKGLSWKNNEIGD
 68 | KDGPKLYPKVIFNRKKGEFVTIFTKDDDVEPETIEDPRTILDRRCVVQAALRLESVFVHN
 69 | KVAIQLRINDVLISEWKEASSKPQPLILRRHRFTKPSSSVAKSTSPSLRNSGSDESDLNQ
 70 | SDSDKEDERVVPVPKTKRIVKTVKLPN
 71 | >sp|Q197F2|008L_IIV3 Uncharacterized protein 008L OS=Invertebrate iridescent virus 3 GN=IIV3-008L PE=4 SV=1
 72 | MSFKVYDPIAELIATQFPTSNPDLQIINNDVLVVSPHKITLPMGPQNAGDVTNKAYVDQA
 73 | VMSAAVPVASSTTVGTIQMAGDLEGSSGTNPIIAANKITLNKLQKIGPKMVIGNPNSDWN
 74 | NTQEIELDSSFRIVDNRLNAGIVPISSTDPNKSNTVIPAPQQNGLFYLDSSGRVWVWAEH
 75 | YYKCITPSRYISKWMGVGDFQELTVGQSVMWDSGRPSIETVSTQGLEVEWISSTNFTLSS
 76 | LYLIPIVVKVTICIPLLGQPDQMAKFVLYSVSSAQQPRTGIVLTTDSSRSSAPIVSEYIT
 77 | VNWFEPKSYSVQLKEVNSDSGTTVTICSDKWLANPFLDCWITIEEVG
 78 | >sp|Q6GZW6|009L_FRG3G Putative helicase 009L OS=Frog virus 3 (isolate Goorha) GN=FV3-009L PE=4 SV=1
 79 | MDTSPYDFLKLYPWLSRGEADKGTLLDAFPGETFEQSLASDVAMRRAVQDDPAFGHQKLV
 80 | ETFLSEDTPYRELLLFHAPGTGKTCTVVSVAERAKEKGLTRGCIVLARGAALLRNFLHEL
 81 | VFNCGTGGRYIPEGYADMGDQERTRKMRKAVSSYYQFRTYETFAKSVATMSAEAIRARYD
 82 | RFVIVMDEVHHLRSVQAEGVNTYSAISRFLRTVRGCVKMLLTGTPMTNEPGELADVLNLI
 83 | LPQDKTIRPEDGIFSNSGDLLKPDELAERVRGRVSYLKAARPDAGLTFAGEVLGGTGMTH
 84 | LRLVRLEMSAFQSDAYASAWDQDAGDRNIFSNSRQCSLAVMPDRRWGSAAEARNPSQVRR
 85 | MAGQNLAEYSVKYDYLVRVASSSPKTFAYCEYVNGSGLSLLSDILLANGWRRATGRETTP
 86 | GKRFALLTASQKNIHKIVQRFNHEDNVDGAYISLLLGSRVVAEGLTFKEVRHTVILTPHW
 87 | NYTETAQAIARSWRAGSHDRLKARGEAVAVTVHRLVAVPRGRDTPRSIDSDMYAVSEVKD
 88 | KRIKAVERILMTSAADCSLLRSRNLYPSEFDGSRECEYGRCAYRCSNVSVEPGPLPALLG
 89 | ASAAEAVAQVRLDGGGDPAIMKVDMSTLWAEVTAGRRYVNRWGDGAVLRAEGGRLELSAP
 90 | YGSSEEGRWGDFYKTRNLCYAKMDQDHLRADDLRDSLPQEVEELLTVSPVETIGETASAM
 91 | PQEVATAILMACVQARADGKTLNVVRRDALLDFYKGFYAMGPSGWTVWLHARGANAKVYD
 92 | GRRWNPADEDTLEFLAARSAKFTDTRIGYYGLYNPNLKDFCIRDVTQGKRDKVDLRKLTV
 93 | GRRCVDWDQRTLVHIVARLMKIDGRRDFMPHATLREMRELAEQDPLHEPSDLTSKEACRR
 94 | FLFWTQKGDNKFRRQDICKAMEKWFIENDLMEDNFDCGHQHKRRGKFA
 95 | >sp|Q91G85|009R_IIV6 Uncharacterized protein 009R OS=Invertebrate iridescent virus 6 GN=IIV6-009R PE=3 SV=1
 96 | MIKLFCVLAAFISINSACQSSHQQREEFTVATYHSSSICTTYCYSNCVVASQHKGLNVES
 97 | YTCDKPDPYGRETVCKCTLIKCHDI
 98 | >sp|Q6GZW5|010R_FRG3G Uncharacterized protein 010R OS=Frog virus 3 (isolate Goorha) GN=FV3-010R PE=4 SV=1
 99 | MKMDTDCRHWIVLASVPVLTVLAFKGEGALALAGLLVMAAVAMYRDRTEKKYSAARAPSP
100 | IAGHKTAYVTDPSAFAAGTVPVYPAPSNMGSDRFEGWVGGVLTGVGSSHLDHRKFAERQL
101 | VDRREKMVGYGWTKSFF
102 | >sp|Q197E9|011L_IIV3 Uncharacterized protein 011L OS=Invertebrate iridescent virus 3 GN=IIV3-011L PE=4 SV=1
103 | MMESPKYKKSTCSVTNLGGTCILPQKGATAPKAKDVSPELLVNKMDNLCQDWARTRNEYN
104 | KVHIEQAPTDSYFGVVHSHTPKKKYTSRDSDSEPEATSTRRSATAQRAANLKSSPVDQWS
105 | TTPPQPQPQPAAPTVKKTCASSPPAALSVKRTCTSPPPPPVLIDDDTGEDAFYDTNDPDI
106 | FYDIENGVSELETEGPKRPVYYQRNIRYPIDGSVPQESEQWYDPIDDEFLASSGDVVSLE
107 | PSPIAAFQPTPPKTVQFVPMPEEIIVPPPPPPKTVVDEGVQAMPYTVDQMIQTDFEESPL
108 | LANVNLRTIPIEEVNPNFSPVLMQDMVRDSFVFGTVAQRVMASQRVKQFFKELIEQDVSL
109 | AGRMCMDSGSPQLNLYNSLMGVKLLYRWRSSTTFYRAIVPEIDEPVQVMQDVLSSSEWAK
110 | FDSQAGIPPKMVYIHYKLLNDLVKTLICPNFQLTHAALVCVDCRPEAVGSDGLQDGRQRR
111 | CSNLVSEYHEMTLEDLFNTIKPADLNAKNIILSVLFQMLYAVATVQKQFGMGGLFANADS
112 | VHVRRIQPGGFWHYTVNGLRYSVPNYGYLVILTNFTDVVNYRPDFATTRYFGRRQAKVVP
113 | TRNWYKFVPFTTRYRPFVTVDPITQAKTTAYAPNPPTEGITINEFYKDSSDLRPSVPVDL
114 | NDMITFPVPEFHLTICRLFSFFSKFYDSNFIGNDPFVRNLVDRYSQPFEFPDVYWPEDGV
115 | SRVLACYTIEEIYPNWVDGDTDYVIESYNLD
116 | >sp|Q6GZW4|011R_FRG3G Uncharacterized protein 011R OS=Frog virus 3 (isolate Goorha) GN=FV3-011R PE=4 SV=1
117 | MTSVKTIAMLAMLVIVAALIYMGYRTFTSMQSKLNELESRVNAPQLRPPVMSPIVPLNFI
118 | ESEDLDKELD
119 | >sp|Q6GZW3|012L_FRG3G Uncharacterized protein 012L OS=Frog virus 3 (isolate Goorha) GN=FV3-012L PE=4 SV=1
120 | MCAKLVEMAFGPVNADSPPLTAEEKESAVEKLVGSKPFPALKKKYHDKVPAQDPKYCLFS
121 | FVEVLPSCDIKAAGAEEMCSCCIKRRRGQVFGVACVRGTAHTLAKAKQKADKLVGDYDSV
122 | HVVQTCHVGRPFPLVSSGMAQETVAPSAMEAAEAAMDAKSAEKRKERMRQKLEMRKREQE
123 | IKARNRKLLEDPSCDPDAEEETDLERYATLRVKTTCLLENAKNASAQIKEYLASMRKSAE
124 | AVVAMEAADPTLVENYPGLIRDSRAKMGVSKQDTEAFLKMSSFDCLTAASELETMGF
125 | >sp|Q197E7|013L_IIV3 Uncharacterized protein IIV3-013L OS=Invertebrate iridescent virus 3 GN=IIV3-013L PE=4 SV=1
126 | MYYRDQYGNVKYAPEGMGPHHAASSSHHSAQHHHMTKENFSMDDVHSWFEKYKMWFLYAL
127 | ILALIFGVFMWWSKYNHDKKRSLNTASIFY
128 | >sp|Q6GZW2|013R_FRG3G Uncharacterized protein 013R OS=Frog virus 3 (isolate Goorha) GN=FV3-013R PE=4 SV=1
129 | MANSVAFSSMTWYSPLASDNLYDICVDKVHNRVLCLCHSFGCCTNAVVIWILPSFDEFTP
130 | QTLSCKGP
131 | >sp|Q6GZW1|014R_FRG3G Uncharacterized protein 014R OS=Frog virus 3 (isolate Goorha) GN=FV3-014R PE=4 SV=1
132 | METLVQAYLDIQGKIAEFRREIKALRVEEKAITANLFEAMGEAGVESIRISEDRYLVAEE
133 | KPKRTRSKQQFYQAAEGEGFTQEDVDRLMSLSRGAVTGSSSNVKIRKSAPARNEEDDDG
134 | >sp|Q6GZW0|015R_FRG3G Uncharacterized protein 015R OS=Frog virus 3 (isolate Goorha) GN=FV3-015R PE=4 SV=1
135 | MEQVPIKEMRLSDLRPNNKSIDTDLGGTKLVVIGKPGSGKSTLIKALLDSKRHIIPCAVV
136 | ISGSEEANGFYKGVVPDLFIYHQFSPSIIDRIHRRQVKAKAEMGSKKSWLLVVIDDCMDN
137 | AKMFNDKEVRALFKNGRHWNVLVVIANQYVMDLTPDLRSSVDGVFLFRENNVTYRDKTYA
138 | NFASVVPKKLYPTVMETVCQNYRCMFIDNTKATDNWHDSVFWYKAPYSKSAVAPFGARSY
139 | WKYACSKTGEEMPAVFDNVKILGDLLLKELPEAGEALVTYGGKDGPSDNEDGPSDDEDGP
140 | SDDEEGLSKDGVSEYYQSDLDD
141 | >sp|Q6GZV8|017L_FRG3G Uncharacterized protein 017L OS=Frog virus 3 (isolate Goorha) GN=FV3-017L PE=4 SV=1
142 | METMSDYSKEVSEALSALRGELSALSAAISNTVRAGSYSAPVAKDCKAGHCDSKAVLKSL
143 | SRSARDLDSAVEAVSSNCEWASSGYGKQIARALRDDAVRVKREVESTRDAVDVVTPSCCV
144 | QGLAEEAGKLSEMAAVYRCMATVFETADSHGVREMLAKVDGLKQTMSGFKRLLGKTAEID
145 | GLSDSVIRLGRSIGEVLPATEGKAMRDLVKQCERLNGLVVDGSRKVEEQCSKLRDMASQS
146 | YVVADLASQYDVLGGKAQEALSASDALEQAAAVALRAKAAADAVAKSLDSLDVKKLDRLL
147 | EQASAVSGLLAKKNDLDAVVTSLAGLEALVAKKDELYKICAAVNSVDKSKLELLNVKPDR
148 | LKSLTEQTVVVSQMTTALATFNEDKLDSVLGKYMQMHRFLGMATQLKLMSDSLAEFQPAK
149 | MAQMAAAASQLKDFLTDQTVSRLEKVSAAVDATDVTKYASAFSDGGMVSDMTKAYETVKA
150 | FAAVVNSLDSKKLKLVAECAKK
151 | >sp|Q6GZV7|018L_FRG3G Uncharacterized protein 018L OS=Frog virus 3 (isolate Goorha) GN=FV3-018L PE=3 SV=1
152 | MQNSKTDMCAALWAVTGLVLNVAVRFALEPFKESMGQGWHTAARVAVNGAIVLALADRLS
153 | DSPVTMTLFVMALSASPE
154 | >sp|Q6GZV6|019R_FRG3G Putative serine/threonine-protein kinase 019R OS=Frog virus 3 (isolate Goorha) GN=FV3-019R PE=3 SV=1
155 | MATNYCDEFERNPTRNPRTGRTIKRGGPVFRALERECSDGAARVFPAAAVRGAAAARAAS
156 | PRVAAASPCPEFARDPTRNPRTGRPIKRGGPVFRALERECADYGGASPRRVSPARAFPNR
157 | RVSPARRQSPAEAAEASPCPEFARDPTRNPRTGRTIKRGGPTYRALEAECADYGRLSPIR
158 | SPWSDWSSTGLSPFRSHMRKSPARRSPARRSPARRSLARYTEHLTSDSETEVDYDARNVI
159 | RSQVGPGGVCERFAADPTRNPVTGSPLSRNDPLYTDLMEICKGYPDTPLTKSLTGEGTDD
160 | DTCEAFCRDPTRNPVTGQKMRRNGIEYQMFAEECDCSGISRPSGVSRTSGTSGSSGSSAS
161 | SRPPNSFEAPGASSRPPNSFEASGAARVPGTPSVSRGEPRWMSSISTRHNYDESNPMSVA
162 | FRLRHVKDIRKFLRTVRPGRSGFCATDKGGWLGSAAVSDNVIGQGSWGSVHMVKFRDFPE
163 | EFVVKEAVLMSVSEKHRYKPTVVWDEWAAGSVPDEVVVNNMVTEIAATGMTPFVPLTAGA
164 | GACDSCNPQLLEKAAKVTKCYLQAMEAADFSLDRVLPTMSPDQAASALAQILLGLQSLQT
165 | TLGIMHNDIKAHNILVKRVPPGGYWKVTDSFNGQVFYIPNEGYLCMLADYGVVRLVKPAV
166 | GMDTLYGTRNARFVPRDVGRWGKGAGTEYVVTPIRSKISVVVRGGRFVGVEPNKAVRYWK
167 | NTDTSKVGDVITTNNVFYMGYDIEPDMQVQLDDTNSFPVWESRGDVADCVRTFVGGKRAS
168 | QPGFHRLFYKKTGSAWEKAAETVAKQNPLFSGFTLDGSGLKYIRAATACAYIFPGMAVPR
169 | PGEREIESFTM
170 | >sp|Q6GZV5|020R_FRG3G Uncharacterized protein 020R OS=Frog virus 3 (isolate Goorha) GN=FV3-020R PE=4 SV=1
171 | MLQNYAIVLGMAVAVAIWYFFKIEEEAPPGPNPPKPDPPKPDPPKMHMPKKKPHWMDPHL
172 | TGSQTVQYSRNRSMGDPIRGDLPIIPRDDGWFSTAANPAHTLHAGALSMIAPASTGGGLT
173 | VNKLISAYADKGNAMSGRHNSPSYYGSS
174 | >sp|Q6GZV4|021L_FRG3G Uncharacterized protein 021L OS=Frog virus 3 (isolate Goorha) GN=FV3-021L PE=4 SV=1
175 | METIVLVPRQDQETFSDSRPVLDGDLMLEFLENKIRHPVRRRQPRVVPVTSSDPEVVDDE
176 | DDEDQSDDSDEERQRLYFQYMVLKRMYPTEVIPEMTTYSNVAIMREKYKLLTRRLSLDKH
177 | INEWKKYIIVGMCIMELVMTKLNFDASGFARYQIKSLGAYDQLLAEMADKYYEATPQSSV
178 | EMRLMTTMGMNMAVFMLGKLLGGQMDFLGLLENAFGSSS
179 | >sp|Q197D8|022L_IIV3 Transmembrane protein 022L OS=Invertebrate iridescent virus 3 GN=IIV3-022L PE=4 SV=1
180 | MSFVHKLPTFYTAGVGAIIGGLSLRFNGAKFLSDWYINKYNDSVPAWSLQTCHWAGIALY
181 | CVGWVTLASVIYLKHRDNSILKGSILSCIVISAVWSILEYNQDMFVSNPKLPLISCAMLV
182 | SSLAALVALKYHIKDIFTILGAAIIIILAEYVVLPYQRQYNIVDGIGLPLLLLGFFILYQ
183 | VFSVPNPSTPTGVMVPKPEDEWDIEMAPLNHRDRQVPESELENVK
184 | >sp|Q6GZV2|023R_FRG3G Uncharacterized protein 023R OS=Frog virus 3 (isolate Goorha) GN=FV3-023R PE=4 SV=1
185 | MRVSQTSWIVSRMLEYPRGGFFYSTDMACMMEGLAEELAGGHKDEVLIVSGRNGDDEVFK
186 | EFPNVRAADGLKGPNSIDPETKLVLIIDVSPTAISNALAATLQEFLIPVWVFCNHTRTLT
187 | ASVTRRLGYKLWPKGTYTPYICEKAGVSEVVTYNQPESEKFVAFMSAARQIMDKRKSKKT
188 | MQELAFLPHLAFAEIAMEGDQEMTPTLTAKKVSDIKDEQVNELASAMFRTGKLSHLDMLS
189 | VPDCVYSCGEALKREVAKAKANRERFVVALRNAQYKKYTAGLLEAGTPVKTFTEVIKNWG
190 | AYDTIFLPMGVDWTYTGGSNLIRMMMTPGSHKTVTFVPESDDVHEFCHNKPTVNTMGVES
191 | AATGLAAELNRRWRRDNPVDAS
192 | >sp|Q197D7|023R_IIV3 Uncharacterized protein 023R OS=Invertebrate iridescent virus 3 GN=IIV3-023R PE=4 SV=1
193 | MGSYMLFDSLIKLVENRNPLNHEQKLWLIDVINNTLNLEGKEKLYSLLIVHNKQQTKIYD
194 | PKEPFYDIEKIPVQLQLVWYEFTKMHLKSQNEDRRRKMSLYAGRSP
195 | >sp|Q6GZV1|024R_FRG3G Uncharacterized protein 024R OS=Frog virus 3 (isolate Goorha) GN=FV3-024R PE=3 SV=1
196 | MWQYLPILLMTMISQLEWTVAAVKRYPAGGFITGDKLSRVFEALPWRVAVVSDEPEKYEG
197 | FPILTEEDPAVFEDADCILFAVSDPKCVTGAMKSVFMASSKTAWVVYDGTETRATVRSWM
198 | RRLWRAETYVPLLTHRGFVTDVCVYSQPDSERYVSVMTATAHFYSNRLEVLEEMAFVPHL
199 | AYAKLAMGRYTVLDGCMSVKGSADVAPLNRSMWFLTAAAIPHGEIDTDSLFSDPGAVYSC
200 | GSALREALGSLPEGSTSVVAVRNSSYRKYVRGILGPNFRVETFTNVVKTWGVYDYVLLPM
201 | GISDSYKQGRDLMEKLEMPGGHRVVTFAPENYTVNEVHLNRPLKYAIKRMDLITPMVLRH
202 | VSLNK
203 | >sp|Q197D5|025R_IIV3 Uncharacterized protein 025R OS=Invertebrate iridescent virus 3 GN=IIV3-025R PE=3 SV=1
204 | MNYSVIWAITILILGLVLTLAWARQNPTHPINPLVLNYHTKPSPKRHRMVLVVESFASVD
205 | ALVELVENILSQTIRVASITVVSQRPDHLRQVPLLHQTCTFSRASGLSALFKETSGTLVV
206 | FISKEGFHHFQSPTLLETIDQRGVTAEQTLPGIVLRNTDMPGIDLTTVYRQQRLGLGN
207 | >sp|Q91G70|026R_IIV6 Uncharacterized protein 026R OS=Invertebrate iridescent virus 6 GN=IIV6-026R PE=4 SV=1
208 | MAISFFSDTSYIIKSILLISLFSIIPLEDEVTKLKSSSLRETSELNKEEGITTCLYTFN
209 | >sp|Q6GZU9|027R_FRG3G Uncharacterized protein 027R OS=Frog virus 3 (isolate Goorha) GN=FV3-027R PE=4 SV=1
210 | MANFLQDVNCETVSEYDGPDASIPEGVWEGYVGHDHAALWRTWSYIYECCKKGTLVQFRG
211 | GKLVTFSMFDNPRFSNGAGIDAQKVLDLEDRARELQGYGPVNRRTDVMPVDRWTLNGPLL
212 | RYDKMVLEDVGGTGSNRTMVRAQLEALQDERDVPDCDFILNVRDYPLLRRDGTRPYPQVY
213 | GKGRRLPEPWARGGPHVPVVSMCSGPTYADIAVPTYECIAHAYTSSGRTLPAGGRFVKTP
214 | SADSLPAWRDRKALAVFRGSSTGAGTSTEDNQRLRALQISMSRPDLADVGITKWNLRPRK
215 | TERYDGYRIIEPWQFGRKSPYPAAAKPMTPEQIAGYKYVLCLWGHAPAFRLARDLSLGSV
216 | VLLPSRPPGQEGLDMWHSSVLKPWTHYIPVRGDLSDLEKRIEWCRDNDAECEKIAAAGME
217 | ASLNLLGWEGQLDRWMDVLRSVRLECCPGGYDMPPSPSLVSDSMCVRQMVSFPRYEDIPQ
218 | PSSPMPVLPRCSGTLRGWGLAASLGWDLGDAAEVLNVKRSTAVLSKTVFNNLIYRTPHLR
219 | YTFGVAASDPESTAAVILSEKLKGAVTMRSWLEDSRAWARGRNVASVLCQVSQALLEAQA
220 | AAGTVFGDLSLDTILVVPNPLPEYIYHDGTGGSFGLKLMPGDKWAVVTYGDYTRARIRVL
221 | KGDGRKGHLAVVGPQPVYTKLSERKWHDICCLVSCILRTARTSKRPAARALAAAVARAAG
222 | VKRPDMDAEALEATPYEAREEPLTRFGPAEFINGLVREFKLEEGGWAWTEKNKNIEKVLR
223 | PWERGLPLYPVRLWLSGDRKEAMRACVSSVLKAAPPRPATAAGAHHTFQTYLRTVGADLD
224 | SFPEWAAAAAHLKRLWKSPGSLPAGSASLRAPSVPPPCHGPAWALPFGTRTPGEFPSWFD
225 | PSCLGDWTEAMGQGAPLDLENGPAKAGSDPVAVHSAWETASQLSFEEDGWTESEPRPVRR
226 | EAHVRAKERH
227 | >sp|Q6GZU8|028R_FRG3G Uncharacterized protein 028R OS=Frog virus 3 (isolate Goorha) GN=FV3-028R PE=4 SV=1
228 | MDPNVLKNLSLMLSRRAGVSGGEPPRMIEWPEYGQRSEPCGSQTVWYVDRPVGAPFIKAF
229 | ASEVEERGGGILIHAGKVTFDSAKKLAAMKEVQVFDVKYFSFDLMAVVPEHSLWKRPGDK
230 | GYPEKTAQSFPKIMASDPVCRYHGFRPRDLVHVKPHDVYIVC
231 | >sp|Q197D2|028R_IIV3 Uncharacterized protein 028R OS=Invertebrate iridescent virus 3 GN=IIV3-028R PE=4 SV=1
232 | MDQYITLVELYIYDCNLFKSKNLKSFYKVHRVPEGDIVPKRRGGQLAGVTKSWVETNLVH
233 | FPLWLSEWDETRWGVLNHYPLESWLEKNVSSKVPVNPVMWNFDSECLVYFFHNGRRTPFL
234 | TPKGVVKLQVFYNLMSGKEVEWFYEISNGFLKPHLHQLSNVRELVRLKHAPVVVGAGGPR
235 | LVTEGVYSLRDDDFVVDCSQIAAVKRAIERGESHQSLRKYQCPLFVALTDKFQDTVKLVE
236 | KKFEVQLNELKAETTIQVLREQLRQEKKLKEQVLSLTQSFIPTIGGRGEEFGKPDETPSS
237 | ASVGDDNFPSSTNHTFEARRRPSSLSSGGALKPSKIL
238 | >sp|Q6GZU7|029L_FRG3G Uncharacterized protein 029L OS=Frog virus 3 (isolate Goorha) GN=FV3-029L PE=4 SV=1
239 | MRRMRSGFKHCAIPIDICRWEYILSPLILQDLQGPQQGGSVAVDVTVRCSVRFVHLPHYG
240 | GFNHGTVQRRVDPDDCRILRQLHIVLSLRLCLIDRDRL
241 | >sp|Q91G67|029R_IIV6 Uncharacterized protein 029R OS=Invertebrate iridescent virus 6 GN=IIV6-029R PE=4 SV=1
242 | MVERLGIAVEDRSPKLRKQAIRERFVLFKKNTERVEKYEYYAIRGQSIYINGRLSKLQSE
243 | RYPKMIILLDIFCQPNPRNLFLRFKERIDGKSEWENNFTYAGNNIGCTKEMESDMIRIFN
244 | ELDDEKRDV
245 | >sp|Q197D0|030L_IIV3 uncharacterized protein 030L OS=Invertebrate iridescent virus 3 GN=IIV3-030L PE=4 SV=1
246 | MHPTLKSNAGEWSQPIVNLFYSNFSGNCKALLQYIDNAGITDHIPIKFINVDNPTMRSVV
247 | SAKISHVPALVVLQDDQMSLYVAESVWEWFDNYRTPPPLADGATVDSQASENGEKEAQPT
248 | PPKEGLLTVLELAKQMRKEREQQT
249 | >sp|Q6GZU6|030R_FRG3G Uncharacterized protein 030R OS=Frog virus 3 (isolate Goorha) GN=FV3-030L PE=4 SV=1
250 | MSLYLLLGLKILRYLKMVIVLRCHSAFLLSVKFLREKRRLKMYLGIMLGF
251 | >sp|Q6GZU5|031R_FRG3G Uncharacterized protein 031R OS=Frog virus 3 (isolate Goorha) GN=FV3-031R PE=4 SV=1
252 | MDTPCKLFCIELKEGYVPGTVSHNHMMPYFLAGSGWPVEITFHAATVELKTQEDFPPAIG
253 | IGIHNMTGVPVVETPHSGRMHFVFIFHSKSGRFSATYKCIPVPVVVRDYKTVASVSLTTL
254 | SLEDIVGVKLFGTACDRSS
255 | >sp|Q6GZU4|032R_FRG3G Uncharacterized protein 032R OS=Frog virus 3 (isolate Goorha) GN=FV3-032R PE=4 SV=1
256 | MVTVTELRATAKNLGIRGYSTMRKAELEEAIRDHGRVSEARVASPRRSPARSPRKSPAGR
257 | KSPSKSPAGRKSPSKSPAGRKSPSKSPAGRKSPSKSPAGRKSPSKSPAGRKSPSKSPVRK
258 | SPSKSPVRKSPRKSPAAKLQAGDRPASMNICKNLPKQRLVDIATEMGIDLNRESDGKPKT
259 | KDQLCADIMGGAGRKSPRKSPSRSPVRKSPSRSPVRKSPVRSPRKSPVRVPSPVRSPVKE
260 | KTPVRSPARSEDAGSDLAPRPRRGKAVRLDYDEDDDYSYGASTDNLFSGNKEIPFPTRKR
261 | RTRKPEKVFVDVRSPHTLTDSEDEDDMVEVPELEDKEITMPGVLSPYSDEIVERGYVSQG
262 | GADYINYIYRTEYALESDESFARGARPKTNKRDSDRAVREAAAAAAIARALDRRSQSGND
263 | EPAVRRRSAPTDSSRESRRDREPQRDIAEPQRDIAEPQRDIAEPQRDIAEPRKVRFREAG
264 | SADVRVFERDEPKEYGRVPVRPPLFMPAGEPLQPLKFRPKTPKIDDTIHRAQMVLPSKPS
265 | QKETDNYYKQFAGEAVRPSEPVQWDKDDQVLYHKVPAWDDSSYAAAVSAWPMSVDPKQAE
266 | SVFAEFEQLSAQDSDLIKVRKSIMKALGY
267 | >sp|Q197C8|032R_IIV3 Uncharacterized protein 032R OS=Invertebrate iridescent virus 3 GN=IIV3-032R PE=4 SV=1
