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July 14, 2019 16:48
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{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"from rdkit.Chem import AllChem as Chem\n", | |
"from rdkit.Chem.Draw import IPythonConsole\n", | |
"IPythonConsole.ipython_3d = True" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"mol = Chem.AddHs(Chem.MolFromSmiles(\"O=C(N1CC(CCCCCCCC)CCCCCCCCCC)C(C2=C1C3=CC=CS3)=C(C4=CC=C(C5=CC(SC(C6=CC=C(C7=C8C(C(N7CC(CCCCCCCC)CCCCCCCCCC)=O)=C(C9=CC=C(C%10=CC(SC(C%11=CC=C(C%12=C%13C(C(N%12CC(CCCCCCCC)CCCCCCCCCC)=O)=C(C%14=CC=C(C%15=CC(SC=C%16)=C%16S%15)S%14)N(CC(CCCCCCCC)CCCCCCCCCC)C%13=O)S%11)=C%17)=C%17S%10)S9)N(CC(CCCCCCCC)CCCCCCCCCC)C8=O)S6)=C%18)=C%18S5)S4)N(CC(CCCCCCCC)CCCCCCCCCC)C2=O\"))" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"0" | |
] | |
}, | |
"execution_count": 3, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"Chem.EmbedMolecule(mol, useRandomCoords=True)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"application/3dmoljs_load.v0": "<div id=\"3dmolviewer_1563122892557303\" style=\"position: relative; width: 400px; height: 400px\">\n <p id=\"3dmolwarning_1563122892557303\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension: <br>\n <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n </div>\n<script>\n\nvar loadScriptAsync = function(uri){\n return new Promise((resolve, reject) => {\n var tag = document.createElement('script');\n tag.src = uri;\n tag.async = true;\n tag.onload = () => {\n resolve();\n };\n var firstScriptTag = document.getElementsByTagName('script')[0];\n firstScriptTag.parentNode.insertBefore(tag, firstScriptTag);\n});\n};\n\nif(typeof $3Dmolpromise === 'undefined') {\n$3Dmolpromise = null;\n $3Dmolpromise = loadScriptAsync('https://3dmol.csb.pitt.edu/build/3Dmol.js');\n}\n\nvar viewer_1563122892557303 = null;\nvar warn = document.getElementById(\"3dmolwarning_1563122892557303\");\nif(warn) {\n warn.parentNode.removeChild(warn);\n}\n$3Dmolpromise.then(function() {\nviewer_1563122892557303 = $3Dmol.createViewer($(\"#3dmolviewer_1563122892557303\"),{backgroundColor:\"white\"});\n\tviewer_1563122892557303.removeAllModels();\n\tviewer_1563122892557303.addModel(\"\\n RDKit 3D\\n\\n470487 0 0 0 0 0 0 0 0999 V2000\\n -8.7465 0.4131 3.4531 O 0 0 0 0 0 0 0 0 0 0 0 0\\n -8.6707 1.6600 3.3735 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -9.5249 2.6329 3.9679 N 0 0 0 0 0 0 0 0 0 0 0 0\\n -10.6193 2.3892 4.8651 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -11.9665 2.0141 4.3368 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -12.8213 1.9449 5.6442 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -14.2049 1.5493 5.4578 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -15.0052 1.4973 6.7070 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -14.7114 0.5521 7.7822 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -13.3894 0.5197 8.4395 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -13.3779 -0.4488 9.6673 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -11.9408 -0.4058 10.2334 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -11.6063 1.0037 10.6333 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -12.0353 0.6645 3.6924 C 0 0 0 0 0 0 0 0 0 0 0 0\\n -11.6697 -0.4618 4.6438 C 0 0 0 0 0 0 0 0 0 0 0 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"\tviewer_1563122892557303.setStyle({\"stick\": {}});\n", | |
"\tviewer_1563122892557303.setBackgroundColor(\"0xeeeeee\");\n", | |
"\tviewer_1563122892557303.zoomTo();\n", | |
"viewer_1563122892557303.render();\n", | |
"});\n", | |
"</script>" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
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\n", | |
"text/html": [], | |
"text/plain": [ | |
"<rdkit.Chem.rdchem.Mol at 0x11d7296c0>" | |
] | |
}, | |
"execution_count": 4, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"mol" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.7.3" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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