268 | MKLMLEIVKNISEPVGKLAIWFNETYQVDVSETINKWNELTGMNITVQENAVSADDTTAE
269 | ETEYSVVVNENPTRTAARTRKESKTAAKPRKMQIPKTKDVCQHIFKSGSRAGEQCTTKPK
270 | NNALFCSAHRVRNSVTSNATEASEKTVAKTNGTAAPQKRGVKSKSPTVIPSDFDDSDSSS
271 | SATRGLRKAPTLSPRKPPPTTTTASSAQEEEDEQQAHFSGSSSPPPKNNGNGAVYSDSSS
272 | DEDDDDAHHTTVIPLLKKGARKPLDENVQFTSDSSDEED
273 | >sp|Q91G65|032R_IIV6 Uncharacterized protein 032R OS=Invertebrate iridescent virus 6 GN=IIV6-032R PE=4 SV=1
274 | MGVYKFCYNKKKEVGQVAVLQKERLIFYIVTKEKSYLKPTLANFSNAIDSLYNECLLRKC
275 | CKLAIPKIGCCLDRLYWKTVKNIIIDKLCKKGIEVVVYYI
276 | >sp|Q6GZU3|033R_FRG3G Transmembrane protein 033R OS=Frog virus 3 (isolate Goorha) GN=FV3-033R PE=4 SV=1
277 | MSGIQLDKETILKYSSAALVALSAVVAVMMVSNNSESWKPILVGAVVAASGAAAYQSWWP
278 | KQS
279 | >sp|Q6GZU2|034R_FRG3G Uncharacterized protein 034R OS=Frog virus 3 (isolate Goorha) GN=FV3-034R PE=4 SV=1
280 | MSAGHLRKRRYVKVGDIHDMGPILGGVHDVSSPPPNVHYQQQDDHNDPGCMIHYPGEGWF
281 | SSMSTVEKLMLGAVIVAAVVVGVRMFMSSGNSSATSSFSTAPYFMG
282 | >sp|Q91G63|034R_IIV6 Uncharacterized protein 034R OS=Invertebrate iridescent virus 6 GN=IIV6-034R PE=4 SV=1
283 | MKQNLLILLSLLLVVVAIMWWLYEKKKEVPLPPPTPPTPPTPTGVPFLPMYAGLSSPVQY
284 | NPADYLYGWEKYPHGPAWSFGDRVPYAEAKNALGGHFGGGLYSPRDPILESKLGGVYIGN
285 | DLYTVGGVGGDGHW
286 | >sp|Q6GZU1|035L_FRG3G Uncharacterized protein 035L OS=Frog virus 3 (isolate Goorha) GN=FV3-035L PE=4 SV=1
287 | MIWVWPATGRGPGWWGIRRDPWGPEDSSCPCPRLPLSPTGPVGHSGPMGQCHPPVPSYRR
288 | GRRDQKDPPLRRQTSPPLPPHPWDRPLPWVPWIPLDLCRHGDPRHPWDPGAQSGYPRVRE
289 | VRGVPADRPLRPCPRQGPRTAATRKESSCRIPS
290 | >sp|Q6GZU0|036L_FRG3G Uncharacterized protein 036L OS=Frog virus 3 (isolate Goorha) GN=FV3-036L PE=4 SV=1
291 | MTLPDVSGSLGPLSPGTNGTLWAVGPRVVRYQIPALAYLTPGALWTLRTRGTSLTSGPIG
292 | TRDSIRTLHAVHYDVWTLGPLGPLGPTSPRGPSARPCRLQTDSLHSTDARCYRCKMLQMQ
293 | DATDARCKKDMSPFSFPGILEPSHLVGSLKSPRVDPGVPCRPLALWGHPYQCLRLVPLYQ
294 | RCLHPHCFPAAPGRPWDPWCRPDRLDP
295 | >sp|Q197C3|037L_IIV3 Uncharacterized protein 037L OS=Invertebrate iridescent virus 3 GN=IIV3-037L PE=4 SV=1
296 | MNAATSGIQLNAQTLSQQPAMNTPLIHRSFRDDYTGLVSAGDGLYKRKLKVPSTTRCNKF
297 | KWCSIGWSIGALIIFLVYKLEKPHVQPTSNGNLSLIEPEKLVSESQLIQKILNATTPQTT
298 | TPEIPSSTEPQELVTEILNTTTPQTTTPEIPSSTEPQELVTEIPSSTEPQEEIFSIFKSP
299 | KPEEPGGINSIPQYEQESNNVEDEPPPNKPEEEEDHDNQPLEERHTVPILGDVIIRNKTI
300 | IIDGGNETIIIKP
301 | >sp|Q6GZT9|037R_FRG3G uncharacterized protein 037R OS=Frog virus 3 (isolate Goorha) GN=FV3-037R PE=4 SV=1
302 | MQVFLDLDETLIHSIPVSRLGWTKSKPYPVKPFTVQDAGTPLSVMMGSSKAVNDGRKRLA
303 | TRLSLFKRTVLTDHIMCWRPTLRTFLNGLFASGYKINVWTAASKPYALEVVKALNLKSYG
304 | MGLLVTAQDYPKGSVKRLKYLTGLDAVKIPLSNTAIVDDREEVKRAQPTRAVHIKPFTAS
305 | SANTACSESDELKRVTASLAIIAGRSRRR
306 | >sp|Q6GZT7|039R_FRG3G Uncharacterized protein 039R OS=Frog virus 3 (isolate Goorha) GN=FV3-039R PE=4 SV=1
307 | MTSYCDTLKALAAESDSTGSERATIRMYMAMFSDASLRPAVSDTVASILGTDSLDHEDAE
308 | MMLKFKLLFFSGSANASATSHYPKADDPQRFARSVSRGPSRVRRPARNSASRPVRR
309 | >sp|Q6GZT6|040R_FRG3G Uncharacterized protein 040R OS=Frog virus 3 (isolate Goorha) GN=FV3-040R PE=3 SV=1
310 | MIRALCTIVLIAAGVAVALYLSLVYGYYMSVGVQDASWLTALTGNRPDAKVPFFDKAVGE
311 | APEDKVAYTERPYPVSSTQSPTTTQSPTTTTLKPTTMAVLASIGATPTPVVCHNVRGDMQ
312 | GIACNVVMKKTVAAALKVQPEAKKDNVNAQYRYGMWTPLRRSRSPFGVWNIPKKLAIAAP
313 | DV
314 | >sp|Q197C0|040R_IIV3 Uncharacterized protein 040R OS=Invertebrate iridescent virus 3 GN=IIV3-040R PE=4 SV=1
315 | MVTMAIKNFHIQDDRLKNGRGNKTMSESDYNTSDSGGWVLVRKKRDRSTRPPDVVDRWSN
316 | STSTFPMGLDQIKIKRNGCVNTY
317 | >sp|Q91G57|041L_IIV6 Uncharacterized protein 041L OS=Invertebrate iridescent virus 6 GN=IIV6-041L PE=4 SV=1
318 | MNFIRENETKYVLSTYQSMTPKNLMEYLLKYNYDNDCVYIFNNLPKDLQKEVDDLAKEVV
319 | KANDEQIKAQDEQIKANDQKLKQLDVMIEFMKQYNKQLDNDIYLLEHQLENKRELNRQLG
320 | IF
321 | >sp|Q6GZT5|041R_FRG3G Uncharacterized protein 041R OS=Frog virus 3 (isolate Goorha) GN=FV3-041R PE=4 SV=1
322 | MRVVVNAKALEVPVGMSFTEWTRTLSPGSSPRFLAWNPVRPRTFKDVTDPFWNGKVFDLL
323 | GVVNGKDDLLFPASEIQEWLEYAPNVDLAELERIFVATHRHRGMMGFAAAVQDSLVHVDP
324 | DSVDVTRVKDGLHKELDEHASKAAATDVRLKRLRSVKPVDGFSDPVLIRTVFSVTVPEFG
325 | DRTAYEIVDSAVPTGSCPYISAGPFVKTIPGFKPAPEWPAQTAHAEGAVFFKADAEFPDT
326 | KPLKDMYRKYSGAAVVPGDVTYPAVITFDVPQGSRHVPPEDFAARVAESLSLDLRGRPLV
327 | EMGRVVSVRLDGMRFRPYVLTDLLVSDPDASHVMQTDELNRAHKIKGTVYAQVCGTGQTV
328 | SFQEKTDEDSGEAYISLRVRARDRKGVEELMEAAGRVMAIYSRRESEIVSFYALYDKTVA
329 | KEAAPPRPPRKSKAPEPTGDKADRKLLRTLAPDIFLPTYSRKCLHMPVILRGAELEDARK
330 | KGLNLMDFPLFGESERLTYACKHPQHPYPGLRANLLPNKAKYPFVPCCYSKDQAVRPNSK
331 | WTAYTTGNAEARRQGRIREGVMQAEPLPEGALIFLRRVLGQETGSKFFALRTTGVPETPV
332 | NAVHVAVFQRSLTAEEQAEERAAMALDPSAMGACAQELYVEPDVDWDRWRREMGDPNVPF
333 | NLLKYFRALETRYDCDIYIMDNKGIIHTKAVRGRLRYRSRRPTVILHLREESCVPVMTPP
334 | SDWTRGPVRNGILTFSPIDPITVKLHDLYQDSRPVYVDGVRVPPLRSDWLPCSGQVVDRA
335 | GKARVFVVTPTGKMSRGSFTLVTWPMPPLAAPILRTDTGFPRGRSDSPLSFLGSRFVPSG
336 | YRRSVETGAIREITGILDGACEACLLTHDPVLVPDPSWSDGGPPVYEDPVPSRALEGFTG
337 | AEKKARMLVEYAKKAISIREGSCTQESVRSFAANGGFVVSPGALDGMKVFNPRFEAPGPF
338 | AEADWAVKVPDVKTARRLVYALRVASVNGTCPVQEYASASLVPNFYKTSTDFVQSPAYTI
339 | NVWRNDLDQSAVKKTRRAVVDWERGLAVPWPLPETELGFSYSLRFAGISRTFMAMNHPTW
340 | ESAAFAALTWAKSGYCPGVTSNQIPEGEKVPTYACVKGMKPAKVLESGDGTLKLDKSSYG
341 | DVRVSGVMIYRASEGKPMQYVSLLM
342 | >sp|Q6GZT4|042L_FRG3G Uncharacterized protein 042L OS=Frog virus 3 (isolate Goorha) GN=FV3-042L PE=4 SV=1
343 | MFAPPSSLFVPATAPAPSTSGFTIPANLRRDAYVCPFATAEKERKEREQQQPASKGLNHD
344 | LAAQEPLHPSLVSRFPSNYRGSFLR
345 | >sp|Q91G56|042R_IIV6 Uncharacterized protein 042R OS=Invertebrate iridescent virus 6 GN=IIV6-042R PE=4 SV=1
346 | MATLQQAQQQNNQLTQQNNQLTQQNNQLTQRVNELTRFLEDANRKIQIKENVIKSSEAEN
347 | RKNLAEINRLHSENHRLIQQSTRTICQKCSMRSN
348 | >sp|Q91G55|043L_IIV6 Uncharacterized protein 043L OS=Invertebrate iridescent virus 6 GN=IIV6-043L PE=4 SV=1
349 | MDLINNKLNIEIQKFCLDLEKKYNINYNNLIDLWFNKESTERLIKCEVNLENKIKFNQKY
350 | NSDTIKIMNILFLICSDGVFGKIENNDVKPLTDEDEKICVKFGYKIMIGCLNDIPI
351 | >sp|Q6GZT3|043R_FRG3G Uncharacterized protein 043R OS=Frog virus 3 (isolate Goorha) GN=FV3-043R PE=4 SV=1
352 | MEEVDGCAGPNSEAGALTAGALTAGAFAVTAGAGVAGAGVAGVGWCSWCSWCSWCWCSWC
353 | SWCWCSWCWCSWCWCSWCWCSWCWCSWCWCSWCWCSWCLSKGWEDRGGLEGCKSCKGWCL
354 | CSHCWCWCSWCWCSWCSWCLSKGWEDRGGLEGCKSCKGWCLCSHCRCWSIN
355 | >sp|Q197B6|044L_IIV3 Putative serine/threonine-protein kinase 040L OS=Invertebrate iridescent virus 3 GN=IIV3-044L PE=3 SV=1
356 | MPLSVFAEEFAEKSVKRYIGQGLWLPCNLSDYYYYQEFHDEGGYGSIHRVMDKATGNEVI
357 | MKHSYKLDFSPGILPEWWSKFGSLTDDLRERVVSNHQLRVSREAQILVQASTVLPEMKLH
358 | DYFDDGESFILIMDYGGRSLENIASSHKKKITNLVRYRAYKGNWFYKNWLKQVVDYMIKI
359 | YHKIKILYDIGIYHNDLKPENVLVDGDHITIIDFGVADFVPDENERKTWSCYDFRGTIDY
360 | IPPEVGTTGSFDPWHQTVWCFGVMLYFLSFMEYPFHIDNQFLEYALEGEKLDKLPEPFAQ
361 | LIRECLSVDPDKRPLTSLLDRLTELHHHLQTIDVW
362 | >sp|Q6GZN9|044R_FRG3G Uncharacterized protein 044R OS=Frog virus 3 (isolate Goorha) GN=FV3-044R PE=4 SV=1
363 | MVVRLAVRANMPKDSLARDSLPKDSLARDFLSDKTSPTDGTQSSDRYLLKIVTAVDYVHL
364 | T
365 | >sp|Q91G54|044R_IIV6 Uncharacterized protein 044R OS=Invertebrate iridescent virus 6 GN=IIV6-044R PE=4 SV=1
366 | MYLYQKIKNCLLLTMYQKKNKSHMYDILQSYLYYQKPIPKNLYSHPKKNLYLNIHHYKNI
367 | NKDLM
368 | >sp|Q6GZT1|045L_FRG3G Uncharacterized protein 045L OS=Frog virus 3 (isolate Goorha) GN=FV3-045L PE=4 SV=1
369 | MDDVEYRTEFSARERAGGDIEEGLELFGPATFKGMEGDPVQRFYNGIESAGRNLIRDGHI
370 | KLNKQEQTRLLSSVLRITYPNYKNPMGTVLGFYVTDGGRGPIDKGRLSHVQSFMEEVTDM
371 | DLRDLIRYCRLWLALK
372 | >sp|Q197B5|045R_IIV3 Uncharacterized protein 045R OS=Invertebrate iridescent virus 3 GN=IIV3-045R PE=4 SV=1
373 | MYKCSQGAMNTEKVMEKFVIQSRFREMYPDKAKAIAGMTVPARYADSVEDMVAFANEKIR
374 | VQKAKVEAEKNARQAMGAPAKFDKYGKYKY
375 | >sp|Q6GZT0|046L_FRG3G Uncharacterized protein 046L OS=Frog virus 3 (isolate Goorha) GN=FV3-046L PE=4 SV=1
376 | MYSVRNSGCSVGCSPRQGASPIMFGPSLGAMLSAPVVRASAPVVRASSPVVKRKSLVKRK
377 | SPVKRSPLKKRSQMRTSPCEA
378 | >sp|Q6GZS9|047L_FRG3G Uncharacterized protein 047L OS=Frog virus 3 (isolate Goorha) GN=FV3-047L PE=4 SV=1
379 | MHTISDWLNLNAPVRCFHVRQLSESEWRFTVNDTIRVVASVDGPWTVDAKGVEDLKMHKL
380 | YVPGPAKCWTRARDKAMAAALAEAVSESETCAADIVRPAVAKNTPRRPVVKRRVDAVKPA
381 | APDNLESWTKDDWYELDL
382 | >sp|Q6GZS8|048L_FRG3G Uncharacterized protein 048L OS=Frog virus 3 (isolate Goorha) GN=FV3-048L PE=4 SV=1
383 | MTAKTLDPSDYNVRDDSTTGMFTPVDRFVCDPESDRIIVRKIPPEWTIGNSMRFVHFTKE
384 | FTQTFDPSESPSNIVRHTNGKKK
385 | >sp|Q6GZS7|049L_FRG3G Putative SAP domain-containing protein 049L OS=Frog virus 3 (isolate Goorha) GN=FV3-049L PE=4 SV=1
386 | MAAPKAEGEDKPKRVRKSRAKPKPETKEVKKPKSKEFCTADDSSDDYNEVKPSPAMIALM
387 | AVKEIPESEDVPDKSDSEAEAPVPAIVKKRRTPPKKAESSDDKKLDEATGEQVIDEDALS
388 | KLTIQTLKGMCKTRNLKISGNKAALVQRLIEADGIAHIIPTTATVVQKVKKTKRPAVFSK
389 | VDSELKLIPCPGREHMLMDEATGLVFLDEDPSTAVGFIEHGEVFGLDSEHMTVCKNMGIR
390 | YSWTEDYLC
391 | >sp|Q91G50|049L_IIV6 Transmembrane protein 049L OS=Invertebrate iridescent virus 6 GN=IIV6-049L PE=4 SV=1
392 | MDKIEELKIEELKIEIPQRKTKFFHDSENSDKRDEEETLNPTITSKAKILIKSKNFWIET
393 | LIFVISVFGALCVAFGIMLIGFLLWLVSNTISILYFIKQKQYPLSLQQMVFLITTCIGVY
394 | NNV
395 | >sp|Q197B1|049R_IIV3 Uncharacterized protein 049R OS=Invertebrate iridescent virus 3 GN=IIV3-049R PE=4 SV=1
396 | MLRIENTVCKSACRVDSATAQPVYSSFDGENFKAEIHSKLDSFERKLNASPTYRDEEGGG
397 | NPEHYETLSQEINDLQSQIENLSLEVENLQGSSSSPSNVAAALAELSQSIRTIKEQLEAN
398 | RKERYNLTVTVANLTAAVNAAKKTGSESTTATATTTTNYETQLKAFEAQIKALDNQLQTQ
399 | KNLVQTTSVEAKNDRDSLRKTIEVIRLTVKTLQDQVESQTGPKKRRKSPIENQPTAGSEL
400 | ATLTTNLTFLTQRVEKLSQGVATHTTAMFTLEETMKKVHTTLQEATASNTNNIDAIRTRV
401 | QELADKIALFDQVQYSVGYEMAKKNPDSTKLRTDLDSAISTVNEEKKSLLTVKDSVQSLK
402 | TQLDELKRTLENDGDVSSLRQTVHDMASSIRDETATIYNKINALEEGLKRGGQTTTTPLT
403 | QLQTRVEEIDKTIVKWNNQHGEWTTRLNKLEAGVSNNQTLMNRFIQQVNGDVNPLKELPA
404 | ELETFKMTITNTWAQLNKKFLDFSAKTDTSVDNFTKKFTEIHPQIASLVDKMDQQIRDNP
405 | HTTEKLMDEIRQLKSAMTRLGTQSSGKPIFSINTKSSYNEKSKKTIFGHPGIIFPETVKI
406 | SSIYITLAAKEADGKEDARLFELTATSTHNNITSTIKQFEKKCTEETILEDYNPPLVIDA
407 | QTKLVLSCNQKVFGVAIFTLQYS
408 | >sp|Q6GZS6|050L_FRG3G Uncharacterized protein 050L OS=Frog virus 3 (isolate Goorha) GN=FV3-050L PE=4 SV=1
409 | MQVYSPSKISQQLETFLNSVANGLGHTMSHAMSQTFSETIVASVAKKAPKTSVLAAAQAA
410 | MQAEDKVSKPKKVKKTKSYADAAPKRVKKVKAPKEDTVVSEPEEAVVEQQEKQQPEKAVV
411 | EQQEKQQPEEAVVEQQEKQQPEEAVVEQQEKQQPEEAVVESEQPEQPEQPERQQQAQPER
412 | QQQAQPERQQQAQPEEAEDAEQEPVEQPTAKPKKVRKTQTESEDKPKRG
413 | >sp|Q6GZS5|051R_FRG3G Uncharacterized protein 051R OS=Frog virus 3 (isolate Goorha) GN=FV3-051R PE=4 SV=1
414 | MTVRITTTTGYPHGLLNPTVPLPMSRYTLVQETAQDILYTPMGKELALMGTCTKTECKYV
415 | RMQEDAHLLAEASKKALTMRLEQNPELKDLLASSGSQPIVYGDTRLVAHLTLLRGVSVLS
416 | PEGMVFSEDAMRKLYKGTIDMFVSDPSSLLNVDRATLTLESLRAMVKASGNWPSTSATAA
417 | VAIPEAPVTGVSVSDKVVMEHSASVYATQKMDFERSLLIRHLLAMDPAAEADVSHLVSRM
418 | DARTRAASSRLAAMYHDGLLDSAVTDGLVPPDQRLLEPMSTPSTPEVHAPQDGMSFEVPH
419 | VLTFAGGPVKVDDHVYDTPLHYAYNLAIRRMFADFGEGDLDDVHVSQVSVIYSDMLDKWI
420 | DAMYPQTLWRLMTEKFSGNQSCLAVLLSTDGADVKWTGRTEEESFLISDMMGQIKTGWIR
421 | SGPPSSSPLSSADIAGTDFFYGWLSYMSRTYATALNVISEMTLARLLDLPDIPEEVRQPT
422 | DREQAALGSDYVRSAWRVCYSEFVHKFEGKNLFASVDYCVKTHLKALKVSRDSVTGTAKT
423 | LSAKGYGTLIALPVIRLAMKS
424 | >sp|Q6GZS4|052L_FRG3G Uncharacterized protein 052L OS=Frog virus 3 (isolate Goorha) GN=FV3-052L PE=3 SV=1
425 | MVKYVVTGGCGFLGSHIVKCILKYAPEVTEVVAYDINISHIMTMWSSKLKVVRGDVMDVM
426 | ALAKAVDGADVVIHTAGIVDVWYRHTDDEIYRVNVSGTKNVLMCCINAGVQVLVNTSSME
427 | VVGPNTTSGVFVRGGERTPYNTVHDHVYPLSKDRAEKLVKHYTGVAAAPGMPALKTCSLR
428 | PTGIYGEGCDLLEKFFHDTVNAGNVAYGGSPPDSEHGRVYVGNVAWMHLLAARALLAGGE
429 | SAHKVNGEAFFCYDDSPYMSYDAFNAELFEDRGFGYVYVPYWVMKPMAAYNDLKRKFLGC
430 | FGVKRSPILNSYTLALARTSFTVKTSKARRMFGYMPLYEWSEAKRRTKDWISTLK
431 | >sp|Q197A7|053L_IIV3 Uncharacterized protein 053L OS=Invertebrate iridescent virus 3 GN=IIV3-053L PE=4 SV=1
432 | MEQYLQAFEFVEEMVVLPKYLSWELYHHLAVLLREKYPKTYKNKGYIFNIKVKSILDNRI
433 | TPTGQIVLVVMFQSDLYVPQVGHVFTERIRVNSVDDRYQWITIEPLTVFLRSNIPYKPNT
434 | LVTVQICSIKMDNTLCFGTILD
435 | >sp|Q6GZS3|053R_FRG3G Putative myristoylated protein 053R OS=Frog virus 3 (isolate Goorha) GN=FV3-053R PE=3 SV=1
436 | MGAAESINTVNIVTKAYAKIMTTMVTDQDITADQSQVFSIDHVKGDVVIKGDVFTQMLVI
437 | NLASLMKAIATQSAQDQLIDNIAQQAQAAVSGLNLAQYAYVSNNIDRLITACVQMSTDMR
438 | VSCKSKVTMTQSFSVTDVEGDVRVTGVKFNQFANILSSCAMDASVNNDQARDIVSQIKQR
439 | GDAKASGLDPTTLIVIIVLVMVGAPMGAGFMAGRRAIGPLLASVGLIGGGAVALGYVPRP
440 | VKIEGFSSDPDFTLAQPAATVKGLTFTAAVAKLKSTDGYGALFWKNYDVKGTTAVKLQET
441 | LSYFAPAGYDPASWAGVGDSAPPFRIFPGLYQGKGDPGARPRAAYGYAGPVAGPKKGDAY
442 | LDGDTGSYYVLGDSWKMRGTISGHQNGRTDYWGTVDPTTTAALTGSERYIWVDPFTLVKS
443 | TVWLFTGSPKKWTQQQTAPLDIPLTNTPSDFNVWVYKDDTAVQAVKWSSVGAGVAGAALT
444 | ASALLMPDSVASSEMSPAVGTGTPAIGTGSPAVGTGFPAHRG
445 | >sp|Q6GZS2|054L_FRG3G Uncharacterized protein 054L OS=Frog virus 3 (isolate Goorha) GN=FV3-054L PE=4 SV=1
446 | MPLRLCQGRKDRASDPVRDDGSPPRLFVSQVCRRAPKDPQGFQGHRGGQNVGDCSPIFHQ
447 | EKKQVMRRFYSLCEWK
448 | >sp|Q197A6|054L_IIV3 Uncharacterized protein 054L OS=Invertebrate iridescent virus 3 GN=IIV3-054L PE=4 SV=1
449 | MASEATVESVETKVESPIVESPVDQGLLESIKNFMDDLAVVTENENFQDYHTIVRRIDET
450 | KVKSYNKLVGGFREFFSLNKTALMEGNFEGLIEPHISYKTESGSFFFNFQTTYLETDEAN
451 | QEIIKEHLNHIWAQIRSENKCPEQLYIDEIFQKLKNKDQLTMDDQLIRDLFTKFQTANFN
452 | VTALIRAGCSKAREFLTNNGSQKSSSTFRLIETIENVNVDNFTQMDFMALISKISAIFSE
453 | SGESNPLNLCLSSLFGGGNTNQPSLTSMFPFPTPPLPDNVLLDNLDQLTLEQQSETTGDD
454 | DHHSFEPEK
455 | >sp|Q6GZS1|055L_FRG3G Putative helicase 055L OS=Frog virus 3 (isolate Goorha) GN=FV3-055L PE=4 SV=1
456 | MAKLLRLNAIDGDMPGAGEADLFTLAPGGKAYVPFAWGSRVLGCKPPPAHGAARERGSVS
457 | LRPHQKGVLKEAWGHVTSKGYCMLKCPPGFGKTFMALELWRRLGLPALVLTNRRVLATQW
458 | RDSATRFLPDSRVFTSGTPPPDALPRDLYVTGPASLRNRRIKAKDSPAKFLLIVDEAHQL
459 | TSPVSCRVLLSVRPSHLLGLSATPMRYDDYHAALGAFFGREDSTVDRVDPRPHEVEILST
460 | GVHIEPEFSKITGKMDWNSVIKAQSDNPERDAALADRMLLRPDVKWLVLCKRVDHVKRMA
461 | ETLSSRSGKKVDVLHGSKDEWDRDAWCVVGTYSKAGTGFDACERTGLCLAADVDRYFEQC
462 | LGRLRANGGTVLDPVDDLGVLRKHSKNREAVYIAAGCTIKKTKCDASRPSQSTPTPTGSS
463 | QPAPRTRRPQR
464 | >sp|Q67475|055R_FRG3G Uncharacterized protein 055R OS=Frog virus 3 (isolate Goorha) GN=FV3-055R PE=4 SV=1
465 | MLPQNSQVVHGVQDGPPVGPQPAQALLKVPVDVRRQAQAGPLAGVEPRPRLGVGAHHTPG
466 | VPVPLILGAVQHVHLLPGPRGQCLGHPLDVVHPLAQHQPLYVGPEEHPVGQGGVPLGVIG
467 | LGLDHRVPVHLARDLAKLGLYVHARAEYLHLVGPGVDPVHRAVLPAEKGPQCSVVVVVPH
468 | GCSAQTQQVRGPHRQEDPTRHGGRQLVGLIHNQEKFCGRVLGLDPPVSQRSRTRHIQVPG
469 | QGVGRRGAGCKDPRVRKEPGRRVPPLSRQHPPVCQDEGGQPQPPPQLQGHEGLAEAGRAL
470 | EHAVPLGGDVAPGLLQDPFLVRSERDGAPLPGCAVSGRRFASQDPGTPGEGDVGLSPGRE
471 | GKQVRFPRAGHVSIYRVEP
472 | >sp|Q6GZR9|056R_FRG3G Uncharacterized protein 056R OS=Frog virus 3 (isolate Goorha) GN=FV3-056R PE=4 SV=1
473 | MGVYSPAPRTPRGPWNIRIRFLSWSNSFLLEVKKNYGDVYLCDVCPVRPPGLQAPREQPV
474 | LHDRKVLHLYGQDSGVRDVQEVLWNPVSHQEVRRDNHGVLHGRRRARVRQAEEGRRRRQE
475 | GHRFRDWERLHQRVEGCPGLQGHGF
476 | >sp|O55703|056R_IIV6 Uncharacterized protein 056R OS=Invertebrate iridescent virus 6 GN=IIV6-056R PE=4 SV=1
477 | MEQKIDKKNSYSFGITSSTTVHVLGEVVAIGGILYYTHSQVNQLNTKIASLEKQILDLTN
478 | ILKHLSPHSFQQLQSSPTTQSTPPLPQSTPQSQQSQQSAVLPQRPSFLGGSTPKESQSFP
479 | GVETRSLGEKTTRGKLKSPHPSQIPVTQENFHYPYQTMNKTMRWEFLKPVESDESEDETN
480 | CQNGVCTLQKQEKNVTFNGSVEQLKYGNFSPQRSTKTMIGSPSIRPLIPHESIESVSESI
481 | ESSQDQSFSSRETISGNFKSKDDHQLSESEINQLVSKAIRTKK
482 | >sp|Q197A3|057L_IIV3 Uncharacterized protein 057L OS=Invertebrate iridescent virus 3 GN=IIV3-057L PE=4 SV=1
483 | MFKIYRTSCMGQHQSQFLHSGTVVQTVDGVTTTSFFQPCLVFPFSIEIISISLVSLNTTN
484 | ETKLIKMSIMENSELVDYNESAYTLAHLPGKQMTYLKYPAPFTIRQHQPFFFVHHGDLGD
485 | ASLTLEYRIK
486 | >sp|Q6GZR8|057R_FRG3G Putative phosphotransferase 057R OS=Frog virus 3 (isolate Goorha) GN=FV3-057R PE=4 SV=1
487 | MAMVSNVKYFADALQGTQGKVGTFTVLGENVFFKRGDGTDTVCGLEMVAGRILRARSDVH
488 | FCEPKYFVEMDDGEKVCSFELLDCKPLGSMAPGRKGKKSVGSVTQYLSGLYQTFAAAAAA
489 | HSVGVVHSDLHTGNVMLCPEPVSHYVYNLGGGEMLSLETNGVRAVVVDLGMARIPGKNTV
490 | ACDIFVHVGHVVNGRPDYAADVRTLTLGSCYDMVMMCASGKPSLEERMLCYEVMAAYNNL
491 | FAGVCAPSKGGWFVDHYPSMCAVMEATIPDSVASRGGGSWLLAVANMCKLLVPRPYVKRA
492 | CGKEKAHAMWMTLFTELGLTAKKSISKVDMVDAVQRLRAIADGSEIPPASLMKAACAVGL
493 | LTASVAEACYEKVEEIKASHVGMLRWKDALDAWVRLPVRCSGSVPKLGSTVILHTESGTE
494 | ETVVTQSMLRQIVKTREALDMAQAASDAVWTDTAYYEADDELMKGAHEESAEDFATSFLK
495 | GGTTGPIAKRCRLILKSL
496 | >sp|Q6GZR7|058R_FRG3G Uncharacterized protein 058R OS=Frog virus 3 (isolate Goorha) GN=FV3-058R PE=4 SV=1
497 | MEIRDTTVGLDRPVQSGAWDPGATREQLALAGISGRCDLGGRDEDLWSRKSQKDETFKDC
498 | ERRRGGEAPRLLCDKWRRDREAEAVRRRVQSQRRQGGREDPDGPARVRGRRRRVAVCGHS
499 | PDRGPAREEHKGPAGGSDHKDLGHHKGPEVGSGLRGPQARQVCGRSRGHEVQRVQKGLRQ
500 | GVQGHGCREVALDARLCLVRVLGRSGQKGRHGRLSVASRRLDGQEKVEKRGLFSLGA
501 | 


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/Presentations and Tutorials/Protvec demo 2017/helpers.py:
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 1 | import matplotlib.pyplot as plt
 2 | import numpy as np
 3 | 
 4 | """
 5 | Copyright (C) 2017 by Samo Turk and Sabrina Jaeger, BioMed X GmbH
 6 | This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 License. 
 7 | To view a copy of this license, visit https://creativecommons.org/licenses/by-sa/4.0/ or send a letter 
 8 | to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.
 9 | """
10 | 
11 | class nGram:
12 |     """Class for storing n-grams with useful default depiction in jupyter.
13 |     >>>nGram(split_ngrams('ABCDEFGHIJKLMNOPQRSTUVWXYZABCDEFGHIJKLMNOPQRSTUVWXYZ',3))"""
14 |     
15 |     def __init__(self, n_gram):
16 |         self.n_gram = n_gram
17 |     def __len___(self):
18 |         return len(self.n_gram)
19 |     def __str__(self): # Stringe representation
20 |         return 'n-gram with %i sentences' %len(self.n_gram)
21 |     __repr__ = __str__ # Default representation
22 |     def __contains__(self, word): # Contains method enable usage of "'Word' in nGram"
23 |         if word in [item for sublist in self.n_gram for item in sublist]:
24 |             return True
25 |         else:
26 |             return False
27 |     contains = __contains__ # nGram.contains('word')
28 |     def __iter__(self): # Iterate over sentences (for sentence in nGram:...)
29 |         for x in self.n_gram:
30 |             yield x
31 |     def _repr_html_(self): # default jupyter representation
32 |         colors = ['Red','Maroon','Yellow','Olive','Lime','Green','Aqua','Teal','Blue','Navy','Fuchsia','Purple']
33 |         html = "<samp><b>"
34 |         for i,ng in enumerate(self.n_gram):
35 |             ng_2 = ''
36 |             for n,c in zip(ng, colors[:len(ng)]): # depicts only as many as we have colors
37 |                 ng_2 += '<span style="color: %s">' %c
38 |                 ng_2 += n
39 |                 ng_2 += '</span>'
40 |             html += " "*i + ng_2
41 |             if len(ng) > len(colors): # append ... if we run out of colors
42 |                 html += "..."
43 |             html += "\n"
44 |         html += "</b></samp>"
45 |         return html
46 | 
47 | class DfVec:
48 |     """
49 |     Helper class to store vectors in a pandas DataFrame
50 |     
51 |     Parameters  
52 |     ---------- 
53 |     vec: np.array
54 |     """
55 |     def __init__(self, vec):
56 |         self.vec = vec
57 |     def __str__(self):
58 |         return "%d dimensional vector" % len(self.vec)
59 |     def __repr__(self):
60 |         return "%d dimensional vector" % len(self.vec)
61 |     def __len__(self):
62 |         return len(self.vec)
63 | 
64 | def confusion_matrix_plot(cm, names, title='Confusion matrix', cmap=plt.cm.Blues):
65 |     """Creates confusion matrix plot from confusion_matrix(observations, predictions).
66 |     You can calculate confusion matrix with help of ``sklearn.metrics.confusion_matrix``
67 |     
68 |     Parameters
69 |     ----------
70 |     cm : np.array
71 |         Confusion matrix
72 |     names : list
73 |         Names of classes
74 |     title : str
75 |         Title of the plot
76 |     cmap : plt.cm
77 |         Matplotlib colormap
78 | 
79 |     Returns
80 |     -------    
81 |     plt.figure
82 |         matplotlib figure
83 |     """
84 |     fig = plt.figure()
85 |     axes = fig.add_axes([0, 0, 1, 1])
86 |     im = axes.imshow(cm, interpolation='nearest', cmap=cmap)
87 |     fig.colorbar(im)
88 |     tick_marks = np.arange(len(names))
89 |     plt.xticks(tick_marks, names, rotation=45)
90 |     plt.yticks(tick_marks, names,)
91 |     axes.set_ylabel('True value')
92 |     axes.set_xlabel('Predicted value')
93 |     axes.set_title(title)
94 |     return fig
95 | 


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/Presentations and Tutorials/Protvec demo 2017/trained_models/model_SwissProt_small:
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/Presentations and Tutorials/Protvec demo 2017/trained_models/swissprot_reviewed_protvec:
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/Presentations and Tutorials/RDKit UGM 2014/biomedx.png:
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/Presentations and Tutorials/RDKit UGM 2014/hackaton/XLSX export.ipynb:
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  1 | {
  2 |  "metadata": {
  3 |   "name": "",
  4 |   "signature": "sha256:d1c239959bbfc2922992b270c32e0a3f52ded415ef8c116012f7cc9a9a74d1dd"
  5 |  },
  6 |  "nbformat": 3,
  7 |  "nbformat_minor": 0,
  8 |  "worksheets": [
  9 |   {
 10 |    "cells": [
 11 |     {
 12 |      "cell_type": "markdown",
 13 |      "metadata": {},
 14 |      "source": [
 15 |       "# Demo of SaveXlsxFromFrame function"
 16 |      ]
 17 |     },
 18 |     {
 19 |      "cell_type": "code",
 20 |      "collapsed": false,
 21 |      "input": [
 22 |       "import rdkit.Chem as Chem\n",
 23 |       "from rdkit.Chem import Draw\n",
 24 |       "from rdkit.Chem import PandasTools\n",
 25 |       "from rdkit.Chem.Draw import IPythonConsole # Enables RDKit IPython integration\n",
 26 |       "import pandas as pd"
 27 |      ],
 28 |      "language": "python",
 29 |      "metadata": {},
 30 |      "outputs": [],
 31 |      "prompt_number": 1
 32 |     },
 33 |     {
 34 |      "cell_type": "markdown",
 35 |      "metadata": {},
 36 |      "source": [
 37 |       "Load data"
 38 |      ]
 39 |     },
 40 |     {
 41 |      "cell_type": "code",
 42 |      "collapsed": false,
 43 |      "input": [
 44 |       "df = pd.read_csv('drugs.smi', delimiter=\"\\s\")"
 45 |      ],
 46 |      "language": "python",
 47 |      "metadata": {},
 48 |      "outputs": [
 49 |       {
 50 |        "output_type": "stream",
 51 |        "stream": "stderr",
 52 |        "text": [
 53 |         "/usr/lib/python2.7/site-packages/pandas/io/parsers.py:635: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support regex separators; you can avoid this warning by specifying engine='python'.\n",
 54 |         "  ParserWarning)\n"
 55 |        ]
 56 |       }
 57 |      ],
 58 |      "prompt_number": 2
 59 |     },
 60 |     {
 61 |      "cell_type": "code",
 62 |      "collapsed": false,
 63 |      "input": [
 64 |       "df.columns"
 65 |      ],
 66 |      "language": "python",
 67 |      "metadata": {},
 68 |      "outputs": [
 69 |       {
 70 |        "metadata": {},
 71 |        "output_type": "pyout",
 72 |        "prompt_number": 3,
 73 |        "text": [
 74 |         "Index([u'SMILES', u'Name'], dtype='object')"
 75 |        ]
 76 |       }
 77 |      ],
 78 |      "prompt_number": 3
 79 |     },
 80 |     {
 81 |      "cell_type": "code",
 82 |      "collapsed": false,
 83 |      "input": [
 84 |       "smiles = 'SMILES'\n",
 85 |       "names = 'Name'"
 86 |      ],
 87 |      "language": "python",
 88 |      "metadata": {},
 89 |      "outputs": [],
 90 |      "prompt_number": 4
 91 |     },
 92 |     {
 93 |      "cell_type": "code",
 94 |      "collapsed": false,
 95 |      "input": [
 96 |       "df = df[df[smiles].notnull()]"
 97 |      ],
 98 |      "language": "python",
 99 |      "metadata": {},
100 |      "outputs": [],
101 |      "prompt_number": 5
102 |     },
103 |     {
104 |      "cell_type": "markdown",
105 |      "metadata": {},
106 |      "source": [
107 |       "Add mol objects"
108 |      ]
109 |     },
110 |     {
111 |      "cell_type": "code",
112 |      "collapsed": false,
113 |      "input": [
114 |       "PandasTools.AddMoleculeColumnToFrame(df, smilesCol=smiles)"
115 |      ],
116 |      "language": "python",
117 |      "metadata": {},
118 |      "outputs": [],
119 |      "prompt_number": 6
120 |     },
121 |     {
122 |      "cell_type": "markdown",
123 |      "metadata": {},
124 |      "source": [
125 |       "Add some columns with number"
126 |      ]
127 |     },
128 |     {
129 |      "cell_type": "code",
130 |      "collapsed": false,
131 |      "input": [
132 |       "from rdkit.Chem import Descriptors\n",
133 |       "df['logp'] = df['ROMol'].map(Descriptors.MolLogP)\n",
134 |       "df['mw'] = df['ROMol'].map(Descriptors.MolWt)\n",
135 |       "df['hac'] = df['ROMol'].map(Descriptors.HeavyAtomCount)"
136 |      ],
137 |      "language": "python",
138 |      "metadata": {},
139 |      "outputs": [],
140 |      "prompt_number": 7
141 |     },
142 |     {
143 |      "cell_type": "code",
144 |      "collapsed": false,
145 |      "input": [
146 |       "len(df)"
147 |      ],
148 |      "language": "python",
149 |      "metadata": {},
150 |      "outputs": [
151 |       {
152 |        "metadata": {},
153 |        "output_type": "pyout",
154 |        "prompt_number": 8,
155 |        "text": [
156 |         "1000"
157 |        ]
158 |       }
159 |      ],
160 |      "prompt_number": 8
161 |     },
162 |     {
163 |      "cell_type": "markdown",
164 |      "metadata": {},
165 |      "source": [
166 |       "Check dtypes of columns"
167 |      ]
168 |     },
169 |     {
170 |      "cell_type": "code",
171 |      "collapsed": false,
172 |      "input": [
173 |       "df.dtypes"
174 |      ],
175 |      "language": "python",
176 |      "metadata": {},
177 |      "outputs": [
178 |       {
179 |        "metadata": {},
180 |        "output_type": "pyout",
181 |        "prompt_number": 9,
182 |        "text": [
183 |         "SMILES     object\n",
184 |         "Name       object\n",
185 |         "ROMol      object\n",
186 |         "logp      float64\n",
187 |         "mw        float64\n",
188 |         "hac         int64\n",
189 |         "dtype: object"
190 |        ]
191 |       }
192 |      ],
193 |      "prompt_number": 9
194 |     },
195 |     {
196 |      "cell_type": "code",
197 |      "collapsed": false,
198 |      "input": [
199 |       "df.head(1)"
200 |      ],
201 |      "language": "python",
202 |      "metadata": {},
203 |      "outputs": [
204 |       {
205 |        "html": [
206 |         "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
207 |         "<table border=\"1\" class=\"dataframe\">\n",
208 |         "  <thead>\n",
209 |         "    <tr style=\"text-align: right;\">\n",
210 |         "      <th></th>\n",
211 |         "      <th>SMILES</th>\n",
212 |         "      <th>Name</th>\n",
213 |         "      <th>ROMol</th>\n",
214 |         "      <th>logp</th>\n",
215 |         "      <th>mw</th>\n",
216 |         "      <th>hac</th>\n",
217 |         "    </tr>\n",
218 |         "  </thead>\n",
219 |         "  <tbody>\n",
220 |         "    <tr>\n",
221 |         "      <th>0</th>\n",
222 |         "      <td> NC1=NCC(c2ccccc2)O1</td>\n",
223 |         "      <td> CHEMBL106258</td>\n",
224 |         "      <td> <img src=\"data:image/png;base64,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\" alt=\"Mol\"/></td>\n",
225 |         "      <td> 1.0726</td>\n",
226 |         "      <td> 162.192</td>\n",
227 |         "      <td> 12</td>\n",
228 |         "    </tr>\n",
229 |         "  </tbody>\n",
230 |         "</table>\n",
231 |         "</div>"
232 |        ],
233 |        "metadata": {},
234 |        "output_type": "pyout",
235 |        "prompt_number": 10,
236 |        "text": [
237 |         "                SMILES          Name                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  ROMol    logp       mw  hac\n",
238 |         "0  NC1=NCC(c2ccccc2)O1  CHEMBL106258  <img 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\" alt=\"Mol\"/>  1.0726  162.192   12"
239 |        ]
240 |       }
241 |      ],
242 |      "prompt_number": 10
243 |     },
244 |     {
245 |      "cell_type": "code",
246 |      "collapsed": false,
247 |      "input": [
248 |       "len(df)"
249 |      ],
250 |      "language": "python",
251 |      "metadata": {},
252 |      "outputs": [
253 |       {
254 |        "metadata": {},
255 |        "output_type": "pyout",
256 |        "prompt_number": 11,
257 |        "text": [
258 |         "1000"
259 |        ]
260 |       }
261 |      ],
262 |      "prompt_number": 11
263 |     },
264 |     {
265 |      "cell_type": "code",
266 |      "collapsed": false,
267 |      "input": [
268 |       "import numpy as np\n",
269 |       "import os\n",
270 |       "from cStringIO import StringIO\n",
271 |       "\n",
272 |       "def SaveXlsxFromFrame(frame, outFile, molCol='ROMol', size=(300,300)):\n",
273 |       "    \"\"\"\n",
274 |       "    Saves pandas DataFrame as a xlsx file with embedded images.\n",
275 |       "    It maps numpy data types to excel cell types:\n",
276 |       "    int, float -> number\n",
277 |       "    datetime -> datetime\n",
278 |       "    object -> string (limited to 32k character - xlsx limitations)\n",
279 |       " \n",
280 |       "    Cells with compound images are a bit larger than images due to excel.\n",
281 |       "    Column width weirdness explained (from xlsxwriter docs):\n",
282 |       "    The width corresponds to the column width value that is specified in Excel. \n",
283 |       "    It is approximately equal to the length of a string in the default font of Calibri 11. \n",
284 |       "    Unfortunately, there is no way to specify \u201cAutoFit\u201d for a column in the Excel file format.\n",
285 |       "    This feature is only available at runtime from within Excel.\n",
286 |       "    \"\"\"\n",
287 |       "    \n",
288 |       "    import xlsxwriter # don't want to make this a RDKit dependency\n",
289 |       "       \n",
290 |       "    cols = list(frame.columns)\n",
291 |       "    print cols\n",
292 |       "    cols.remove(molCol)\n",
293 |       "    dataTypes = dict(frame.dtypes)\n",
294 |       "\n",
295 |       "    workbook = xlsxwriter.Workbook(outFile) # New workbook\n",
296 |       "    worksheet = workbook.add_worksheet() # New work sheet\n",
297 |       "    worksheet.set_column('A:A', size[0]/6.) # column width\n",
298 |       "    \n",
299 |       "    # Write first row with column names\n",
300 |       "    c2 = 1\n",
301 |       "    for x in cols:\n",
302 |       "        worksheet.write_string(0, c2, x)\n",
303 |       "        c2 += 1\n",
304 |       "    \n",
305 |       "    c = 1\n",
306 |       "    for index, row in frame.iterrows():\n",
307 |       "        image_data = StringIO()\n",
308 |       "        img = Draw.MolToImage(row[molCol], size=size)\n",
309 |       "        img.save(image_data, format='PNG')\n",
310 |       "        \n",
311 |       "        worksheet.set_row(c, height=size[1]) # looks like height is not in px?\n",
312 |       "        worksheet.insert_image(c, 0, \"f\", {'image_data': image_data})\n",
313 |       "\n",
314 |       "        \n",
315 |       "        for c2, x in enumerate(cols, start=1):\n",
316 |       "            if str(dataTypes[x]) == \"object\":\n",
317 |       "                worksheet.write_string(c, c2, str(row[x])[:32000]) # string length is limited in xlsx\n",
318 |       "            elif ('float' in str(dataTypes[x])) or ('int' in str(dataTypes[x])):\n",
319 |       "                if (row[x] != np.nan) or (row[x] != np.inf):\n",
320 |       "                    worksheet.write_number(c, c2, row[x])\n",
321 |       "            elif 'datetime' in str(dataTypes[x]):\n",
322 |       "                worksheet.write_datetime(c, c2, row[x])\n",
323 |       "        c += 1\n",
324 |       "\n",
325 |       "    workbook.close()\n",
326 |       "    image_data.close()"
327 |      ],
328 |      "language": "python",
329 |      "metadata": {},
330 |      "outputs": [],
331 |      "prompt_number": 12
332 |     },
333 |     {
334 |      "cell_type": "markdown",
335 |      "metadata": {},
336 |      "source": [
337 |       "#### Lets write selected columns and first 500 compounds"
338 |      ]
339 |     },
340 |     {
341 |      "cell_type": "code",
342 |      "collapsed": false,
343 |      "input": [
344 |       "% time SaveXlsxFromFrame(df[['ROMol', smiles, names, 'logp', 'hac']][:500], 'demo.xlsx', size=(200,200))"
345 |      ],
346 |      "language": "python",
347 |      "metadata": {},
348 |      "outputs": [
349 |       {
350 |        "output_type": "stream",
351 |        "stream": "stdout",
352 |        "text": [
353 |         "['ROMol', 'SMILES', 'Name', 'logp', 'hac']\n",
354 |         "CPU times: user 4.52 s, sys: 46.7 ms, total: 4.57 s"
355 |        ]
356 |       },
357 |       {
358 |        "output_type": "stream",
359 |        "stream": "stdout",
360 |        "text": [
361 |         "\n",
362 |         "Wall time: 4.58 s\n"
363 |        ]
364 |       }
365 |      ],
366 |      "prompt_number": 13
367 |     },
368 |     {
369 |      "cell_type": "markdown",
370 |      "metadata": {},
371 |      "source": [
372 |       "\n",
373 |       "\n",
374 |       "Copyright (C) 2014 by Samo Turk, [BioMed X GmbH](http://bio.mx)\n",
375 |       "\n",
376 |       "This work is licensed under the Creative Commons Attribution-ShareAlike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.\n"
377 |      ]
378 |     }
379 |    ],
380 |    "metadata": {}
381 |   }
382 |  ]
383 | }


--------------------------------------------------------------------------------
/Presentations and Tutorials/RDKit UGM 2014/hackaton/drugs.smi:
--------------------------------------------------------------------------------
   1 | SMILES Name 
   2 | NC1=NCC(c2ccccc2)O1 CHEMBL106258
   3 | C=CC1(C)CC(OC(=O)CSCCN(CC)CC)C2(C)C3C(=O)CCC3(CCC2C)C(C)C1O CHEMBL498466
   4 | CCCCn1c2ncn(CC(C)=O)c2c(=O)n(CCCC)c1=O CHEMBL277465
   5 | CCC(C(N)=O)N1CCCC1=O CHEMBL1286
   6 | C(C1CO1)N1CCC(C2CCN(CC3CO3)CC2)CC1 CHEMBL462393
   7 | CN1CCN(c2c(F)cc3c(=O)c(C(=O)O)cn4c3c2SCC4)CC1 CHEMBL295619
   8 | ClC(Cl)Cl CHEMBL44618
   9 | CNCCCCOc1ccccc1Cc1ccccc1 CHEMBL1192517
  10 | CCCCCN(CCCOC)C(=O)C(CCC(=O)O)NC(=O)c1ccc(Cl)c(Cl)c1 CHEMBL550781
  11 | CCN(CC)CCNC(C(=O)OCCC(C)C)c1ccccc1 CHEMBL253592
  12 | CCCC(CCC)C(=O)NCC(N)=O CHEMBL471638
  13 | O=c1[nH]c2cc(C(F)(F)F)c(N3CCOCC3)cc2n(CP(=O)(O)O)c1=O CHEMBL19892
  14 | CCN(c1nncs1)P(=O)(N1CC1)N1CC1 CHEMBL474928
  15 | Nc1ccncc1N CHEMBL354077
  16 | CN(C)S(=O)(=O)NC1CC2c3cccc4c3c(cn4C)CC2N(C)C1 CHEMBL12314
  17 | O=P(O)(O)C(Cl)(Cl)P(=O)(O)O CHEMBL12318
  18 | O=C(C=CC=Cc1ccc2c(c1)OCO2)N1CCCCC1 CHEMBL43185
  19 | [Na+].O=S(=O)([O-])NC1CCCCC1 CHEMBL273977
  20 | CC(C)NCC(O)COc1cccc2ccccc21 CHEMBL275742
  21 | CC(C)NCC(O)COc1ccc(COCCOC(C)C)cc1 CHEMBL645
  22 | NCCCS(=O)(=O)O CHEMBL149082
  23 | CC(C)(CC1Cc2ccccc2C1)NCC(O)COc1cc(CCC(=O)O)cc(F)c1F CHEMBL1198855
  24 | CC(C)Nc1cccnc1N1CCN(C(=O)c2cc3cc(NS(C)(=O)=O)ccc3[nH]2)CC1 CHEMBL593
  25 | CC(=O)C(=Cc1cc(O)c(O)c([N+](=O)[O-])c1)C(C)=O CHEMBL167055
  26 | NCCCNc1ccc2c3c(nn2CCNCCO)-c2c(O)ccc(O)c2C(=O)c31 CHEMBL203666
  27 | COC(=O)C1C(O)CCC2CN3CCc4c5ccccc5[nH]c4C3CC21 CHEMBL15245
  28 | CN1CCc2cccc3c2C1Cc1ccc(O)c(O)c1-3 CHEMBL53
  29 | CC(C(O)c1ccc(O)cc1)N1CCC(Cc2ccccc2)CC1 CHEMBL305187
  30 | CC(C)NCC(O)COc1ccc(CC(N)=O)cc1 CHEMBL24
  31 | CC12CCC(=O)C=C1CCC1C3CCC(C(=O)CO)C3(C=O)CC(O)C12 CHEMBL273453
  32 | OCC1OC(O)(CO)C(O)C1O CHEMBL604608
  33 | CCN(CC)CCc1nc(-c2ccccc2)no1 CHEMBL1620875
  34 | Cc1ccc(OCC(O)CNC(C)(C)C)c2oc(=O)ccc12 CHEMBL349807
  35 | Cc1c(C)c(=O)oc2cc(OCc3nnc(C(C)C)s3)ccc12 CHEMBL19004
  36 | C=CCN(C1=NCCN1)c1c(Cl)cccc1Cl CHEMBL278581
  37 | CN1c2ccc(Cl)cc2C2c3ccccc3CCN2CC1=O CHEMBL1723823
  38 | CCCCCCCC(=O)O CHEMBL324846
  39 | CCOC1OC2OC3(C)CCC4C(C)CCC(C1C)C42OO3 CHEMBL301267
  40 | CNCC(O)c1ccc(O)c(O)c1 CHEMBL1740
  41 | C=C1CC(N)C(C(=O)O)C1 CHEMBL343803
  42 | CC(=O)Nc1ccc(C(=O)O)cc1 CHEMBL112687
  43 | CCc1c(C)n2cc(C(=O)c3ccccc3)nc2nc1OC CHEMBL281164
  44 | Cc1cccc(OCC(O)CNC(C)(C)C)c1C CHEMBL347795
  45 | CC(=O)Nc1cccc(N2CCN(CCCCNS(=O)(=O)CC3CCCCC3)CC2)c1 CHEMBL209821
  46 | CCn1c2ccc(OC(C)=O)cc2c(C)c1-c1ccc(OC(C)=O)cc1 CHEMBL32227
  47 | O=C(NP(=O)(N1CC1)N1CC1)OCc1ccccc1 CHEMBL504088
  48 | CC(C)(C)C(=O)C(Oc1ccc(Cl)cc1)n1ccnc1 CHEMBL1437764
  49 | CCOC(=S)SSC(=S)OCC CHEMBL331743
  50 | O=C1c2ccccc2OC=C(Cl)N1CCCCN1CC=C(c2ccccn2)CC1 CHEMBL345237
  51 | NCC(CC(=O)O)c1ccc(Cl)cc1 CHEMBL301742
  52 | CC(=O)c1ccc2c(c1)C(=O)C1(CC1)O2 CHEMBL18098
  53 | CCCCCCCC(=O)OC(O)C(O)CO CHEMBL1200882
  54 | COc1ccc(CCNCC(O)c2ccc(O)cc2)cc1OC CHEMBL493682
  55 | Cc1cc(-c2ccc(O)cc2)nnc1NCCN1CCOCC1 CHEMBL150980
  56 | CCCCCCCCCCCCCC(=O)O CHEMBL111077
  57 | CC(C)n1cc2c3c1cccc3C1CC(C(=O)NC3CCCCC3)CN(C)C1C2 CHEMBL160293
  58 | NC(=O)Cc1cccc(C(=O)c2ccccc2)c1N CHEMBL1021
  59 | CCCC(NC(C)C(=O)N1C(C(=O)O)CC2CCCCC21)C(=O)O CHEMBL1201368
  60 | Cc1c(F)cc2c(=O)c(C(=O)O)cn3c2c1CCC3C CHEMBL170052
  61 | CN(C)CCN1C(=O)c2cccc3cc([N+](=O)[O-])cc(c32)C1=O CHEMBL43482
  62 | [Cl-].[Cl-].[Sr+2] CHEMBL2219640
  63 | CN(C)CCOC(C)(c1ccccc1)c1ccccc1 CHEMBL1742465
  64 | CN(C)S(=O)(=O)c1ccc2c(c1)N(CCCN1CCN(C)CC1)c1ccccc1S2 CHEMBL609109
  65 | CCN(CC)C(=O)N1CCN(C)CC1 CHEMBL684
  66 | COc1cc2c(cc1OCCCF)CCN1CC(CC(C)C)C(O)CC21 CHEMBL579217
  67 | O=C(Nc1cccc(C2=NCCN2)c1)Nc1cccc(C2=NCCN2)c1 CHEMBL427342
  68 | CC1COC2(c3ccccc3Cl)c3cc(Cl)ccc3NC(=O)CN12 CHEMBL1743261
  69 | CCCCCCCCCCCCOCCCN CHEMBL1887483
  70 | CCOC(=O)C(C#N)=C(c1ccccc1)c1ccccc1 CHEMBL1889451
  71 | O=C(NCC1CCCCN1)c1cc(OCC(F)(F)F)ccc1OCC(F)(F)F CHEMBL652
  72 | Cc1cnc(NCCCN(C)C)c2c1[nH]c1ccc3cc(O)ccc3c12 CHEMBL1908351
  73 | O=C1NC(=O)C2C1C1C2C2C=CC1C1C(=O)NC(=O)C12 CHEMBL1908340
  74 | CC(O)C(=O)OP(=O)(O)O CHEMBL2111170
  75 | CCOC(=O)C1(c2ccccc2)CCN(CCCNc2ccccc2)CC1 CHEMBL2110995
  76 | COc1ccc(Cl)c2c1CCCC2N(C)C CHEMBL2111119
  77 | C#CCOC1CN2CCC1CC2 CHEMBL2111051
  78 | CCC(=O)OC(CC(=O)O)C[N+](C)(C)C CHEMBL1516469
  79 | C=CCC1(CC(C)C)C(=O)NC(=S)NC1=O CHEMBL2110937
  80 | CCNC(C)C(O)c1ccc(O)c(O)c1 CHEMBL2110629
  81 | [Cl-].[Cl-].[Ra+2] CHEMBL2111187
  82 | OC1CN2CCCC(O)C2C1O CHEMBL371197
  83 | CC12CCC3C(CCC4CC(=O)CCC43C)C1CCC2C(=O)COC(=O)CCC(=O)O CHEMBL2110850
  84 | Cc1cc(OCCN(C)C)c(C(C)C)cc1OC(=O)OC(C)C CHEMBL2110682
  85 | COc1ccc2c(C)c(C(C)=O)c(C)nc2c1 CHEMBL2104051
  86 | Cc1cccc2c1NC(=O)C2(c1ccc(OS(=O)(=O)O)cc1)c1ccc(OS(=O)(=O)O)cc1 CHEMBL2104944
  87 | NCC1CC(=O)N(Cc2ccccc2)C1 CHEMBL2104682
  88 | O=[N+]([O-])c1ccc(-c2nc3ccccc3c(N(CCO)CCO)n2)o1 CHEMBL2107101
  89 | CCN(CC)CCOc1c2occc2c(O)c2c(=O)cc(C)oc12 CHEMBL2104025
  90 | C[N+](C)(C)CC(O)CC(=O)[O-] CHEMBL1149
  91 | CCCCOC(=O)c1ccc(N)cc1 CHEMBL127516
  92 | O=C1CN=C(c2ccccc2Cl)c2cc([N+](=O)[O-])ccc2N1 CHEMBL452
  93 | CC1=CC(=O)NS(=O)(=O)O1 CHEMBL176687
  94 | CC(C)(C)NCC(O)COc1ccccc1OCC1CCCO1 CHEMBL347830
  95 | CC12CCC3c4ccc(O)cc4CCC3C1CCC2O CHEMBL286452
  96 | CNC(C)C(O)c1ccc(O)c(O)c1 CHEMBL416557
  97 | CC(=O)OC1CCC2C3C(C)CC4=CC(=O)CCC4C3CCC12C CHEMBL452329
  98 | CC(=O)NC(Cc1ccccc1)C(=O)O CHEMBL134570
  99 | COc1ccc2c3c1OC1CC(O)C=CC31CCN(C)C2 CHEMBL659
 100 | c1ccc2c(c1)Nc1ccccc1S2 CHEMBL828
 101 | CCC(=O)NS(=O)(=O)c1ccc(-c2c(C)onc2-c2ccccc2)cc1 CHEMBL1206690
 102 | CN1C2CCC1CC(OC(=O)c1c[nH]c3ccccc13)C2 CHEMBL56564
 103 | CN(C)CCN1C(=O)c2cccc3cc(N)cc(c32)C1=O CHEMBL428676
 104 | CC(C)CC(N)C(=O)O CHEMBL291962
 105 | CC(CN1CC(=O)NC(=O)C1)N1CC(=O)NC(=O)C1 CHEMBL444186
 106 | O=C(c1ccc2nonc2c1)N1CCCCC1 CHEMBL1276138
 107 | COc1ccc(S(=O)(=O)Nc2nnc(CC(C)C)s2)cc1 CHEMBL1481457
 108 | CC(C)NCC(O)c1cccc(O)c1 CHEMBL327122
 109 | O=C(COc1ccc(Cl)cc1)N1CCN(Cc2ccc3c(c2)OCO3)CC1 CHEMBL254857
 110 | COc1cc(C=C2CCCC(=Cc3ccc(O)c(OC)c3)C2=O)ccc1O CHEMBL17205
 111 | Cc1onc(-c2c(F)cccc2Cl)c1C(=O)NC1C(=O)N2C1SC(C)(C)C2C(=O)O CHEMBL222645
 112 | CC12C=CC(=O)C=C1CCC1C2CCC2(C)OC(=O)CCC12 CHEMBL1571
 113 | OCCN1CCN(C2CC(c3ccc(F)cc3)c3ccc(C(F)(F)F)cc32)CC1 CHEMBL95636
 114 | CN(C)CCC1c2ccc(Cl)cc2CCc2cccnc21 CHEMBL1738982
 115 | CC12CCC3C(C=CC4=CC(=O)CCC43C)C1CCC2(O)CCC(=O)O CHEMBL1616951
 116 | O=C1C=C(N2CC2)C(=O)C(N2CC2)=C1N1CC1 CHEMBL313302
 117 | CN1C(=O)CC(c2ccccc2)C1=O CHEMBL797
 118 | CCN(CC)CC1CCCCN1CC(=O)N1c2ccccc2C(=O)Nc2cccnc21 CHEMBL17045
 119 | OCCN1CCN(CCCN2c3ccccc3C=Cc3ccccc32)CC1 CHEMBL370753
 120 | O=C(O)CCCCCCCNC(=O)c1ccccc1O CHEMBL16503
 121 | CSc1ccc(C(=O)c2[nH]c(=O)[nH]c2C)cc1 CHEMBL249856
 122 | CS(=O)(=O)Nc1ccc(OCC(O)CNCCOc2ccc(-n3ccnc3)cc2)cc1 CHEMBL99585
 123 | CCc1nc(N)nc(N)c1-c1ccc(Cl)c(Cl)c1 CHEMBL21799
 124 | CCCCCCCCCCC(=O)O CHEMBL108030
 125 | O=C(O)C(S)C(S)C(=O)O CHEMBL1201073
 126 | C=C(c1ccccc1OCc1cccc(Cl)c1)n1ccnc1 CHEMBL27289
 127 | NCCCC(N)C(=O)O CHEMBL446143
 128 | NCC(Cl)C(O)c1cnc(N)[nH]1 CHEMBL1171272
 129 | OC(CCl)CN1CC[N+]2(CC1)CC[N+]1(CCN(CC(O)CCl)CC1)CC2 CHEMBL1187562
 130 | CN1CCC(OC(c2ccccc2)c2ccccc2)CC1 CHEMBL1492
 131 | CN1c2ccccc2C(NCCCCCCC(=O)O)c2ccc(Cl)cc2S1(=O)=O CHEMBL1289110
 132 | CC(=O)Oc1ccc(C2(c3ccc(OC(C)=O)cc3)C(=O)Nc3ccccc32)cc1 CHEMBL1402684
 133 | COc1ccc(C(=O)c2ccccc2O)c(O)c1 CHEMBL1326877
 134 | CC1=CC(=O)c2ccccc2C1=O CHEMBL590
 135 | CC1(C)SCCN(S(=O)(=O)c2ccc(Oc3ccncc3)cc2)C1C(=O)NO CHEMBL75094
 136 | CCOC(=O)NC(C)(C)Cc1ccc(Cl)cc1 CHEMBL1697686
 137 | CC(CCc1ccc(O)cc1)NCCc1ccc(O)c(O)c1 CHEMBL926
 138 | Cc1cc(N)c2cc(NC(=O)Nc3ccc4nc(C)cc(N)c4c3)ccc2n1 CHEMBL87223
 139 | COc1ccc(N2CC(CN3CCC(O)(c4ccc5c(c4)OCO5)CC3)OC2=O)cc1 CHEMBL45686
 140 | NC(=O)CCCCC1CCSS1 CHEMBL1403899
 141 | CC(C)(C)[SiH2]O[Si](C)(C)O[SiH2]C(C)(C)C CHEMBL1200838
 142 | NC(=O)c1ccc([N+](=O)[O-])cc1Cl CHEMBL1450565
 143 | Cc1cccc(N2CC(CO)OC2=O)c1 CHEMBL18116
 144 | Nc1cc2[nH]cnc2c(=O)[nH]1 CHEMBL31882
 145 | CC1CC2=CC(=O)CCC2(C)C2CCC3(C)C(CCC3(C)O)C12 CHEMBL259548
 146 | COc1ccc2c(c1)c1c3n2CCN(C)C3=NCC1 CHEMBL1619017
 147 | NCc1cccnc1 CHEMBL1988272
 148 | O=P(O)(O)Oc1ccc(C(c2ccc(OP(=O)(O)O)cc2)c2ccccn2)cc1 CHEMBL2111180
 149 | [Na+].NC(CCC(=O)[O-])C(=O)O CHEMBL2107256
 150 | [Na+].[K+].O=C([O-])C(O)C(O)C(=O)[O-] CHEMBL2219738
 151 | CCCN(c1ccncc1)n1ccc2ccccc21 CHEMBL29835
 152 | CC(C)NCC(O)c1ccc(O)c(NS(C)(=O)=O)c1 CHEMBL30746
 153 | CCOc1ccc(S(=O)(=O)O)c2cccnc12 CHEMBL1356732
 154 | CCOCn1cnc2c1c(=O)n(CCCCC(C)(C)O)c(=O)n2C CHEMBL2104934
 155 | CN1CCCCC1C(C)(C)OC(=O)C(c1ccccc1)c1ccccc1 CHEMBL2106597
 156 | CCOc1ccc2nc(SC(C)(C(=O)O)c3ccccc3)sc2c1 CHEMBL2107083
 157 | O=C(c1ccccc1)N1CC2COCC2C1 CHEMBL2106524
 158 | C=CC1(O)CCC2C3CCC4=C(CCC(=O)C4)C3CCC21C CHEMBL2106812
 159 | O=c1[nH]c2ccccc2c2cc(CO)nn21 CHEMBL2106923
 160 | CC(=O)NC(CSCC(C)C(=O)c1ccccc1)C(=O)O CHEMBL2104015
 161 | Cc1cccc(Cl)c1NC(=O)C=C1SCC(=O)N1C CHEMBL2106933
 162 | COc1ccc(C2Sc3ccccc3N(CCN(C)C(C)C)C(=O)C2OC(C)=O)cc1 CHEMBL2107305
 163 | Cc1nnc(NS(=O)(=O)c2ccc(NC(=O)c3ccccc3C(=O)O)cc2)s1 CHEMBL2106914
 164 | COc1ccc(-n2c(C)c[nH]c2=O)cc1 CHEMBL2104723
 165 | CCCC(C)(O)C1CC23C=CC1(OC)C1Oc4c5c(ccc4OC(C)=O)CC2N(C)CCC513 CHEMBL2104593
 166 | CCOC(=O)C1(c2cccc(O)c2)CCN(C)CC1 CHEMBL1182665
 167 | CN(CCC1c2ccccc2COc2ccccc21)CC(O)COc1ccccc1 CHEMBL2106287
 168 | CCCCCCn1c(=O)c2c(ncn2C)n(C)c1=O CHEMBL2105338
 169 | CC(NCCC(=O)C1CCCCC1)C(O)c1ccccc1 CHEMBL2104023
 170 | O=C1CCCCC1c1c(O)ccc2ccccc21 CHEMBL2106809
 171 | O=C1N=C2SCCN2C(=O)C1Cc1ccc(Cl)cc1 CHEMBL2106465
 172 | NC(Cc1ccccn1)c1ccccc1 CHEMBL2107647
 173 | N=C(N)C(O)c1ccc2c(c1)OCO2 CHEMBL2104702
 174 | CC12CCC3c4ccc(OC5CCCC5)cc4CCC3C1CC(O)C2O CHEMBL2107004
 175 | CCOC(=O)N(Cc1ccccc1)C1CC1 CHEMBL2104204
 176 | CN1CCC23c4c5c(O)ccc4CC1C2CCC(C)(O)C3O5 CHEMBL2104436
 177 | CC1NC(C2CC2)CC1c1ccc(Cl)cc1 CHEMBL2105225
 178 | CN(C)CCCOC1(Cc2ccccc2)CCCCCC1 CHEMBL2110767
 179 | CCN(CC)CCCNCc1cc(Cl)c2cccnc2c1O CHEMBL2110791
 180 | CNC1C(O)C(OC2C(N)CC(N)C(OC3OC(CN)C(O)C(O)C3O)C2O)OCC1(C)O CHEMBL2110604
 181 | CC(CSC(=O)C(C)(C)C)C(=O)N(CC(=O)O)C1CCCC1 CHEMBL2051970
 182 | CN1CCC23c4c5c(O)ccc4CC1C2CCCC3O5 CHEMBL2106274
 183 | OC(CN1CCCCC1)c1cc(-c2ccccc2)on1 CHEMBL2105453
 184 | COc1cc(C=CC(N)=O)cc(OC)c1OC CHEMBL2107098
 185 | O=C(c1ccc(Cl)cc1)n1cc(Cc2nnn[nH]2)c2ccccc21 CHEMBL2104903
 186 | Cc1cc(C(=O)c2cc(I)c(O)c(I)c2)c(C)o1 CHEMBL2107414
 187 | NC(=O)C(CCN1CCN2CCCC2C1)(c1ccccc1)c1ccccc1 CHEMBL2106959
 188 | CC(C)NC(=N)NC(=N)Nc1ccc(Cl)c(Cl)c1 CHEMBL1213553
 189 | O=c1[nH]c2ccccc2n1C1CCN(CCCc2noc3cc(F)ccc23)CC1 CHEMBL2111040
 190 | O=C1CCC2C3Cc4cccc(O)c4C2(CCN3CC2CC2)C1 CHEMBL2104366
 191 | CC(=O)c1ccc2c(c1)N(CC(C)N(C)C)c1ccccc1S2 CHEMBL2104054
 192 | C=C(CC(=O)c1ccc(-c2ccccc2Cl)cc1)C(=O)O CHEMBL2104844
 193 | Cc1cc(NS(=O)(=O)c2ccc(N)cc2)n(-c2cccc(Cl)c2)n1 CHEMBL2104945
 194 | O=S1(=O)CCNCN1 CHEMBL2104848
 195 | COc1ccc(C(=O)N=c2[cH-][n+](N3C(C)CCCC3C)no2)cc1 CHEMBL2104889
 196 | CCc1c(-c2ccccc2)[nH]n(C2CCN(C)CC2)c1=O CHEMBL2104576
 197 | C=C(C)CNCC(=O)N(C)c1ccc(Cl)cc1C(=O)c1ccccc1 CHEMBL2106239
 198 | CC(C)C1(C(C)C)OCC(CO)O1 CHEMBL2104577
 199 | CC(=O)OCC(=O)OCCC(SC(=O)c1ccco1)=C(C)N(C=O)Cc1cnc(C)nc1N CHEMBL2104090
 200 | CC1CC(OC(=O)CN2CCCC2=O)CC(C)(C)C1 CHEMBL2105253
 201 | CC1(C)C2CCC1(C)C(=O)C2Br CHEMBL2106181
 202 | CC1C=CC(C)N1CC(=O)N=C(N)N CHEMBL2104785
 203 | CN1C(CC(=O)c2ccccc2)CCCC1CC(O)c1ccccc1 CHEMBL2103769
 204 | NCCOC(c1ccc(F)cc1)c1ccc(F)cc1 CHEMBL2105476
 205 | CN1C2CCC1CC(OC(=O)C(C)(CO)c1ccccc1)C2 CHEMBL2104939
 206 | CCOc1ccccc1C(=O)NN=C(C)C(=O)O CHEMBL2107047
 207 | O=C(NCCCN1CCOCC1)c1ccc(Cl)cc1 CHEMBL2104298
 208 | COc1ccc2[nH]c(C)c(CC(=O)NO)c2c1 CHEMBL2104618
 209 | c1ccc(C2(c3ccccc3)OCC(C3CCCCN3)O2)cc1 CHEMBL72982
 210 | CC(=O)OC(Cc1ccccc1)(c1ccccc1)C(C)CN1CCCC1 CHEMBL2110705
 211 | CN1C2CCC1CC(NC(=O)c1cc(Cl)cc3c1OC(C)(C)C3)C2 CHEMBL2111147
 212 | CNCCCC1(c2ccccc2)OC(C)(C)c2ccccc21 CHEMBL299233
 213 | CCN(CC)CCn1c(=O)oc2ccccc2c1=O CHEMBL2110855
 214 | CNCC(O)CC12CCC(C3CCCCC31)C1CCCCC12 CHEMBL2111067
 215 | [Ca+2].[Ca+2].[Ca+2].O=P([O-])([O-])[O-].O=P([O-])([O-])[O-] CHEMBL2106566
 216 | [K+].[K+].NC(CC(=O)[O-])C(=O)[O-] CHEMBL2106910
 217 | CC1CCCCN1CCCOC(=O)c1ccccc1 CHEMBL127865
 218 | CC1CC(OC(=O)c2ccccc2)CC(C)(C)N1 CHEMBL2110936
 219 | CCCc1cc2c(s1)CNC1CCc3cc(OC(C)=O)c(OC(C)=O)cc3C21 CHEMBL2104655
 220 | CC(CN(C(=O)c1ccc(C#N)cc1)c1ccccn1)N1CCN(c2cccc3c2OCCO3)CC1 CHEMBL372205
 221 | CCC(=O)N(c1ccccn1)C(C)CN1CCCCC1 CHEMBL2110985
 222 | CCCCN1CCC(CNC(=O)c2c3ccccc3n3c2OCCC3)CC1 CHEMBL356359
 223 | OC(c1ccccc1)(c1ccccc1)C1CCNCC1 CHEMBL127508
 224 | CC(C)(C)NCC(O)COc1ccccc1-c1ccccc1 CHEMBL2104145
 225 | CN(C)CCN(Cc1ccsc1)c1ccccn1 CHEMBL2107485
 226 | CCNC1=Nc2ccc(Cl)cc2C(c2ccccc2)S1 CHEMBL2106208
 227 | CC1=C(C(=O)O)N2C(=O)C(NC(=O)C(N)c3ccc(O)c(Cl)c3)C2SC1 CHEMBL2106477
 228 | CCCOC(=O)c1ccc(N)cc1 CHEMBL2107010
 229 | CCCn1c2nc(C34CC5CC3CC(C4)C5)[nH]c2c(=O)n(CCC)c1=O CHEMBL2103819
 230 | CCCCc1ccc(C(N)=O)nc1 CHEMBL2106646
 231 | CN1CCC23CCCCC2C1Cc1ccc(O)cc13 CHEMBL20803
 232 | CN(C)C(=O)COc1ccc2c(c1)CC(NCC(O)c1ccc(O)c(CCO)c1)CC2 CHEMBL2111083
 233 | CCCCCCC(C(C)O)n1cnc2c1nc[nH]c2=O CHEMBL2304038
 234 | CC(Oc1ccccc1)C(=O)NC1C(=O)N2C1SC(C)(C)C2C(=O)O CHEMBL1614637
 235 | C#CCNC1CCc2ccc(OC(=O)N(C)CC)cc21 CHEMBL255231
 236 | C=CCc1ccccc1OCC(CNC(C)C)=NO CHEMBL2105963
 237 | NC(=O)c1cnc2[nH]ccc2c1NC1C2CC3CC1CC(O)(C3)C2 CHEMBL3137308
 238 | CCC1(O)C(=O)OCc2c(=O)n3c(cc21)-c1nc2ccccc2c(C=NOC(C)(C)C)c1C3 CHEMBL113051
 239 | O=C1c2ccccc2CN2C(=O)c3ccccc3CN12 CHEMBL1536675
 240 | Cc1cnc(C(=O)NCCc2ccc(S(=O)(=O)NC(=O)NC3CCCCC3)cc2)cn1 CHEMBL1073
 241 | CCN(CC)CCNc1ccc(CO)c2sc3ccccc3c(=O)c12 CHEMBL22077
 242 | CCCCCCCCCCCCCCCC(O)C(N)CO CHEMBL1442934
 243 | NC(C(=O)NC1C(=O)N2C(C(=O)O)=C(CSc3c[nH]nn3)CSC12)c1ccc(O)cc1 CHEMBL1095284
 244 | CSCC1CN(N=Cc2ccc([N+](=O)[O-])o2)C(=O)O1 CHEMBL514315
 245 | CCOC(=O)c1ccccc1C(=O)OCC CHEMBL388558
 246 | Sc1[nH]cnc2nncc1-2 CHEMBL119423
 247 | NC(Cc1ccccc1)C(=O)O CHEMBL301523
 248 | CC1CC(=O)NN=C1c1cc(-n2ccnc2)cs1 CHEMBL2104670
 249 | CC1NC(=O)COC1c1ccccc1 CHEMBL2106282
 250 | NC(=O)NCCN1CCN(c2cccc(C(F)(F)F)c2)CC1 CHEMBL2106753
 251 | Cc1ccc(F)cc1NC1=NCCN1 CHEMBL2106760
 252 | Fc1ccc(NC(=S)Nc2cc(Cl)cc(Cl)c2)cc1 CHEMBL2105198
 253 | CCCCCC(C(=O)N1CCCC1C(=O)CC(CCCNC(=N)N)C(=O)O)N(CC)C(=O)CN CHEMBL2107753
 254 | CC(C(=O)O)c1ccc(C(=O)c2cccs2)c(Cl)c1 CHEMBL2104170
 255 | Cc1cc(=O)oc2cc(OCCN3CCOCC3)cc(OCCN3CCOCC3)c12 CHEMBL2105164
 256 | C=CCC1CN(C)CCC1(OC(=O)CC)c1ccccc1 CHEMBL2103995
 257 | Cc1cc(N(C)C)ccc1[PH](=O)O CHEMBL2105341
 258 | CC(C)N1CCNC1=S CHEMBL2103937
 259 | CCC1(O)CCN2CCc3ccc(C)cc3C2C1 CHEMBL2105550
 260 | Cc1cc(C)nc(NS(=O)(=O)c2ccc(N=Nc3ccc(O)c(C(=O)O)c3)cc2)n1 CHEMBL2107040
 261 | CC(C)[N+](C)(C)CC(O)COc1cccc2ccccc21 CHEMBL1710851
 262 | CN(C)CCN1c2ccccc2SC(c2ccccc2)CC1=O CHEMBL2111123
 263 | CC(C)NCC(O)c1ccccc1Cl CHEMBL1902627
 264 | C=CCC(Cc1cc(OC)c(OC)c(OC)c1)NC CHEMBL2111182
 265 | COC1CC2CC(OC(=O)C(O)(c3ccccc3)c3ccccc3)CC1[N+]2(C)C CHEMBL2111174
 266 | CCCCCOc1ccccc1C(N)=O CHEMBL2105369
 267 | COc1ccc(N(CCCC(=O)O)C(=O)c2ccc(Cl)cc2)cc1 CHEMBL2107589
 268 | CC(=O)NC(CCSC(=O)C(C)(C)Oc1ccc(Cl)cc1)C(=O)O CHEMBL2107469
 269 | COCCCP(CCCOC)CCCOC CHEMBL2107255
 270 | CC(C)Oc1ccccc1-c1cc(=O)c2cc(C(=O)O)ccc2o1 CHEMBL2106345
 271 | CCC(C#N)(CC(C)N(C)C)c1ccccc1 CHEMBL2104277
 272 | CN(CCO)c1nc2c(c(=O)n(C)c(=O)n2C)n1C CHEMBL2104570
 273 | CCOC(=O)C1(c2ccccc2)CCN(CCOCc2ccccc2)CC1 CHEMBL2104234
 274 | Cc1cc(O)c2c3[nH]c(-c4ccco4)nc3ccc2n1 CHEMBL2104697
 275 | O=C(O)CSC(SCC(=O)O)SCC(=O)O CHEMBL2105322
 276 | Oc1ccc(C(O)CNC2CCC2)cc1O CHEMBL2106796
 277 | CCOP(=S)(OCC)Oc1cc(C)nc(N(C)C)n1 CHEMBL2106985
 278 | CCCCOc1ccc(C(=O)OCCOCCN(CC)CC)cc1N CHEMBL2110889
 279 | O=C(O)CCCC=CCC1C(O)CC(O)C1C=CC(O)COc1cccc(C(F)(F)F)c1 CHEMBL2220419
 280 | CCCN1CCCC2c3cc(O)ccc3OCC21 CHEMBL2220428
 281 | C#Cc1cnc2nc(O)n(C(CC)CC)c2n1 CHEMBL3039529
 282 | O=c1ccc2c(C(O)CNCCCCCCOCC(F)(F)c3ccccc3)ccc(O)c2[nH]1 CHEMBL3039530
 283 | Cn1ncc(Cl)c1-c1cc(C(=O)NC(CN)Cc2ccc(F)c(F)c2)oc1Cl CHEMBL3137336
 284 | Oc1cccc(O)c1O CHEMBL307145
 285 | O=C(O)c1ccccc1C(=O)Nc1ccc(S(=O)(=O)Nc2nccs2)cc1 CHEMBL1524273
 286 | CC12CCC3C(CCC4CC(O)CCC43C)C13OC3CC2c1ccc(=O)oc1 CHEMBL250172
 287 | CC(O)C(N)C(=O)O CHEMBL291747
 288 | O=C(Nc1ccc(O)cc1)c1ccccc1O CHEMBL389507
 289 | O=c1oc2cc(O)ccc2s1 CHEMBL442687
 290 | OC(Cn1ccnc1)c1ccc(CCc2ccccc2)cc1 CHEMBL41849
 291 | CC(=N)N1CCC(SC2=C(C(=O)O)N3C(=O)C(C(C)O)C3C2)C1 CHEMBL339323
 292 | CN(C(=O)C=Cc1ccoc1)C1CCC2(O)C3Cc4ccc(O)c5c4C2(CCN3CC2CC2)C1O5 CHEMBL267495
 293 | CC(C)(C)NCC(O)COc1cc(Cl)ccc1Cl CHEMBL156791
 294 | COc1ccc(-c2cc(C(F)F)nn2-c2ccc(S(N)(=O)=O)cc2)cc1F CHEMBL28636
 295 | O=c1[nH]c2n[nH]cc2c(=O)[nH]1 CHEMBL859
 296 | COc1ccc2c(c1)C13CCCCC1C(C2)N(C)CC3 CHEMBL22207
 297 | Cc1c(C(N)=O)cc([N+](=O)[O-])cc1[N+](=O)[O-] CHEMBL472565
 298 | N#CC(c1ccc(Cl)cc1)c1c(Cl)cc(-n2ncc(=O)[nH]c2=O)cc1Cl CHEMBL284733
 299 | CCCC(=O)OC(C(Cl)(Cl)Cl)P(=O)(OC)OC CHEMBL1570266
 300 | CCC1Nc2cc(Cl)c(S(N)(=O)=O)cc2S(=O)(=O)N1 CHEMBL2106262
 301 | CC[N+]1(CCOC(=O)c2cc(OC)c(OC)c(OC)c2)CCCC1 CHEMBL2111183
 302 | C[N+]1(CC2CC2)CCC23CC(=O)CCC2(O)C1Cc1ccc(C(N)=O)c(O)c13 CHEMBL2364619
 303 | COc1ccc2c(c1)[nH]c1c2CCN2CC3C(C)OC(OC)=C(C(=O)OCCN(C)C)C3CC12 CHEMBL2106350
 304 | Cn1ncnc1C1c2n[nH]c(=O)c3cc(F)cc(c32)NC1c1ccc(F)cc1 CHEMBL3137320
 305 | CCc1nn(CCCN2CCN(c3cccc(Cl)c3)CC2)c(=O)n1CC CHEMBL1743259
 306 | NS(=O)(=O)c1ccc(C(=O)O)cc1 CHEMBL414
 307 | Cc1ncc2c(c1O)COC2c1ccc(Cl)cc1 CHEMBL191886
 308 | CC(=O)C1CCC2C3CCC4CC(O)CCC4(C)C3C(=O)CC12C CHEMBL190279
 309 | CC(=O)NC(CCC([O-])=C[N+]#N)C(=O)O CHEMBL475736
 310 | Cc1cc(Cn2nnc3c2nc(N)nc3-c2ccco2)ccc1N CHEMBL447664
 311 | CCC(CO[N+](=O)[O-])(CO[N+](=O)[O-])CO[N+](=O)[O-] CHEMBL488280
 312 | Cc1ccc(S(=O)(=O)C(CC#Cc2ccc(Cl)cc2)C(=O)O)cc1 CHEMBL267770
 313 | Nc1nc2[nH]cnc2c(=S)[nH]1 CHEMBL727
 314 | OCC(O)C(O)C(OC1OC(CO)C(O)C(O)C1O)C(O)CO CHEMBL63558
 315 | COc1ccc(-c2nc(C(F)(F)F)[nH]c2-c2ccc(OC)cc2)cc1 CHEMBL430150
 316 | CCN(CC)CCNC(=O)c1cc(S(C)(=O)=O)ccc1OC CHEMBL84158
 317 | CC1=NN(CCOc2ccc3ccccc3c2)C(=O)C1 CHEMBL8425
 318 | Cc1nc(N)nc(N)c1-c1ccc(Cl)c(Cl)c1 CHEMBL264373
 319 | CC(=O)NC(CC(=O)O)C(=O)NC(CCC(=O)O)C(=O)O CHEMBL1329032
 320 | CCCCC1=NC2(CCCC2)C(=O)N1Cc1ccc(-c2ccccc2-c2nn[nH]n2)cc1 CHEMBL1513
 321 | OCC(Br)(Br)Br CHEMBL1697852
 322 | Oc1ccc2[nH]cc(CCCCN3CC=C(c4ccccc4)CC3)c2c1 CHEMBL431367
 323 | CCc1nc(N)nc(N)c1-c1ccc(Cl)cc1 CHEMBL36
 324 | ClC(Cl)=C(Cl)Cl CHEMBL114062
 325 | OCC1OC(n2cnc3c2ncnc3S)C(O)C1O CHEMBL448290
 326 | Cc1ccc(-n2nccn2)c(C(=O)N2CCN(c3nc4cc(Cl)ccc4o3)CCC2C)c1 CHEMBL1083659
 327 | CNc1nc(Cl)c(SC)c(N2CCN(C)CC2)n1 CHEMBL407641
 328 | CC(=O)Oc1cccc2c1C(=O)c1c(OC(C)=O)cc(C(=O)O)cc1C2=O CHEMBL41286
 329 | CC(=O)OCC1=C(C(=O)O)N2C(=O)C(NC(=O)CSc3ccncc3)C2SC1 CHEMBL1599
 330 | CCCCCN(C)CCC(O)(P(=O)(O)O)P(=O)(O)O CHEMBL997
 331 | Fc1ccc(Cn2c3ccccc3nc2NC2CCNCC2)cc1 CHEMBL61301
 332 | CC1(O)CCC2C3CCC4=CC(=O)CCC4=C3C=CC21C CHEMBL166444
 333 | Cc1ccc(S(=O)(=O)NC(=O)NN2CC3CCCC3C2)cc1 CHEMBL427216
 334 | CCc1cccc2cc(C(O)CNC(C)(C)C)oc21 CHEMBL296035
 335 | Cc1nc2c(NCc3c(C)cccc3C)cc(C(=O)NCCO)cn2c1C CHEMBL497011
 336 | C=CCNc1nc(NCC=C)nc(N2CCN(C(c3ccc(F)cc3)c3ccc(F)cc3)CC2)n1 CHEMBL1183717
 337 | OCc1ccccc1OC1OC(CO)C(O)C(O)C1O CHEMBL462997
 338 | CNNCc1ccc(C(=O)NC(C)C)cc1 CHEMBL1321
 339 | CCN(CC)C(=O)C1CN2CCc3cc(OC)c(OC)cc3C2CC1OC(C)=O CHEMBL1201250
 340 | CN(C)CCC(c1ccc(Cl)cc1)c1ccccn1 CHEMBL1201353
 341 | O=C(Nc1ncc([N+](=O)[O-])s1)c1cccs1 CHEMBL1082354
 342 | Cc1cccc(C(=O)O)c1O CHEMBL448399
 343 | Cc1c2[nH]c3ccc(O)cc3c2c(C)c2c[n+](C)ccc12 CHEMBL16699
 344 | CCCn1cnc2c1c(=O)n(CCCCC(C)=O)c(=O)n2C CHEMBL1079905
 345 | COc1cc2c(cc1OC)-c1cc(=Nc3c(C)cc(C)cc3C)n(C)c(=O)n1CC2 CHEMBL285913
 346 | CC(Cl)C(=O)Nc1ccc(C2=NNC(=O)CC2C)cc1 CHEMBL116368
 347 | COc1ccc(Cl)cc1C(=O)NCCc1ccc(C(=O)O)cc1 CHEMBL149930
 348 | [K+].[K+].[K+].O=C([O-])CC(O)(CC(=O)[O-])C(=O)[O-] CHEMBL1200458
 349 | CC(C)S(=O)(=O)n1c(N)nc2ccc(C(=NO)c3ccccc3)cc21 CHEMBL283403
 350 | CCOP(=S)(OCC)Oc1ccc(Cl)cc1Cl CHEMBL1396626
 351 | NS(=O)(=O)c1ccc(N2C(=O)CC(c3ccccc3)C2=O)c(Cl)c1 CHEMBL315877
 352 | O=C1NCCN1CCN1CCN(C2CC(c3ccc(F)cc3)c3ccccc32)CC1 CHEMBL73461
 353 | O=C(O)c1cc(-c2ccccc2)nc2ccccc21 CHEMBL348000
 354 | CC(C(=O)O)c1ccc(C(=O)c2ccccc2)s1 CHEMBL365795
 355 | CCOCc1nc2c(c3ccccc3nc2N)n1CC(C)(C)O CHEMBL383322
 356 | Cn1cnc2c1cc(C(=O)NOCCO)c(Nc1ccc(Br)cc1Cl)c2F CHEMBL1614701
 357 | CC(=O)OC1(C(C)=O)CCC2C3C=C(Cl)C4=CC(=O)C5CC5C4(C)C3CCC21C CHEMBL139835
 358 | COc1cc2c(c(OC)c1OC)-c1ccc(OC)c(=O)cc1C(NC(C)=O)CC2 CHEMBL107
 359 | CC(O)(CC(=O)O)C1CCCCC1 CHEMBL52091
 360 | Nc1nccs1 CHEMBL344760
 361 | CCOC(=O)NC1=C(N2CC2)C(=O)C(NC(=O)OCC)=C(N2CC2)C1=O CHEMBL36016
 362 | O=C(O)CCCCC(=O)O CHEMBL1157
 363 | C=CCN1CCCC1CNC(=O)c1cc2nn[nH]c2cc1OC CHEMBL290194
 364 | O=c1[nH]c2ccccc2n1CCCN1CCN(C(c2ccccc2)c2ccccc2)CC1 CHEMBL13828
 365 | CC1CS(=O)(=O)CCN1N=Cc1ccc([N+](=O)[O-])o1 CHEMBL290960
 366 | COc1cc(C2c3cc4c(cc3C(O)C3COC(=O)C32)OCO4)cc(OC)c1OC CHEMBL61
 367 | NS(=O)(=O)Oc1ccc2c(c1)oc(=O)c1c2CCCCC1 CHEMBL286738
 368 | NCCCCC(N)C(=O)O CHEMBL8085
 369 | O=c1ccc2ccccc2o1 CHEMBL6466
 370 | CNC(=O)OCc1cccc(COC(=O)NC)n1 CHEMBL1620144
 371 | CC(COc1ccccc1)NN CHEMBL1909286
 372 | C(COCCOCC1CO1)OCCOCC1CO1 CHEMBL460287
 373 | CC(N)(Cc1ccc(O)cc1)C(=O)O CHEMBL1330596
 374 | C[N+](C)(C)CCOP(=O)([O-])OCC(O)CO CHEMBL1567463
 375 | CCn1cc(C(=O)O)c(=O)c2cc(F)c(N3CCN(C)CC3)cc21 CHEMBL267648
 376 | CCNC1CN(CCCOC)S(=O)(=O)c2sc(S(N)(=O)=O)cc21 CHEMBL220491
 377 | Cc1cccc(O)c1 CHEMBL298312
 378 | O=P1(N(CCCl)CCCl)OCCCN1CCCl CHEMBL462019
 379 | O=C(O)CCc1nc2ccccc2[nH]1 CHEMBL596009
 380 | OCc1cc(C(O)CNCCCCCCOCCOCc2c(Cl)cccc2Cl)ccc1O CHEMBL1198857
 381 | CC1CC(=O)NN=C1c1ccc(NN=C(C#N)C#N)cc1 CHEMBL313136
 382 | COc1ccc(-c2c(Cl)ncn2-c2ccc(S(N)(=O)=O)cc2)cc1F CHEMBL435381
 383 | O=C1c2cccc3cc([N+](=O)[O-])cc(c32)C(=O)N1CCN1CCCC1 CHEMBL46874
 384 | O=C(C1CC(N2CCN(c3ncccn3)CC2)CN1)N1CCC(F)(F)C1 CHEMBL515387
 385 | CCOC(=O)CC(O)(CC(=O)OCC)C(=O)OCC CHEMBL464988
 386 | Cc1[nH]c2cccc(OCC(O)CNCCOc3ccccc3)c2c1Cl CHEMBL1742464
 387 | Cc1ccc(C23CC2CNC3)cc1 CHEMBL511099
 388 | C=CC(=O)Nc1cc2c(cc1OCCCN1CCOCC1)ncnc2Nc1ccc(F)c(Cl)c1 CHEMBL31965
 389 | CC(Oc1c(Cl)cccc1Cl)C1=NCCN1 CHEMBL17860
 390 | CN1c2ccc(Cl)cc2C(c2ccccc2)=NCC1=S CHEMBL1891606
 391 | CCc1ccc(C(=O)C(C)CN2CCCC2)cc1 CHEMBL1797127
 392 | CN1CCC(=C2c3ccccc3CCc3cccnc32)CC1 CHEMBL946
 393 | C#CC1(O)CCC2C3CCC4=CC(=O)CCC4=C3C=CC21C CHEMBL1908319
 394 | CN(C)c1ccc(C2CC3(C)C(CCC3(O)C=CCO)C3CCC4=CC(=O)CCC4=C23)cc1 CHEMBL1908329
 395 | CC1(O)CCC2C3CCC4=C(O)C(=O)CCC4(C)C3CCC21C CHEMBL1908006
 396 | NC(=O)C1CCN(CCCN2c3ccccc3Sc3ccc(Cl)cc32)CC1 CHEMBL1909072
 397 | COC(=O)CCC[N+](C)(C)C CHEMBL1896433
 398 | O=S(=O)(O)CCCS(=O)(=O)O CHEMBL2111092
 399 | CC[N+](C)(C)CCSCC[N+](C)(C)CC CHEMBL2110709
 400 | c1c(CCc2ccncc2)c2ccccc2n1Cc1ccccc1 CHEMBL2110797
 401 | C=C(CN(C)C)C(Cc1ccccc1)(OC(=O)CC)c1ccccc1 CHEMBL2104265
 402 | CCN(CC)Cc1ccc2oc(-c3ccccc3)c(C)c(=O)c2c1 CHEMBL2104916
 403 | CC(C)(CO)NCC(O)c1ccccc1 CHEMBL2106269
 404 | OCC(O)C1OC2OC(C(Cl)(Cl)Cl)OC2C1O CHEMBL2104181
 405 | CNC(C)C(=O)c1ccc(OC)cc1 CHEMBL2106893
 406 | O=C(O)c1ccccc1C(=O)c1ccc(O)c(-c2ccccc2)c1 CHEMBL2104248
 407 | CC(=O)N=c1sccn1CC(O)c1cccs1 CHEMBL2105962
 408 | COc1cc(OC)c(C(=O)OCCN2CCOCC2)c(OC)c1 CHEMBL2106750
 409 | O=C1NC(=O)C2(c3ccc(Cl)cc3)CC12 CHEMBL2104097
 410 | CN1CCN(C2=Nc3cc(Cl)ccc3Cc3sccc32)CC1 CHEMBL2105484
 411 | Oc1cccc(Oc2nnn[nH]2)c1 CHEMBL2106850
 412 | O=C(CCn1nnc(-c2cccc(Br)c2)n1)N1CCCCC1 CHEMBL2106508
 413 | COc1cc(C(=O)NC(COc2ccccc2)CN2CCCC2)cc(OC)c1OC CHEMBL2106241
 414 | CC(N)C(=O)NC(CCC(=O)C=[N+]=[N-])C(=O)NC(CCC(=O)C=[N+]=[N-])C(=O)O CHEMBL2105946
 415 | CC(=O)NC(CSC(=O)c1ccccc1OC(C)=O)C(=O)O CHEMBL2104494
 416 | O=S(=O)(O)c1ccc2[nH]c(-c3ccccc3)nc2c1 CHEMBL1987518
 417 | COC1OC(C(COCc2ccccc2)OCc2ccccc2)C(OCc2ccccc2)C1O CHEMBL2105173
 418 | NC(=O)c1[nH]nc(C2OC(CO)C(O)C2O)c1O CHEMBL2105330
 419 | CCCCCCCCCNc1ncnc2[nH]ccc21 CHEMBL2106899
 420 | COc1cc(C(=O)OCCCNCC2CC2(c2ccccc2)c2ccccc2)cc(OC)c1OC CHEMBL2107590
 421 | CC1=CC(=NOCC(=O)O)c2ccccc2C1=O CHEMBL2110691
 422 | Cn1c2ncn(CC(O)CN3CCN(CCCSc4ccccc4)CC3)c2c(=O)n(C)c1=O CHEMBL155962
 423 | CN1C2=CC(=O)C(=NNC(N)=O)C=C2CC1S(=O)(=O)O CHEMBL1697827
 424 | CC1(NC2=NS(=O)(=O)C3SC(Cl)=CC3N2)CC1 CHEMBL2107789
 425 | CC(C(=O)O)c1cccc2c(-c3ccccc3)coc21 CHEMBL2107396
 426 | CC(C)CN1CC2CN(C(C)C)CC(C1)C21CCCCC1 CHEMBL2104579
 427 | CCN(CC)CCOc1ccc(C(=O)CCc2ccccc2)cc1 CHEMBL2104343
 428 | Nc1c(NC(=O)C(F)(F)C(F)F)cc(C(F)(F)F)cc1[N+](=O)[O-] CHEMBL2106844
 429 | c1ccc2c(c1)Sc1ccccc1N2CCCN1CCN(CCC2OCCCO2)CC1 CHEMBL2106987
 430 | CC(C)N1CCN=C1CN1CCCCSc2ccc(Cl)cc21 CHEMBL2104610
 431 | CCN1CCCC1CNC(=O)c1cc(C(C)=O)ccc1OC CHEMBL2106206
 432 | COc1ccccc1Oc1c(CS(=O)(=O)c2ccc(C)cn2)nc(-c2ccncc2)nc1OC CHEMBL2107803
 433 | CCCN1CC(NC(=O)N(CC)CC)CC2c3cccc4[nH]cc(c43)CC21 CHEMBL2106986
 434 | COc1ccc(C=NNC(=O)c2ccncc2)cc1OC CHEMBL2104481
 435 | CC1(C)OC2C3OC(C)(C)OCC3OC2(C(=O)O)O1 CHEMBL2110720
 436 | COc1cc2nc(N(C)CCCNC(=O)C3CCCO3)nc(N)c2cc1OC CHEMBL709
 437 | Cc1ccsc1C=CC1=NCCCN1C CHEMBL1240978
 438 | O=C(Cn1ccnc1)c1ccc2ccccc2c1 CHEMBL416801
 439 | Oc1ccc(CCCCNCC(O)c2ccc(O)c(O)c2)cc1 CHEMBL1201251
 440 | Cc1cccc(Nc2cc(Cl)nc(SCC(=O)NCCO)n2)c1C CHEMBL1908320
 441 | CCCC(C)(O)C1CC23C=CC1(O)C1Oc4c5c(ccc4O)CC2N(C)CCC513 CHEMBL1908334
 442 | NC(=O)C1c2ccccc2CCc2ccccc21 CHEMBL1868301
 443 | CC(CN1CCCC1)C(=O)c1ccc(C(F)(F)F)cc1 CHEMBL1951050
 444 | Cc1c(CN2CCN(C(=O)C(C)O)CC2)sc2c1nc(-c1cnc(N)nc1)nc2N1CCOCC1 CHEMBL1922094
 445 | [O-][n+]1cccc(CO)c1 CHEMBL1985503
 446 | O=[N+]([O-])c1cccc(C2CN3CCSC3=N2)c1 CHEMBL2110956
 447 | C=CCOc1cc(Cl)ccc1C(=O)NCCN(CC)CC CHEMBL2103989
 448 | O=[N+]([O-])OCC(O[N+](=O)[O-])C(CO[N+](=O)[O-])O[N+](=O)[O-] CHEMBL2107583
 449 | CCCCC(=O)OC1C(C=O)=CC(O)C(O)C1O CHEMBL2105321
 450 | CC(C)C(CCN(C)C)(C(N)=O)c1cccc2ccccc21 CHEMBL2107641
 451 | CCCCOCCOC(=O)C(c1ccccc1)N1CCCCC1 CHEMBL2104630
 452 | CCC1C(O)N2C3CC45c6ccccc6N(C)C4C2CC1C3C5O CHEMBL2105617
 453 | NC(CCC(=O)NCCS(=O)(=O)O)C(=O)O CHEMBL2106758
 454 | CC=C(C)C(=O)OC1CC2CCC(C1)N2C CHEMBL2107120
 455 | CN(C)c1cccc2c1cccc2S(=O)(=O)Nc1ccc(NC(=O)C(C)(C)COC(=O)CN)cc1 CHEMBL2104762
 456 | NNC(=O)OC1CC2CCC(C1)N2C(=O)Oc1ccccc1 CHEMBL2104515
 457 | OC(OCC1OC(O)C(O)C(O)C1O)C(Cl)(Cl)Cl CHEMBL2105990
 458 | CCOC(=O)C1(c2ccccc2)CCN(CCC(O)c2ccccc2)CC1 CHEMBL2105385
 459 | CCCCc1ccc(NC(=O)CN(CC(=O)O)CC(=O)O)cc1 CHEMBL2104651
 460 | CC(=O)C1(O)CCC2C3CCC4=CC(=O)C=CC4(C)C3C(O)CC21C CHEMBL2105540
 461 | CC(=O)NS(=O)(=O)c1cc(N)ccc1Sc1ccc(N)cc1 CHEMBL2110764
 462 | CC(CO)(CO)NCc1cc2c3ccccc3ccc2c2ccccc12 CHEMBL61495
 463 | CN1CCC23c4c5c(O)ccc4CC1C2CCC(=O)C3(C)O5 CHEMBL2110992
 464 | COc1cc(O)c(C(=O)Nc2nc(C(=O)NCCN(C(C)C)C(C)C)cs2)cc1OC CHEMBL2107723
 465 | Cc1ccccc1C(=O)N1CCC(=NOS(=O)(=O)O)c2ccc(Cl)cc21 CHEMBL2104373
 466 | Nc1nc(N)c2c(n1)nc(N)nc2-c1ccccc1 CHEMBL2107705
 467 | CC(CCc1ccc(O)cc1)NCC(O)c1ccc(O)cc1 CHEMBL2103767
 468 | Cc1cc(O)c(Cl)c(C)c1Cl CHEMBL2104302
 469 | COC1OC2OC3(CN4CCCCC4)C(O)CC(C13)C2C CHEMBL2107624
 470 | C=CC1CNCCC1CCCc1ccnc2ccc(OC)cc12 CHEMBL2104497
 471 | CC(S)C(=O)NCC(=O)O CHEMBL1314
 472 | CC1=C(C)C(=O)C(CCCCC#CCCCC#CCO)=C(C)C1=O CHEMBL304818
 473 | OCC(O)C(O)C(O)C(O)CO CHEMBL16105
 474 | CC1(C)NC(c2ccccc2)C(=O)N1C1C(=O)N2C1SC(C)(C)C2C(=O)O CHEMBL1201116
 475 | Cc1c(C)n(Cc2ccccc2)c2ccc(C(=O)OCCN(C)C)cc12 CHEMBL1518149
 476 | CC12OC(=O)C1(C(O)C1C=CCCC1)NC(=O)C2CCCl CHEMBL371405
 477 | CN(C)CCCC1(c2ccc(F)cc2)OCc2cc(C#N)ccc21 CHEMBL1508
 478 | CC#CCn1c(N2CCCC(N)C2)nc2c1c(=O)n(Cc1nc(C)c3ccccc3n1)c(=O)n2C CHEMBL237500
 479 | Cc1c(=S)ssc1-c1cnccn1 CHEMBL178459
 480 | c1ccc2c(c1)sc1ccccc12 CHEMBL219828
 481 | CC(=O)OC1CN2CCC1CC2 CHEMBL20835
 482 | COc1cc2c(cc1OC)C(c1ccccc1)CN(C)CC2 CHEMBL343569
 483 | C=CCC1(C(C)CCC)C(=O)NC(=S)NC1=O CHEMBL440
 484 | [O-][S+](Cc1ccccn1)c1nc2ccccc2[nH]1 CHEMBL9861
 485 | C[N+]1(CCCCC[N+]2(C)CCCC2)CCCC1 CHEMBL1271
 486 | CCN(CC)CCNC(=O)c1ccc(NC(C)=O)cc1 CHEMBL1097
 487 | CCCCC1CC(=O)C2(O)OC3C(NC)C(O)C(NC)C(O)C3OC2O1 CHEMBL1614655
 488 | COCCOC(=O)C1=C(C)NC(C)=C(C(=O)OC(C)C)C1c1cccc([N+](=O)[O-])c1 CHEMBL1428
 489 | CCc1nn(C2CCCC2)c2c1CCn1c(-c3cccs3)nnc1-2 CHEMBL217899
 490 | COc1ccc2c(=O)c(C)c(-c3ccccc3)oc2c1CN(C)C CHEMBL519364
 491 | CCCc1nn(C)c2c1nc(-c1cc(S(=O)(=O)N3CCN(C)CC3)ccc1OCC)[nH]c2=O CHEMBL192
 492 | CC[N+](C)(C)CCN(C)CC[N+](C)(C)CC CHEMBL1180418
 493 | CC(C)COCC(CN(Cc1ccccc1)c1ccccc1)N1CCCC1 CHEMBL1008
 494 | CCOP(=O)(OCC)SCC[N+](C)(C)C CHEMBL1201341
 495 | O=C(OC1CN2CCC1CC2)N1CCc2ccccc2C1c1ccccc1 CHEMBL1734
 496 | CNCCCC1c2ccccc2C=Cc2ccccc21 CHEMBL668
 497 | OCC1OC(O)C(O)C(O)C1O CHEMBL1233058
 498 | C=C(Br)CC1(C(C)CC)C(=O)NC(=O)NC1=O CHEMBL469253
 499 | OCCN1CCN(CCC=C2c3ccccc3Sc3ccc(C(F)(F)F)cc32)CC1 CHEMBL54661
 500 | Cc1cccc(OCC(O)CNC(C)C)c1 CHEMBL67096
 501 | CCn1c(=O)c2ccccc2n(-c2cccc([N+](=O)[O-])c2)c1=O CHEMBL88990
 502 | O=C1c2ccccc2C(=O)C1c1ccc(Br)cc1 CHEMBL288496
 503 | CC1(C)CCCC(NC(=O)C(S)Cc2ccccc2)C(=O)N1CC(=O)O CHEMBL107747
 504 | C=C(C)C1CC=C(C)CC1 CHEMBL449062
 505 | [Zn+2].O=S(=O)([O-])[O-] CHEMBL1200929
 506 | CCN(CC)CCOc1ccccc1OC(=Cc1ccccc1)C(C)=O CHEMBL164840
 507 | CC(C)NCC(O)c1ccc([N+](=O)[O-])cc1 CHEMBL127349
 508 | COc1cc([S+](C)[O-])ccc1-c1nc2ccc[nH]c-2n1 CHEMBL286020
 509 | Cc1cc(C)cc(NC(=O)Cc2ccc(OC(C)(C)C(=O)O)cc2)c1 CHEMBL18901
 510 | O=NN(CCCl)C(=O)NCCO CHEMBL284907
 511 | NC(C(=O)O)c1ccc(CO)c(O)c1 CHEMBL472562
 512 | CC(C)Nc1ncccn1 CHEMBL1740513
 513 | CC1(c2ccccc2)OC(C(=O)O)=CC1=O CHEMBL278488
 514 | CC(C)(C)NCC(O)c1cc(Cl)c(N)c(C(F)(F)F)c1 CHEMBL86749
 515 | FC(F)(F)COCC(F)(F)F CHEMBL477874
 516 | Oc1ccc(Nc2ccnc3cc(Cl)ccc32)cc1CN1CCCC1 CHEMBL1213257
 517 | O=C(C(O)CS(=O)(=O)c1ccc2cc(Cl)ccc2c1)N1CCC(N2CCCNC2=O)CC1 CHEMBL1095032
 518 | O=C(Nc1ccc([N+](=O)[O-])cc1Cl)c1cc(Cl)ccc1O CHEMBL1448
 519 | CCCn1c2nc[nH]c2c(=O)[nH]c1=O CHEMBL279898
 520 | CCN(CC)CCNC(=O)c1cc(Cl)c(NC(=O)COc2ccc(Cl)cc2)cc1OC CHEMBL10445
 521 | CC(CN1CCOCC1)C(C(=O)N1CCCC1)(c1ccccc1)c1ccccc1 CHEMBL431928
 522 | CC1OC(n2cc(F)c(=O)[nH]c2=O)C(O)C1O CHEMBL1130
 523 | CCCCC1(COC(=O)CCC(=O)O)C(=O)N(c2ccccc2)N(c2ccccc2)C1=O CHEMBL1414320
 524 | COc1c2ccoc2c(OC)c2oc(CSC)cc(=O)c12 CHEMBL297550
 525 | O=C(O)CCC(=O)c1ccc(C2CCCCC2)c(Cl)c1 CHEMBL1697824
 526 | CCCN1CCC(c2cccc(S(C)(=O)=O)c2)CC1 CHEMBL596802
 527 | Cc1cc(O)cc(C)c1Cl CHEMBL398440
 528 | CN(C)C(=O)CCCOC(=O)C(C)(C)Oc1ccc(Cl)cc1 CHEMBL1697831
 529 | CC1(C)CC1C(=O)NC(=CCCCCSCC(N)C(=O)O)C(=O)O CHEMBL766
 530 | CCOCCP(CCOCC)CCP(CCOCC)CCOCC CHEMBL1615784
 531 | COCCc1ccc(OCC(O)C(C)(C)N)cc1 CHEMBL1742421
 532 | CCCN1CCCC2Cc3n[nH]cc3CC21 CHEMBL240773
 533 | CNc1ccc(C=Cc2ccc(OCCOCCOCCF)nc2)cc1 CHEMBL1908919
 534 | CN1CCN(c2cc3c(nn2)Oc2ccccc2N3C)CC1 CHEMBL1886755
 535 | CCCCOC(=O)CC(CC(=O)OCCCC)(OC(C)=O)C(=O)OCCCC CHEMBL1904556
 536 | Cc1ccccc1N1CCN(CCc2nnc3n2CCCC3)CC1 CHEMBL1201216
 537 | CCc1nn(CCCN2CCN(c3cccc(Cl)c3)CC2)c(=O)n1CCOc1ccccc1 CHEMBL623
 538 | c1ccc2c(c1)Sc1ccccc1N2CC12CCN(CC1)CC2 CHEMBL1908311
 539 | C=NC(C(=O)NC1C(=O)N2C1SC(C)(C)C2C(=O)O)c1ccccc1 CHEMBL1908324
 540 | Oc1ccccc1-c1nnco1 CHEMBL1903897
 541 | CN(C)C1C(O)=C(C(N)=O)C(=O)C2(O)C(O)=C3C(=O)c4c(O)cccc4C(C)(O)C3CC12 CHEMBL1236180
 542 | Cc1cc(NC(=O)c2c(C)cccc2C)no1 CHEMBL1958077
 543 | Cc1c(Cl)c(=O)oc2cc(OP(=O)(OCCCl)OCCCl)ccc12 CHEMBL1897362
 544 | COc1ccc(F)cc1CC(O)(C1CCOCC1)C1CNCCO1 CHEMBL2103857
 545 | COc1ccc2c(c1)CC(C)N(CCc1ccc(N)cc1)CC2 CHEMBL2110599
 546 | OCCN1CCN(CCC=C2c3ccccc3COc3ccc(Cl)cc32)CC1 CHEMBL2110968
 547 | CC(C)(C)C(O)C=Cc1ccc2c(c1)OCO2 CHEMBL1983350
 548 | CC(C)CN(CC(C)C)CC(COC1c2[nH]cnc2N(C)C(=O)N1C)OC(=O)c1ccccc1 CHEMBL2106742
 549 | NC(=O)C(O)C(O)C(O)C(O)C=O CHEMBL2107404
 550 | CCOc1cc(OCC)cc(OCCN2CCOCC2)c1 CHEMBL2106361
 551 | O=C1CN=C(c2ccccc2F)c2cc(Cl)ccc2N1CC1CC1 CHEMBL2106743
 552 | CCOC(=O)C(CCc1ccccc1)NC(C)C(=O)N1C2CCC(CC2)C1C(=O)O CHEMBL2106476
 553 | O=C1NC(=O)C2=C(CCCC2)C1=Cc1ccccc1 CHEMBL2107135
 554 | CCCCCOc1ccccc1C(=CSC)n1ccnc1 CHEMBL2107447
 555 | CC(=O)OC(C)C(=O)C1(O)CCC2C3CCC4=CC(=O)C=CC4(C)C3(F)C(O)CC21C CHEMBL2107401
 556 | CN(C)CCC1(c2ccccc2)CCc2ccccc2C1=O CHEMBL2104267
 557 | C=CCN1CCC23c4c5c(OC(C)=O)ccc4CC1C2C=CC(OC(C)=O)C3O5 CHEMBL2106214
 558 | CC(C)=CCN1CCC2(C)c3cc(O)ccc3CC1C2(C)C CHEMBL2106302
 559 | CC(C)c1ccc(C(=O)N(C)CCN2CCN(C(=O)c3cccc4ccoc43)CC2)cc1 CHEMBL2104002
 560 | Cn1c2ncn(CCOC(O)C(Cl)(Cl)Cl)c2c(=O)n(C)c1=O CHEMBL2104491
 561 | CC(N)C(=O)c1ccccc1 CHEMBL2104047
 562 | CSCCC(NC(C)=O)C(=O)Oc1ccc(NC(C)=O)cc1 CHEMBL2107605
 563 | NN=c1ccc(C(N)=O)n[nH]1 CHEMBL2106246
 564 | CC(=O)OC1C=COC=C2CC34SSC5(CC6=COC=CC(O)C6N5C3=O)C(=O)N4C21 CHEMBL2104550
 565 | CCN(CC)CCOC(=O)C1N2C(=O)C(NC(=O)c3c(OC)cccc3OC)C2SC1(C)C CHEMBL2105448
 566 | CC1(c2ccccc2)CC(=O)N(CN2CCOCC2)C1=O CHEMBL2105127
 567 | CC1(C)OC(C)(C)C(=CNCCNC=C2C(=O)C(C)(C)OC2(C)C)C1=O CHEMBL2106748
 568 | [Ca+2].O=P([O-])([O-])OCC(O)CO CHEMBL2106124
 569 | [Na+].NC(CCC(=O)O)C(=O)[O-] CHEMBL2106738
 570 | [Na+].O=CC(O)C(O)C(O)C(O)C(=O)[O-] CHEMBL2104556
 571 | [K+].O=C([O-])c1ccccc1 CHEMBL2105241
 572 | [K+].O=C([O-])C(O)C(O)C(=O)O CHEMBL2105248
 573 | NC(CN(Cc1ccccc1)c1ccccc1)=NO CHEMBL2110778
 574 | Cc1c(CCOP(=O)(O)O)sc[n+]1Cc1cnc(C)nc1N CHEMBL1236378
 575 | CCCCCC(C)(O)C=CC1C(O)CC(=O)C1CC=CCCCC(=O)O CHEMBL2105959
 576 | CC(COc1ccccc1Cc1ccccc1)N1CCCCC1 CHEMBL2105910
 577 | COc1cc(C2c3ccc(N)c(N)c3OC(N)=C2C#N)cc(Br)c1OC CHEMBL2103852
 578 | O=C(NN1CCCCCC1)NS(=O)(=O)c1ccc(Cl)cc1 CHEMBL2106693
 579 | CC12CCC3C(CCC4CC5SC5CC43C)C1CCC2O CHEMBL2106161
 580 | CCOc1c(N2CCOCC2)cnn(C)c1=O CHEMBL2103954
 581 | Cc1cc(S(C)(=O)=O)c(S(C)(=O)=O)cc1C(=O)NC(=N)N CHEMBL2107802
 582 | CC(C)(Oc1ccc(C(O)c2ccc(Cl)cc2)cc1)C(=O)O CHEMBL2106581
 583 | CCCC(=O)c1ccccc1OCCN(C(C)C)C(C)C CHEMBL2107306
 584 | CC(C)(C)C(=O)NNCc1ccccc1 CHEMBL2106941
 585 | CCCC(CC)C1(CC)C(=O)NC(=O)NC1=O CHEMBL2107053
 586 | O=C(COc1ccc(Cl)cc1)OCCNC12CC3CC(CC(C3)C1)C2 CHEMBL2104053
 587 | CN(C)C1CC(c2ccccc2)c2ccccc21 CHEMBL1190753
 588 | c1cn(Cc2ccccc2)c(-c2nnn[nH]2)n1 CHEMBL2105919
 589 | CC1(O)CCC2C3CC4=CC(=O)CCC4(C)C3CCC21C CHEMBL2103992
 590 | OCC1(CO)COC(C(Cl)(Cl)Cl)OC1 CHEMBL2103943
 591 | COC(=O)Nc1nc2ccc(C3(c4ccc(F)cc4)OCCO3)cc2[nH]1 CHEMBL2104600
 592 | NC(Cc1cccc(N(CCCl)CCCl)c1)C(=O)O CHEMBL2107075
 593 | CCC(C)OC(=O)N1CCCCC1CCO CHEMBL2104314
 594 | COC(=O)c1ccccc1C(=O)c1ccc(OCCN2CCCCC2)cc1 CHEMBL2104821
 595 | Cc1c2ccc(NC(=O)N3CCOCC3)cc2oc(=O)c1CCN1CCOCC1 CHEMBL2105094
 596 | CCCCOCCOC(=O)c1cccnc1 CHEMBL2105161
 597 | CCCNC(=O)c1ccc2c(c1)N(C(C)CN1CCCC1)c1ccccc1S2 CHEMBL2104029
 598 | CCC1(CO)CCCN2CCc3c4ccccc4[nH]c3C21 CHEMBL2105559
 599 | CN1C2CCC1CC(NC(=O)c1cn(C3CCCCC3)c3ccccc3c1=O)C2 CHEMBL2110961
 600 | CN1CCC2=C(C1)C(c1ccccc1)c1ccccc12 CHEMBL278398
 601 | CC(CCc1ccc(O)cc1)NCC(O)c1ccc(O)cc1 CHEMBL509336
 602 | Cc1[nH]cnc1CSCCNC(=N)NCCCc1c[nH]cn1 CHEMBL12608
 603 | CC(C)NNCc1ccc2c(c1)OCO2 CHEMBL2111045
 604 | C[S+](C)CCOC(=O)C(c1ccccc1)C1CCCCC1 CHEMBL2111042
 605 | CC12CCC3C(C4CC4C4=CC(=O)CCC43C)C1CCC2(O)CCC(=O)O CHEMBL2111001
 606 | Cc1ccc(O)c(-n2nc3ccccc3n2)c1 CHEMBL1564747
 607 | O=C(O)COc1ccccc1C=NNC(=O)c1ccncc1 CHEMBL1590674
 608 | C#CCC1(OC(=O)CC)CCN(CCc2ccccc2)CC1 CHEMBL1742418
 609 | COc1ccc(CCNCC(O)COc2ccc(OCC(C)=O)c3c2CCC(=O)N3)cc1OC CHEMBL1742442
 610 | NC(Cc1c[nH]cn1)C(=O)O CHEMBL17962
 611 | CC(NC(CCc1ccccc1)C(=O)O)C(=O)N1Cc2ccccc2CC1C(=O)O CHEMBL1733
 612 | [K+].O=[N+]([O-])[O-] CHEMBL1644029
 613 | NC(CC(O)COc1cccc2ccccc21)=NO CHEMBL357513
 614 | CNC(=O)Oc1ccccc1OC(C)C CHEMBL446060
 615 | O=C1NCN(c2ccccc2)C12CCN(CCCOc1ccc(F)cc1)CC2 CHEMBL79834
 616 | CCCC(Nc1nc(-c2ccc(NC(=O)NCC)c(OC)c2)ncc1C)c1cccnc1 CHEMBL552212
 617 | CC(C(=O)O)c1ccc2c(c1)[nH]c1ccc(Cl)cc12 CHEMBL1316
 618 | C=C1C(CO)C(O)CC1n1cnc2c1nc(N)[nH]c2=O CHEMBL713
 619 | CC1CCC2C(C)C(N3CCS(=O)(=O)CC3)OC3OC4(C)CCC1C23OO4 CHEMBL516268
 620 | CN(C)CCC(N)(P(=O)(O)O)P(=O)(O)O CHEMBL122455
 621 | CCN(CC)CCOC(=O)C(O)(c1ccccc1)c1ccccc1 CHEMBL70352
 622 | OCCNCCO CHEMBL119604
 623 | OCC1CNCC(O)C1O CHEMBL206468
 624 | Cc1ccc(S(=O)(=O)NC(=O)NC2CCCCC2)cc1 CHEMBL312394
 625 | CCCOC(=O)c1ccc(O)cc1 CHEMBL194014
 626 | CC(CCC(=O)O)C1CCC2C3C(=O)CC4CC(=O)CCC4(C)C3CC(=O)C12C CHEMBL514446
 627 | O=P(O)(O)OCC1OC(O)(COP(=O)(O)O)C(O)C1O CHEMBL97893
 628 | O=C(O)CN(CCN(CC(=O)O)CC(=O)O)CCN(CC(=O)O)CC(=O)O CHEMBL780
 629 | Cn1c2ncn(CCOC(=O)C(C)(C)Oc3ccc(Cl)cc3)c2c(=O)n(C)c1=O CHEMBL1318939
 630 | NC(CS)C(=O)O CHEMBL863
 631 | Cc1ccccc1CNc1ncnc2c1ncn2C1OC(CO)C(O)C1O CHEMBL331382
 632 | O=C(O)C(Cc1cc(=O)[nH]c2ccccc12)NC(=O)c1ccc(Cl)cc1 CHEMBL1697771
 633 | Cc1nn(C)c2c1C(c1cccc(Cl)c1)=NCCN2 CHEMBL174697
 634 | Cc1nnc2n1-c1ccc(Cl)cc1C(c1ccccc1Cl)=NC2 CHEMBL646
 635 | CC1(C)c2cc(C3=NNC(=O)CC3)ccc2NC1=O CHEMBL38224
 636 | O=C1C[N+]([O-])=C(c2ccccc2)c2cc(Cl)ccc2N1 CHEMBL1597677
 637 | NCCc1ccc(O)c(O)c1 CHEMBL59
 638 | CC1(O)CCC2C3CC=C4CC(O)CCC4(C)C3CCC21C CHEMBL1079446
 639 | Cn1c2ncn(CC(=O)O)c2c(=O)n(C)c1=O CHEMBL70246
 640 | CN1C2CCC1CC(OC1c3ccccc3CCc3ccccc31)C2 CHEMBL1946186
 641 | CCCCCC(=O)OCC(=O)C1C(C)CC2C3CC(F)C4=CC(=O)C=CC4(C)C3C(O)CC21C CHEMBL2107415
 642 | FC(F)(Cl)Cl CHEMBL2106634
 643 | CCCCCC1Nc2cc(C(F)(F)F)c(S(N)(=O)=O)cc2S(=O)(=O)N1 CHEMBL2107203
 644 | CC(I)C1OCC(CO)O1 CHEMBL2105827
 645 | NC(=O)c1cc[n+](CC2=C(C(=O)[O-])N3C(=O)C(NC(=O)Cc4cccs4)C3SC2)cc1 CHEMBL2105567
 646 | O=P(O)(O)OC1C(O)C(O)C(O)C(OP(=O)(O)O)C1OP(=O)(O)O CHEMBL2106016
 647 | CN(C)CCN(Cc1cccs1)c1ccccc1 CHEMBL2111026
 648 | CCOCC1COc2c(Cl)c3c(cc2O1)[nH]cc(C(=O)OCC)c3=O CHEMBL2104710
 649 | COc1ccc2cc(C(C)CO)ccc2c1 CHEMBL2105135
 650 | O=c1nc2cccccc-2n1Cc1ccccc1 CHEMBL2104035
 651 | Cc1cc(C)[n+]([N-]C(=O)c2ccc(Cl)c(S(N)(=O)=O)c2)c(C)c1 CHEMBL2106604
 652 | Cc1c2c(cn1C)NC(=O)CN=C2c1ccccc1 CHEMBL2104741
 653 | CCC(CC)(C(=O)O)c1cccc2ccccc21 CHEMBL2106771
 654 | COc1cc2c(cc1OC)C(CCc1ccc(Cl)cc1)N(C)CC2 CHEMBL2106915
 655 | CN(C)CC1COC2(O1)c1ccccc1CCc1ccccc12 CHEMBL2104552
 656 | Oc1ccc(C2CNCc3c(O)c(O)ccc32)cc1O CHEMBL2105532
 657 | O=C(OCc1ccccc1)C1(CCN2CCCCCC2)CCCCC1=O CHEMBL2105937
 658 | CCC(CCCCC1CCC2CC(=O)CC12)OC CHEMBL2104105
 659 | COc1ccc2c(c1OC)C13CCN(C)C(C2)C1(O)CCC(O)C3 CHEMBL2104603
 660 | CCN(CC)CC(=O)Nc1c(C)cccc1C(=O)OC CHEMBL2105549
 661 | CCC(OC(N)=O)C1CCCCC1 CHEMBL2104652
 662 | CCc1oc2ccccc2c1C(=O)c1ccc(OCCN(CC)CC)cc1 CHEMBL2106228
 663 | CCc1nncn1C1CCCCC1 CHEMBL2105027
 664 | CCN1CCCC1CNS(=O)(=O)c1cc(Cl)c(N)cc1OC CHEMBL2105073
 665 | COC(=O)c1c2ccccc2n2c1C1CN(C)CCN1c1ccccc1C2 CHEMBL2110702
 666 | CN(C)CCOCCOC(=O)N1c2ccccc2Sc2ccccc21 CHEMBL2110862
 667 | CC1NCc2cc(-c3ccc4c(=O)c(C(=O)O)cn(C5CC5)c4c3OC(F)F)ccc21 CHEMBL215303
 668 | O=C(O)CSc1nnc(Br)n1-c1ccc(C2CC2)c2ccccc21 CHEMBL2105720
 669 | Clc1ccc([I+]c2ccc(Cl)cc2Cl)c(Cl)c1 CHEMBL2110834
 670 | CCN(CC)CCOC(=O)C1(c2ccc(C)c(C)c2)CCCC1 CHEMBL2110967
 671 | CC(=O)OC1(C(C)CN(C)C)CCCCC1c1ccccc1 CHEMBL2110963
 672 | CCCCCCCCCCCC[N+](C)(C)CC(=O)OCC CHEMBL2111046
 673 | Clc1ccc(OCC2=NCCc3ccccc32)cc1 CHEMBL2110933
 674 | O=C(O)CN1CCN(CC(=O)O)CCN(C(CO)C(O)CO)CCN(CC(=O)O)CC1 CHEMBL2111181
 675 | C#CCOCC1COC(Cn2ccnc2)(c2ccc(Cl)cc2Cl)O1 CHEMBL2110654
 676 | [Ca+2].[Br-].[Br-] CHEMBL2105852
 677 | [Mg+2].O=C([O-])C(O)C(O)C(O)C(O)CO.O=C([O-])C(O)C(O)C(O)C(O)CO CHEMBL2107145
 678 | Cn1cccc1C(=O)C(C#N)C(=O)Nc1ccccc1 CHEMBL2111033
 679 | [Mg+2].[Mg+2].[Mg+2].O=P([O-])([O-])[O-].O=P([O-])([O-])[O-] CHEMBL2106873
 680 | CC(=O)C1=C(O)C(N)C2Cc3c(C)c4ccc(C)c(O)c4c(O)c3C(=O)C2(O)C1=O CHEMBL2110884
 681 | N=C(N)c1ccc(C=C2c3ccccc3-c3ccccc32)cc1 CHEMBL2111004
 682 | CCN(CC)C(C)CC(=O)Nc1ccccc1 CHEMBL2104563
 683 | CC(=NCc1ccccc1)c1ccccc1O CHEMBL2105284
 684 | CC(Cc1ccccc1)NCCC#N CHEMBL2105566
 685 | CCN(CC)CC(C)(C)COC(=O)C(COP(=O)(O)O)c1ccccc1 CHEMBL2104488
 686 | CCOC(=O)c1nc2c3cc(C)ccc3n(CC)c(=O)n2n1 CHEMBL2105192
 687 | Cc1cc(Cl)cc(C(=NCCCC(N)=O)c2ccc(Cl)cc2)c1O CHEMBL2104937
 688 | COc1ccccc1N1CCN(CC(O)c2ccc(O)c(O)c2)CC1 CHEMBL2105227
 689 | CC(ON=C1c2ncncc2-c2cc(Br)cc(Br)c21)C(=O)NCCN(C)C CHEMBL2106169
 690 | CC(=O)Oc1ccc([N+](=O)[O-])c(OC(C)=O)c1C(=O)Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1 CHEMBL2104705
 691 | COc1ccccc1N1CCN(CCc2c(C)[nH]c3cc(OC)c(OC)cc32)CC1 CHEMBL2105252
 692 | COc1ccc(OC)c(C(O)C(C)NC(C)(C)C)c1 CHEMBL289093
 693 | Cn1ncc(Cl)c1-c1cc(C(=O)NC(CN)Cc2cccc(F)c2)sc1Cl CHEMBL2219422
 694 | O=C(c1ccco1)N(c1cnccn1)C1CCN(CCc2ccccc2)CC1 CHEMBL161084
 695 | COc1c(-c2ccc3cc(NS(C)(=O)=O)ccc3c2)cc(-n2ccc(=O)[nH]c2=O)cc1C(C)(C)C CHEMBL3137312
 696 | CCC1(c2ccccc2)OCC(C2CCCCN2)O1 CHEMBL305904
 697 | CN(C)CCC(O)(P(=O)(O)O)P(=O)(O)O CHEMBL55812
 698 | COc1cc2nccc(Oc3ccc(NC(=O)NC4CC4)c(Cl)c3)c2cc1C(N)=O CHEMBL1289601
 699 | NC(=O)Oc1ccc(Cc2ccccc2)cc1 CHEMBL608856
 700 | COCC1CN=C(c2ccccc2Cl)c2cc(Br)ccc2N1C CHEMBL1290783
 701 | CCCCOC(=O)c1ccc(O)cc1 CHEMBL459008
 702 | CCOC(=O)C(CCc1ccccc1)NC(C)C(=O)N1C(=O)N(C)CC1C(=O)O CHEMBL317094
 703 | O=C1c2ccccc2C(=O)C1c1ccc(F)cc1 CHEMBL24924
 704 | CCC(O)C(CC(C)N(C)C)(c1ccccc1)c1ccccc1 CHEMBL162243
 705 | CCOC(=O)Oc1ccc(CCNC(=O)C(CCSC)NC(C)=O)cc1OC(=O)OCC CHEMBL2106351
 706 | O=C(OCCOCCN1CCCCC1)N1c2ccccc2Sc2cccnc21 CHEMBL2104900
 707 | CC(Oc1c(Cl)cccc1Cl)C1=NCCN1 CHEMBL2107417
 708 | CCCC1(CC(=O)O)OCCc2c3ccccc3[nH]c21 CHEMBL1968386
 709 | CCN(CC)CCN1c2ccccc2Sc2ccccc21 CHEMBL1620412
 710 | C=C1CC(C)C2C3Cc4ccc(O)cc4C2(CCN3CC2CCC2)C1 CHEMBL2111060
 711 | CCOCCOC(=O)C=Cc1ccc(OC)cc1 CHEMBL2104045
 712 | COc1ccccc1OCC1CNC(=O)O1 CHEMBL2104790
 713 | Oc1cc2c(cc1O)C(COc1ccc(Cl)cc1)NCC2 CHEMBL2106010
 714 | CCN(CC)CCOCC(O)COc1ccccc1OC CHEMBL2107454
 715 | NC(=O)c1ccccc1OCC(=O)OCC1CCCO1 CHEMBL2104233
 716 | COc1cc(N)c(Cl)cc1C(=O)NC1CCNCC1OC CHEMBL2107465
 717 | COC1=CC(=O)OC1C(O)c1ccccc1Cl CHEMBL2106442
 718 | CCCC(=O)OC1(C(=O)COC(C)=O)CCC2C3CC(C)C4=CC(=O)CCC4(C)C3C(O)CC21C CHEMBL2104661
 719 | CC(C)C(=O)OC(OC(=O)NCC(CC(=O)O)c1ccc(Cl)cc1)C(C)C CHEMBL2107312
 720 | CCc1c(C(=O)C(N)=O)c2c(cccc2OCC(=O)OC)n1Cc1ccccc1 CHEMBL2105659
 721 | CN(C)CCOC(=O)c1ccc(Cl)c(N)c1 CHEMBL2106019
 722 | Cc1nc2cc(C(c3ccccc3)n3ccnc3)ccc2[nH]1 CHEMBL2105112
 723 | CCOC(=O)OC(C)OC(=O)C1N2C(=O)C(N=CN3CCCCCC3)C2SC1(C)C CHEMBL2106658
 724 | NC(=O)c1ccc(Cl)c(S(N)(=O)=O)c1 CHEMBL2107090
 725 | CNCC1CCc2sc(C)nc2C1 CHEMBL2104686
 726 | O=C1OC2C(O)C(O)OC2C1O CHEMBL2107425
 727 | CC(S)C(=O)NCC(=O)O CHEMBL2106444
 728 | COc1ccc(C(O)CN2CCN(C(c3ccccc3)c3ccccc3)CC2)cc1OC CHEMBL2074664
 729 | N=C(N)c1ccc(C=Cc2ccc(C(=N)N)cc2)cc1 CHEMBL142304
 730 | CN(C)CCC=C1c2ccccc2C(C)(C)c2ccccc21 CHEMBL110094
 731 | O=C1c2ccccc2S(=O)(=O)N1CCCCN1CCN(c2ncccn2)CC1 CHEMBL8412
 732 | OC(CNc1ncccn1)c1ccccc1 CHEMBL2110896
 733 | O=c1[nH]c2ccccc2c(=O)n1CCCN1CCN(c2cccc(Cl)c2)CC1 CHEMBL2110792
 734 | CN(C)CCC=C1c2cccn2CCc2ccc(Cl)cc21 CHEMBL2110942
 735 | OCCCN1CCN(CCCC2c3ccccc3Sc3ccc(Cl)cc32)CC1 CHEMBL2110631
 736 | CC1(C)SC2C(NC(=O)CSc3ccccc3)C(=O)N2C1C(=O)O CHEMBL2111130
 737 | CCCc1c2oc(C(=O)O)cc(=O)c2cc2c(=O)cc(C(=O)O)oc21 CHEMBL2110970
 738 | CC(C)NC1C2CCC(CC2)C1(O)c1ccc(Cl)c(Cl)c1 CHEMBL2110879
 739 | CC(=O)C=C(C)c1ccc(-c2ccccc2)cc1 CHEMBL2104473
 740 | N=C(N)NC(=O)c1ccc(N2CCN(C(=O)c3ccc[nH]3)CC2)c(C(F)(F)F)c1 CHEMBL2105423
 741 | CC(=C(CCO)SSCC1CCCO1)N(C=O)Cc1cnc(C)nc1N CHEMBL1740659
 742 | C=CCNc1nc(C(=O)NN=CC=Cc2ccc([N+](=O)[O-])o2)cs1 CHEMBL2105145
 743 | CCN(CC)CCN1C(=O)c2ccccc2C1c1ccccc1 CHEMBL2104536
 744 | CC(C)OC(=O)OC1CCCCC1 CHEMBL2104038
 745 | CC(C)(C)NCC(O)COCC1COc2ccccc2O1 CHEMBL2106691
 746 | COC(=O)C1(c2ccccc2)CCCN(C)C(C)C1 CHEMBL2104520
 747 | CC(=O)NC(C(O)CC(=O)C(=O)O)C(O)C(O)C(O)CO CHEMBL2105945
 748 | CC[N+](C)(C)CCOC(=O)C(O)(c1ccccc1)c1ccccc1 CHEMBL2110848
 749 | [Ca+2].O=P[O-].O=P[O-] CHEMBL2218895
 750 | CSC[S+]([O-])CC(CO)NC(=O)C=Cc1c(C)nc(O)nc1O CHEMBL2303630
 751 | Cc1cnc(NC(=O)Nc2cc(Br)c(C)cc2OCC2CNCCO2)cn1 CHEMBL3039517
 752 | Cc1nc2ccccc2n1Cc1ccc(Cl)cc1 CHEMBL152649
 753 | O=c1n(Cl)c(=O)n(Cl)c(=O)n1Cl CHEMBL1698868
 754 | OCCOCCOCCN1CCN(C(c2ccccc2)c2ccc(Cl)cc2)CC1 CHEMBL2104263
 755 | CCN(CC)CCOC(=O)N1CCC(Cc2ccccc2)CC1 CHEMBL2105607
 756 | CCC(C)(C)NCC(O)COc1cc(CCC(=O)c2ccc(C)cc2)ccc1OC CHEMBL2104075
 757 | CCCCCCNC(=N)NC(=N)N CHEMBL2106939
 758 | O=C(N1CCCC1)C(CCN1CCOCC1)(c1ccccc1)c1ccccc1 CHEMBL2106152
 759 | [Ca+2].[Ca+2].[Ca+2].O=C([O-])CC(O)(CC(=O)[O-])C(=O)[O-].O=C([O-])CC(O)(CC(=O)[O-])C(=O)[O-] CHEMBL2106123
 760 | C[N+](C)(C)CCOC(=O)C(O)(c1ccccc1)C1CC2C=CC1C2 CHEMBL2110818
 761 | Cc1ccc(C(C)OC(=O)C2(C)CCC(C(=O)O)C2(C)C)cc1 CHEMBL2110648
 762 | O=C(Nc1ccc(Cl)c(S(=O)(=O)N2CCNCC2)c1O)Nc1cccc(F)c1Cl CHEMBL2178579
 763 | CCC(=O)N(c1ccc(Cl)c(Cl)c1)C1CCCC1N(C)C CHEMBL20679
 764 | Cl.CCCCNc1ccc(C(=O)OCCN(CC)CC)cc1 CHEMBL593548
 765 | CCN(CC)CCOC(=O)CC(O)(c1ccccc1)c1ccccc1 CHEMBL2107672
 766 | COC1C(O)C(N)C(OC2OC(C(C)N)CCC2N)C(O)C1N(C)C(=O)CN CHEMBL3084803
 767 | Oc1cc(O)c(Cl)cn1 CHEMBL1730601
 768 | [Na+].O=C([O-])CCC(=O)O CHEMBL1200345
 769 | Cc1ccc2c(-c3ccccc3)nc(=O)n(C(C)C)c2c1 CHEMBL268501
 770 | CC12CCC3C(CCC4=CC(=O)CCC43C)C1CCC2=O CHEMBL274826
 771 | CCC(c1ccc(O)cc1)C(CC)c1ccc(O)cc1 CHEMBL9225
 772 | CCOC(=O)C(C)(C)Oc1ccc(Cl)cc1 CHEMBL565
 773 | CC(O)C1C(=O)N2C(C(=O)O)=C(C3CCCO3)SC12 CHEMBL556262
 774 | Nc1c2c(nc3c1CCCC3)CCC2 CHEMBL130880
 775 | CC1(c2nc3cccc(C(N)=O)c3[nH]2)CCCN1 CHEMBL506871
 776 | O=C(O)C=CC(=O)O CHEMBL503160
 777 | O=C1NC(CCCl)Oc2ccccc21 CHEMBL124815
 778 | O=c1[nH]cnc2c(CN3CC(O)C(CO)C3)c[nH]c21 CHEMBL269864
 779 | O=[N+]([O-])c1cn2c(n1)OCC(OCc1ccc(OC(F)(F)F)cc1)C2 CHEMBL227875
 780 | CCCCC(CC)CNC(=O)CC(C)O CHEMBL452859
 781 | Cc1nnc(SCC2=C(C(=O)O)N3C(=O)C(NC(=O)Cn4cnnn4)C3SC2)s1 CHEMBL1435
 782 | Cc1cc(NC(=O)C(=O)c2cc(Cc3ccc(C#N)cc3)n3ccccc23)sn1 CHEMBL271068
 783 | CC(O)(CC(=O)O)CC(=O)O CHEMBL50444
 784 | COc1ccccc1O CHEMBL13766
 785 | c1ccc(Cn2c3ccccc3nc2N2CCNCC2)cc1 CHEMBL56900
 786 | COc1cc(OC)c(Cl)c2c1C(=O)C1(O2)C(OC)=CC(=O)CC1C CHEMBL562
 787 | CCN(CC)CCCC(C)Nc1cc(OC)cc2cccnc21 CHEMBL472698
 788 | CC(CCC(=O)O)C1CCC2C3C(O)CC4CC(O)CCC4(C)C3CCC12C CHEMBL1551
 789 | Cc1cc(NS(=O)(=O)c2ccc(N)cc2)nc(C)n1 CHEMBL485696
 790 | Cn1c2ncn(CCO)c2c(=O)n(C)c1=O CHEMBL699
 791 | CC(C)NCC(O)COc1ccccc1-n1cccc1 CHEMBL27077
 792 | CCCCCCCCC=CCCCCCCC(N)(CO)C(=O)O CHEMBL1200394
 793 | O=[N+]([O-])OC1COC2C(O)COC12 CHEMBL1311
 794 | CCOC(=O)c1c(C)cc2c(CO)nnc(O)c2c1C CHEMBL153427
 795 | O=C(C=Cc1cccc(F)c1)NC1CC1 CHEMBL132663
 796 | CC(Cc1cccc(C(F)(F)F)c1)NCCOC(=O)c1ccccc1 CHEMBL400599
 797 | Cc1cc(C)cc(C(=O)NCc2ccncc2)c1 CHEMBL1581974
 798 | Nc1ccc(C(=O)Nc2ccccc2N)cc1 CHEMBL1351761
 799 | CCC(O)c1ccccc1 CHEMBL1397202
 800 | CCn1cc(C(=O)O)c(=O)c2cnc(N3CCCC3)nc21 CHEMBL311350
 801 | O=C(O)C1CSC(c2ccccc2O)N1C(=O)CCS CHEMBL309962
 802 | [N-]=[N+]=CC(=O)OCC(N)C(=O)O CHEMBL1095699
 803 | C=CC1(C)CC(=O)C2(O)C(C)(O1)C(OC(C)=O)C(O)C1C(C)(C)CCC(O)C12C CHEMBL52606
 804 | CC(=O)NN=Cc1ccc([N+](=O)[O-])o1 CHEMBL1565322
 805 | O=[As]O[As]=O CHEMBL1200978
 806 | CC(C)N(CCC(CCN1CCCCC1)(C(N)=O)c1ccccc1Cl)C(C)C CHEMBL276177
 807 | [Cl-].C[N+](C)(C)CCO CHEMBL282468
 808 | COP(=O)(OC)C(O)C(Cl)(Cl)Cl CHEMBL167150
 809 | CN(C)CCCC1(c2ccc(F)cc2)OCc2cc(C#N)ccc21 CHEMBL549
 810 | C=CCC1(C(C)C)C(=O)NC(=O)NC1=O CHEMBL7863
 811 | O=c1n(CC2CO2)c(=O)n(CC2CO2)c(=O)n1CC1CO1 CHEMBL453863
 812 | CS(=O)(=O)OCCCNCCCOS(C)(=O)=O CHEMBL96292
 813 | OCCN1CCN(CCC=C2c3ccccc3Sc3ccc(Cl)cc32)CC1 CHEMBL87385
 814 | CCC(C)C(C)(COC(N)=O)COC(N)=O CHEMBL1200922
 815 | CC1CC(=O)NN=C1c1ccc2c(c1)OCC(=O)N2 CHEMBL46765
 816 | C#CC1(O)C=CC2C3CCC4=CC(=O)CCC4C3CCC21CC CHEMBL1213583
 817 | Oc1cc(O)c2c(c1)OC(c1ccc(O)c(O)c1)C(O)C2O CHEMBL123809
 818 | COc1ccc(C2(C#N)CCC(C(=O)O)CC2)cc1OC1CCCC1 CHEMBL511115
 819 | CN1CCC(=C2c3ccccc3C(O)c3ccccc32)CC1 CHEMBL440557
 820 | NCCc1c[nH]cn1 CHEMBL90
 821 | C#CC1(O)CCC2C3CCc4cc(O)ccc4C3C(OC)CC21C CHEMBL1628161
 822 | CCCOC(C(=O)OC1CCN(C)CC1)(c1ccccc1)c1ccccc1 CHEMBL1078261
 823 | O=C(CCCN1CC=C(n2c(=O)[nH]c3ccccc32)CC1)c1ccc(F)cc1 CHEMBL1108
 824 | COc1cc(Cc2cnc(N)nc2N)cc(OC)c1N CHEMBL122351
 825 | [Na+].O=C1OC(C(O)CO)C([O-])=C1O CHEMBL591665
 826 | Cc1cc2nc3c(=O)[nH]c(=O)nc-3n(CC(O)C(O)C(O)COP(=O)(O)O)c2cc1C CHEMBL1201794
 827 | Nc1ncnc2c1ncn2C1OC(CO)C(O)C1O CHEMBL1090
 828 | COCC(NC(C)=O)C(=O)NCc1ccccc1 CHEMBL58323
 829 | CCN(CC)C(=S)S CHEMBL961
 830 | CC(C)(C)C1(O)CCN2CC3c4ccccc4CCc4cccc(c43)C2C1 CHEMBL8514
 831 | CCC1(c2ccc(N)cc2)CCC(=O)NC1=O CHEMBL488
 832 | [Na+].O=C([O-])C(Cl)Cl CHEMBL306823
 833 | CCOC(=O)COc1ccc2c(c1)CC(NCC(O)c1cccc(Cl)c1)CC2 CHEMBL1193948
 834 | CCOC(=O)C(CCc1ccccc1)NC(C)C(=O)N1CC2(CC1C(=O)O)SCCS2 CHEMBL431
 835 | C[N+]1(C)CCN(CC(O)(c2ccccc2)C2CCCCC2)CC1 CHEMBL1201325
 836 | COC(=O)C1=CCCN(C)C1 CHEMBL7303
 837 | CCCN1CC(CSC)CC2c3cccc4[nH]cc(c43)CC21 CHEMBL531
 838 | CN(C)CCCN1c2ccccc2Sc2ccccc21 CHEMBL564
 839 | CN(CCCl)CCCl CHEMBL427
 840 | NC(=O)C(c1ccccc1)(c1ccccc1)C1CCN(CCc2ccc3c(c2)CCO3)C1 CHEMBL1346
 841 | C#CCOc1ccc2c(C)cc(=O)oc2c1 CHEMBL1377940
 842 | O=[N+]([O-])c1ccc(Nc2ccc(N=C=S)cc2)cc1 CHEMBL93385
 843 | O=C(C(c1ccccc1)c1ccccc1)N1CCN(CC(O)COc2cccc3ncccc32)CC1 CHEMBL65067
 844 | O=C(C[S+]([O-])C(c1ccccc1)c1ccccc1)NO CHEMBL93077
 845 | COCN1c2ccc([N+](=O)[O-])cc2C(c2ccccc2)=NCC1=O CHEMBL146817
 846 | CN(C(=O)c1c(O)c2ccccc2n(C)c1=O)c1ccccc1 CHEMBL11672
 847 | COC(S)=NCCn1c(C)ncc1[N+](=O)[O-] CHEMBL135000
 848 | CCC1(CC)C(=O)NCC(C)C1=O CHEMBL1200790
 849 | NCCCCCC(O)(P(=O)(O)O)P(=O)(O)O CHEMBL55214
 850 | COc1ccc2c(c1)CN(C)CC2c1ccc(Cl)c(Cl)c1 CHEMBL287257
 851 | O=S(=O)(c1nc(-c2ccc(F)cc2)c(-c2ccc(F)cc2)[nH]1)C(F)(F)C(F)F CHEMBL18647
 852 | CC(C)NCC(O)c1ccc2ccccc2c1 CHEMBL16476
 853 | CC(=O)c1ccc2c(c1)N(CCCN1CCC(CCO)CC1)c1ccccc1S2 CHEMBL1584
 854 | O=C1CN(N=Cc2ccc(-c3ccc([N+](=O)[O-])cc3)o2)C(=O)N1 CHEMBL1201288
 855 | CCOC(=O)C1(c2ccccc2)CCN(CCc2ccccc2)CC1 CHEMBL285517
 856 | O=C(O)CCNC(=O)c1ccccc1 CHEMBL1231530
 857 | Oc1ccc(OCc2ccccc2)cc1 CHEMBL1388
 858 | Cn1c(COC(N)=O)ncc1[N+](=O)[O-] CHEMBL290299
 859 | O=C1CSC2(CCN(CCCN3c4ccccc4Sc4ccc(Cl)cc43)CC2)N1 CHEMBL1483796
 860 | FC(F)(F)C(F)(F)C(F)(F)F CHEMBL1663
 861 | COc1ccc(-c2noc(CC(=O)O)c2-c2ccc(OC)cc2)cc1 CHEMBL259972
 862 | NCCCC(=O)O CHEMBL96
 863 | CCNC1(c2ccccc2)CCCCC1 CHEMBL279924
 864 | CCC(C(=O)O)C1(O)CCCCC1 CHEMBL1697739
 865 | CC(C)OP(=O)(F)OC(C)C CHEMBL1025
 866 | CC(N)C(O)c1ccccc1 CHEMBL61006
 867 | Cc1cc(=O)oc2cc(O)ccc12 CHEMBL12208
 868 | CC(C)n1c2ccccc2n2cnc(-c3noc(C4CC4)n3)c2c1=O CHEMBL279867
 869 | Cc1ncc([N+](=O)[O-])n1CC(C)O CHEMBL498847
 870 | O=C(O)CNC(=O)CNC(=O)CNC(=O)CS CHEMBL1615778
 871 | CCN(CC)CCNC(=O)c1ccc(N)c(Cl)c1 CHEMBL1618378
 872 | CCCOc1cc(N)ccc1C(=O)OCCN(CC)CC CHEMBL1195
 873 | CC(C)NCCCC1(C(N)=O)c2ccccc2-c2ccccc21 CHEMBL1201242
 874 | Cc1cc(S(=O)(=O)O)c2c(C)ccc(C(C)C)cc1-2 CHEMBL1852533
 875 | CN(C)C1CCc2[nH]c3c(cc(F)cc3F)c2C1 CHEMBL1882682
 876 | COC1OC2OC3(C)CCC4C(C)CCC(C1C)C42OO3 CHEMBL566534
 877 | CC(C)C(=O)Nc1cccc(C2CN3CCSC3=N2)c1 CHEMBL2110807
 878 | CNC1(C)C2CCC(C2)C1(C)C CHEMBL2103881
 879 | CC1CN(N=Cc2ccc([N+](=O)[O-])o2)C(=O)O1 CHEMBL2107517
 880 | OC(C1=CC(=C(c2ccccn2)c2ccccn2)C=C1)(c1ccccn1)c1ccccn1 CHEMBL2105304
 881 | COC(=O)C(C)c1cccc(C(c2ccccc2)n2ccnc2)c1 CHEMBL2107439
 882 | [O-][N+]1=C(c2ccccc2)c2cc(Cl)ccc2N=C(NCC2CC2)C1 CHEMBL2104165
 883 | Cc1ccccc1OCC(O)CN1CC=CCC1 CHEMBL2107693
 884 | O=C(Nc1ccc(CC2CCC(C(O)c3ccccc3)N2)cc1)C1CCc2nccc(=O)n21 CHEMBL2107826
 885 | O=C1c2ccccc2C(=O)C1c1ccc(C(F)(F)F)cc1 CHEMBL2105129
 886 | CCC(C)(CC)OC(N)=O CHEMBL2104208
 887 | COc1ccccc1OCCNCC(O)COc1cccc2[nH]nnc21 CHEMBL2104914
 888 | C[N+](C)(CCO)CC(=O)[O-] CHEMBL2105274
 889 | CC(C)(O)CC(C)(O)c1ccc(Cl)cc1 CHEMBL2106273
 890 | CN(C)C(=O)COC1c2ccccc2CCc2ccccc21 CHEMBL2104766
 891 | CN(C)C(=O)NC1CCC(CCN2CCN(c3cccc(Cl)c3Cl)CC2)CC1 CHEMBL2028019
 892 | OCc1cccc(Cc2c[nH]cn2)c1O CHEMBL2104355
 893 | c1cc(CNCc2ccncc2)ccn1 CHEMBL2103958
 894 | C[N+]1(C)CCC(OC(=O)C(O)(c2cccs2)c2ccccc2)C1 CHEMBL2110853
 895 | CC[N+]1(CC)CCC(OC(=O)C(O)(c2ccccc2)c2ccccc2)C1 CHEMBL2110788
 896 | c1ccc2c(c1)CCN1CCNCC21 CHEMBL2104690
 897 | CC(CC#N)N(C)CC(=O)N(C)c1ccc(Cl)cc1C(=O)c1ccccc1F CHEMBL2104077
 898 | O=C(O)CCCNC(=O)c1ccc(Cl)cc1O CHEMBL2107776
 899 | O=C(O)CC1(CO)CCCCC1 CHEMBL2110826
 900 | CN(C(=O)CNC1CC1)c1ccc(Cl)cc1C(=O)c1ccccc1Cl CHEMBL2104597
 901 | COC(=O)CCC=C=CCC1C(O)CC(O)C1C=CC(O)COc1ccccc1 CHEMBL2104232
 902 | O=c1cc(CN2CCOCC2)c2cc(O)c(O)cc2o1 CHEMBL2104742
 903 | CC(C)C(OC(=O)c1cccnc1)c1ccc(Cl)cc1 CHEMBL2107111
 904 | CCCCN(C(=O)C(C)C)c1nc(C)co1 CHEMBL2105068
 905 | CCc1cc(S(=O)(=O)O)c2cc(C(C)C)cccc1-2 CHEMBL2105570
 906 | COc1cc2c(cc1OC)S(=O)(=O)OC(C(=O)NC(C)CC(C)(C)N(C)C)C2 CHEMBL2105495
 907 | O=C1COC(c2ccc(C(F)(F)F)cc2)CN1 CHEMBL2105520
 908 | COC(=O)c1cnc2cc(OC(C)C)c(OC(C)C)cc2c1O CHEMBL2105380
 909 | Nc1ncc(S(=O)(=O)c2ccc(N)cc2)s1 CHEMBL2107139
 910 | COc1ccc2c3c1OC1C(OC(=O)c4cccnc4)CCC4C(C2)N(C)CCC314 CHEMBL2104623
 911 | NC(=O)c1ccc(Oc2ccc(CNCCC3CCOCC3)cc2F)nc1 CHEMBL2103878
 912 | OCC(O)C(O)C(O)C(O)COC1OC(CO)C(O)C(O)C1O CHEMBL2104398
 913 | CCCCOCC(O)COc1ccccc1 CHEMBL2104223
 914 | CN(C)CCN(C)n1cc(-c2ccccc2)c2ccccc21 CHEMBL2104611
 915 | CCCCC(C)C(O)C=CC1C(O)CC2OC(=C(C#N)CCCC(=O)O)CC21 CHEMBL2104724
 916 | Cn1c2ncn(CCCNC3COC4C(O[N+](=O)[O-])COC34)c2c(=O)n(C)c1=O CHEMBL2107483
 917 | CCOC(=O)C1(c2ccccc2)CCC=CC1N(C)C CHEMBL2104560
 918 | CCNC1=Nc2ccc(Cl)cc2C(C)(c2ccccc2)O1 CHEMBL2106227
 919 | COc1c2c(cc3c1CN(C)CC3)OCO2 CHEMBL1606295
 920 | CCN(CC)CCOC1(c2ccccc2)CCN(CCNc2ccccc2)CC1 CHEMBL2110911
 921 | CCn1cc(C(=O)O)c(=O)c2cc3c(cc21)CCO3 CHEMBL2110851
 922 | CCC1CC(=O)C2Oc3c4c(ccc3OC)CC3C1C42CCN3CC1CC1 CHEMBL2110790
 923 | NC(=O)OCC1C(NC(=O)C(=NOCC(=O)O)c2csc(N)n2)C(=O)N1S(=O)(=O)O CHEMBL1614658
 924 | CN(C)c1cnccn1 CHEMBL2110770
 925 | CN=C(NC)NCc1ccc(OC)cc1 CHEMBL2110972
 926 | COC(=O)C1CC2=CC(=O)CCC2(C)C2CCC3(C)C(CCC3(O)CCC(=O)O)C12 CHEMBL2110977
 927 | CCCCN(CCCC)C(=O)OCC[N+](C)(C)CC CHEMBL2110746
 928 | CNC(=O)CCN1CCN(CCC=C2c3ccccc3Sc3ccc(Cl)cc32)CC1 CHEMBL2110894
 929 | CC[N+](C)(C)CCOC(=O)CCC(=O)OCC[N+](C)(C)CC CHEMBL2111153
 930 | NCc1ccccc1Sc1ccccc1CO CHEMBL310160
 931 | C[N+]1(C)CCC(OC(=O)C(O)(c2ccccc2)c2ccccc2)CC1 CHEMBL2110714
 932 | NC1CCCC1c1ccccc1 CHEMBL2110918
 933 | N.O=C(O)c1ccccc1 CHEMBL2105970
 934 | S=C=Nc1ccc(N=C=S)cc1 CHEMBL2104676
 935 | COC(=O)Nc1cc(N2CC=CCC2)nc2nc(=O)on21 CHEMBL2104058
 936 | CC1C[S+]([O-])C(C)(C)C(C(=O)O)N1 CHEMBL2105470
 937 | c1csc(Cc2ccccc2OCC2CNCCO2)c1 CHEMBL2105438
 938 | O=C1CCCC(=O)C1C(=S)Nc1ccc(Cl)cc1 CHEMBL2105264
 939 | N#CCNC(=O)c1ccc(-c2ccnc(Nc3ccc(N4CCOCC4)cc3)n2)cc1 CHEMBL1078178
 940 | CCOP(=S)(OCC)Oc1cc(C)nc(C(C)C)n1 CHEMBL388560
 941 | OC(O)C(Cl)(Cl)Cl CHEMBL455917
 942 | O=C1c2ccccc2S(=O)(=O)N1C1CCCNC1=O CHEMBL72115
 943 | O=C(O)c1ccccc1Nc1cccc(Cl)c1Cl CHEMBL23115
 944 | Nc1ccc(OCCCCCN2C(=O)c3ccccc3C2=O)cc1 CHEMBL94192
 945 | CC(C)C1CCC(C)CC1O CHEMBL256087
 946 | CC(=O)Nc1ccc(OC(=O)c2ccccc2O)cc1 CHEMBL92590
 947 | N=C(N)NN=Cc1c(Cl)cccc1Cl CHEMBL420
 948 | O=[N+]([O-])OCC(CO)(CO[N+](=O)[O-])CO[N+](=O)[O-] CHEMBL466660
 949 | CN(C)CC1CCn2cc(c3ccccc32)C2=C(c3cn(c4ccccc34)CCO1)C(=O)NC2=O CHEMBL91829
 950 | C#CC1(OC(N)=O)CCCCC1 CHEMBL1576
 951 | BrC(Br)Br CHEMBL345248
 952 | Cc1cc2cc3c(C)cc(=O)oc3c(C)c2o1 CHEMBL1475
 953 | N#Cc1cc(-c2ccccc2)nnc1NCCN1CCOCC1 CHEMBL150365
 954 | CC(N)C(O)c1ccc(O)c(O)c1 CHEMBL677
 955 | COc1cc2c(cc1OC)C1CC(=O)C(CC(C)C)CN1CC2 CHEMBL117785
 956 | CCOC(=O)C1=C(C)NC(C)=C(C(=O)OC)C1c1cccc(Cl)c1Cl CHEMBL1480
 957 | CCC1(C)CC(=O)NC1=O CHEMBL696
 958 | C=C1CC2C3C=C(C)C4=CC(=O)CCC4(C)C3CCC2(C)C1(OC(C)=O)C(C)=O CHEMBL1328968
 959 | c1ccc(Cc2nc3ccccc3[nH]2)cc1 CHEMBL355063
 960 | CCCCCCCCC=CCCCCCCCC(=O)OCC(O)CO CHEMBL428593
 961 | CCOC(=O)C(CCc1ccccc1)NC1CCCN2CCCC(C(=O)O)N2C1=O CHEMBL515606
 962 | CCC1(c2c[nH]cn2)Cc2ccc(F)cc2C1 CHEMBL1255582
 963 | CC(=O)NS(=O)(=O)c1ccc(N)cc1 CHEMBL455
 964 | Nc1c(CC(=O)O)cccc1C(=O)c1ccc(Br)cc1 CHEMBL1077
 965 | CCS(=O)(=O)c1ccc(F)cc1 CHEMBL93309
 966 | Cc1cc(CC(=O)O)n(C)c1C(=O)c1ccc(Cl)cc1 CHEMBL19490
 967 | CCCCCc1ccc(C)cc1O CHEMBL1512677
 968 | CC1(C)SC2C(Br)C(=O)N2C1C(=O)O CHEMBL73622
 969 | CCn1cc(C(=O)O)c(=O)c2ccc(Cc3ccccc3)nc21 CHEMBL35337
 970 | CCN(CC)CCOC(=O)C(c1ccccc1)c1ccccc1 CHEMBL353846
 971 | CNC1CCCN(c2c(F)cc3c(=O)c(C(=O)O)cn(C4CC4)c3c2OC)C1 CHEMBL1210954
 972 | CC(C)CNC1CCS(=O)(=O)c2sc(S(N)(=O)=O)cc21 CHEMBL417975
 973 | CNC1=Nc2ccc(Cl)cc2C(c2ccccc2)=[N+]([O-])C1 CHEMBL451
 974 | NC12CC3CC(CC(C3)C1)C2 CHEMBL660
 975 | CN1CCCN=C1COC(=O)C(O)(c1ccccc1)C1CCCCC1 CHEMBL1495
 976 | Nc1c2ccccc2nc2c1CCCC2 CHEMBL95
 977 | O=C(O)COCCN1CCN(C(c2ccccc2)c2ccc(Cl)cc2)CC1 CHEMBL1201191
 978 | O=CCCCC=O CHEMBL1235482
 979 | O=C1C(O)N=C(c2ccccc2F)c2cc(Cl)ccc2N1CCO CHEMBL64677
 980 | CC12CC(O)C3C(CC(F)C4=CC(=O)C=CC43C)C1CCC2(O)C(=O)CO CHEMBL1200774
 981 | O=C(O)Cc1nn(Cc2nc3cc(C(F)(F)F)ccc3s2)c(=O)c2ccccc12 CHEMBL10372
 982 | Cc1cc(Cl)ccc1N=C1SCS1 CHEMBL93885
 983 | CN1c2c(=O)nc(N)[nH]c2NCC1CNc1ccc(C(=O)NC(CCC(=O)O)C(=O)O)cc1 CHEMBL1231574
 984 | CNC(=N)NC(=O)Nc1c(C)cccc1C CHEMBL448416
 985 | CCCCC(C)(O)CC=CC1C(O)CC(=O)C1CCC=CCCC(=O)OC CHEMBL266979
 986 | Cc1cccc(C(C)c2c[nH]cn2)c1C CHEMBL778
 987 | COc1ccc(Cc2cnc(N)nc2N)cc1OC CHEMBL19633
 988 | Oc1ccc(Cl)cc1 CHEMBL57053
 989 | NCCCCC(NC1CCc2ccccc2N(CC(=O)O)C1=O)C(=O)O CHEMBL430554
 990 | CCOC(=O)c1ccc(OC(=O)CCCCCN=C(N)N)cc1 CHEMBL87563
 991 | COc1ccc(C=Cc2cc(OC)c(OC)c(OC)c2)cc1OP(=O)(O)O CHEMBL1206232
 992 | CN1CCC(=C2c3ccsc3CCc3ccccc32)CC1 CHEMBL294951
 993 | CN(C)CCCOC1C(C(O)CO)OC2OC(C)(C)OC12 CHEMBL1316321
 994 | CC1(C(=O)O)CSC(c2ccc(O)cc2O)=N1 CHEMBL432481
 995 | CCN(CC)C(=O)NC1C=C2c3cccc4[nH]cc(c43)CC2N(C)C1 CHEMBL157138
 996 | CC(C[N+](C)(C)C)OC(N)=O CHEMBL1482
 997 | Cc1ccc(C(=CCN2CCCC2)c2cccc(C=CC(=O)O)n2)cc1 CHEMBL1224
 998 | CCOC(=O)C(C)(N)Cc1ccc(O)c(O)c1 CHEMBL1201233
 999 | CNS(=O)(=O)CCc1ccc2[nH]cc(C3CCN(C)CC3)c2c1 CHEMBL1278
1000 | CC(CN1CC(=O)NC(=O)C1)N1CC(=O)NC(=O)C1 CHEMBL1738
1001 | Cc1cc(O)ccc1Cl CHEMBL1230222
1002 | 


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/README.md:
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 1 | #### Code snippets from Team-SKI 
 2 | This repository contains code snippets that shall demonstrate the use of RDKit, pandas, and other python libaries for common computer-aided drug design tasks. 
 3 | 
 4 | ```
 5 | ├── Cheminformatics
 6 | │   └── scaffold-analysis
 7 | │
 8 | ├── Kinase inhibitors
 9 | │   └── approved-or-in-clinical-trials
10 | │
11 | ├── Presentations and Tutorials
12 | │   ├── Molecular Modelling Workshop 2014
13 | │   └── Protvec demo 2017
14 | │   └── RDKit UGM 2014
15 | │       └── hackaton
16 | │
17 | └── Virtual-Screening
18 | ```
19 | These projects were supported by [BioMed X](http://bio.mx/) Innovation Center, Heidelberg 
20 | 
21 | ---
22 | #### Presentations and tutorials
23 |   * **Molecular Modelling Workshop 2014**  
24 | *Scaffold analysis in Python with RDKit and pandas*  
25 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Presentations%20and%20tutorials/Molecular%20Modelling%20Workshop%202014/Scaffold%20analysis%20in%20Python%20with%20RDKit%20and%20pandas%20-%20MMWS%20Erlangen%202014.ipynb)
26 | 
27 |   * **Protvec demo 2017**  
28 | *Demo of encoding protein sequences via vectors*
29 | 
30 |   * **RDKit UGM 2014** - [RDKit UGM](https://github.com/rdkit/UGM_2014)  
31 | *Scaffold analysis of ChEMBL data with pandas and RDKit*  
32 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Presentations%20and%20tutorials/RDKit%20UGM%202014/Scaffold%20analysis%20of%20ChEMBL%20data%20with%20pandas%20and%20RDKit%20-%20RDKit%20UGM2014.ipynb)  
33 | 
34 |     *hackaton contribution*  
35 | Demo of SaveXlsxFromFrame function that can export PandasDataFrame to Excel including images of molecules.  
36 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Presentations%20and%20tutorials/RDKit%20UGM%202014/rdkit_hackaton/XLSX%20export.ipynb) -- Resulting demo xlsx: [download](https://github.com/Team-SKI/snippets/blob/master/IPython/rdkit_hackaton/demo.xlsx)
37 | 
38 | ---
39 | #### Cheminformatics
40 |   * **Scaffold analysis in Python with RDKit and pandas**  
41 | Internal presentation given at BioMed X team meeting, March 2014.  
42 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Cheminformatics/Basics/Scaffold%20analysis%20%26%20Schnellkurs%20in%20chemoinformatics.ipynb)
43 | 
44 |   * **Markdown usage**  
45 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Cheminformatics/Basics/Markdown%20demo.ipynb)
46 |  
47 |   * **RDKit pandas integration**  
48 | Demo of new functions that were integrated in [RDKit] (https://github.com/rdkit/rdkit/commit/8269bc9002cf3c6b106c847d86bcbabc016b697e), 2013.   
49 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Cheminformatics/Basics/RDKit%26pandas%20demo%20of%20new%20functions.ipynb)
50 | 
51 |   * **Rendering of images in IPython**  
52 | Example of how to use object representations.  
53 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Cheminformatics/Basics/Custom%20objects%20and%20their%20rendering%20in%20IPython.ipynb)
54 | 
55 | ---
56 | #### Kinase-Inhibitors
57 |   * **approved or in clinical trials**  
58 | Notebook that extracts all kinase inhibitors that are in clinical trials or are on the market.  
59 | Jupyter notebook: [view](https://github.com/Team-SKI/snippets/blob/master/Kinase%20inhibitors/Kinase%20inhibitors%20-%20approved%20or%20in%20clinical%20trials.ipynb)
60 | 
61 | ---
62 | #### Virtual-Screening
63 |   * **ligand-3D-conformations**  
64 | [prepare_for_docking.py](https://github.com/Team-SKI/snippets/blob/master/Structural%20bioinformatics/prepare_for_docking.py): Script that uses Open Babel to generate 3D structures of compounds.    
65 | For usage info run `prepare_for_docking.py -h`
66 | 
67 |   * **filtering**  
68 | [filter_pains.py](https://github.com/Team-SKI/snippets/blob/master/Cheminformatics/Screening/filter_pains.py): Script that uses RDKit to remove PAINS compounds from sdf or smile files.  
69 | For usage info run `filter_pains.py -h`
70 | 


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/Virtual-Screening/ligand-3D-conformations/prepare_for_docking.py:
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 1 | #!/usr/bin/env python
 2 | 
 3 | __author__ = "Samo Turk"
 4 | __copyright__ = "Copyright (C) 2014 by BioMed X GmbH"
 5 | __credits__ = ["Simone Fulle", "Katra Kolsek"]
 6 | __license__ = "GPL"
 7 | __version__ = "0.1"
 8 | __email__ = "turk@bio.mx"
 9 | __status__ = "Development"
10 | 
11 | import argparse
12 | import sys
13 | import os
14 | import pybel
15 | 
16 | def gen3D(mol, pH=7.4, forcefield="MMFF94", s1=10, s2=500):
17 |     """
18 |     Add protons for certain pH and generates 3D conformation and minimizes molecule
19 |     - pH: defaults to 7.4
20 |     - forcefield: options - MMFF94, UFF or Ghemical, defaults to MMFF94
21 |     - s1: how many steps for make3D, defaults to 10
22 |     - s2: how many steps for localopt, defaults to 500
23 |     """
24 |     mol.OBMol.AddHydrogens(False, True, pH)
25 |     mol.make3D(forcefield=forcefield, steps=s1)
26 |     mol.localopt(forcefield=forcefield, steps=s2)
27 |     return mol
28 | 
29 | def arg_parser():
30 |     parser = argparse.ArgumentParser(description='Generate 3D structures of molecules.')
31 |     parser.add_argument('-i', '--infile', help="Specifies input file")
32 |     parser.add_argument('-o', '--outfile', help="Specifies output file")
33 |     parser.add_argument('-p', '--ph', default=7.4, help="Specifies pH for hydrogen addition")
34 |     parser.add_argument('-f', '--forcefield', default='MMFF94', help="Specifies forcefield. MMFF94, UFF or Ghemical, defaults to MMFF94")
35 |     parser.add_argument('-s1', '--steps1', default=10, help="Specifies how many steps for make3D, defaults to 10")
36 |     parser.add_argument('-s2', '--steps2', default=500, help="Specifies how many steps for localopt, defaults to 500")
37 |     
38 |     return parser
39 | 
40 | if __name__ == "__main__":
41 |     parser = arg_parser()
42 |     if len(sys.argv) == 1:
43 |         argv = ['-h']
44 |     else:
45 |         argv = sys.argv[1:]
46 |     args = parser.parse_args(argv)
47 |     
48 |     informat = args.infile.split(".")[-1]
49 |     outformat = args.outfile.split(".")[-1]
50 |     
51 |     # Limit acceptable in and out formats
52 |     informats = ['smi', 'ism', 'sdf', 'mol2', 'mol', 'pdb']
53 |     outformats = ['mol2', 'sdf', 'pdbqt']
54 |     
55 |     
56 |     if informat in informats and outformat in outformats:
57 |         mols = pybel.readfile(informat, args.infile)
58 |         numMols = 0
59 |         for mol in mols:
60 |             numMols += 1
61 |         mols = pybel.readfile(informat, args.infile)
62 |         os.system('cls' if os.name == 'nt' else 'clear') # Clear the terminal
63 |         molsdetected = str(numMols) + " molecules detected."
64 |         print(molsdetected)
65 |         i = 1
66 |         output = pybel.Outputfile(outformat, args.outfile, overwrite=True)
67 |         for mol in mols:
68 |             mol = gen3D(mol, pH=float(args.ph), forcefield=args.forcefield, s1=int(args.steps1), s2=int(args.steps2))
69 |             os.system('cls' if os.name == 'nt' else 'clear')
70 |             print(molsdetected)
71 |             print("Processing molecule titled: " + str(mol.title))
72 |             output.write(mol)
73 |             print(str(i) + " out of " + str(numMols))
74 |             i += 1
75 |         output.close()
76 |     else:
77 |         print("Format either of infile or outfile not recognized!\nSupported formats are: " + " ".join(list(set(informats+outformats))))
78 |     


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