Skip to content

Instantly share code, notes, and snippets.

@iwatobipen
Created June 1, 2019 12:08
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save iwatobipen/27b5111bd97bbcdcd68cde51bc8c8ed9 to your computer and use it in GitHub Desktop.
Save iwatobipen/27b5111bd97bbcdcd68cde51bc8c8ed9 to your computer and use it in GitHub Desktop.
hetero_suffle_Example
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import pprint\n",
"from rdkit import Chem\n",
"from rdkit.Chem import rdChemReactions\n",
"from rdkit.Chem import AllChem\n",
"from rdkit.Chem import RWMol\n",
"from rdkit.Chem.Draw import IPythonConsole"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"mol = Chem.AddHs(Chem.MolFromSmiles('Cc1ccccc1'))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"AllChem.EmbedMolecule(mol)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('\\n'\n",
" ' RDKit 3D\\n'\n",
" '\\n'\n",
" ' 15 15 0 0 0 0 0 0 0 0999 V2000\\n'\n",
" ' 2.1985 -0.1426 0.0619 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.7133 -0.0733 0.0106 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.0761 1.1546 0.1011 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.2976 1.2884 0.0602 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0772 0.1594 -0.0761 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.4454 -1.0663 -0.1665 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -0.0700 -1.1998 -0.1256 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.4632 -0.5975 1.0482 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6208 0.8583 0.0206 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6037 -0.8414 -0.7013 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.7267 2.0352 0.2090 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.7313 2.2955 0.1378 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -3.1580 0.2587 -0.1088 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0514 -1.9718 -0.2751 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.4286 -2.1575 -0.1960 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 1 2 1 0\\n'\n",
" ' 2 3 2 0\\n'\n",
" ' 3 4 1 0\\n'\n",
" ' 4 5 2 0\\n'\n",
" ' 5 6 1 0\\n'\n",
" ' 6 7 2 0\\n'\n",
" ' 7 2 1 0\\n'\n",
" ' 1 8 1 0\\n'\n",
" ' 1 9 1 0\\n'\n",
" ' 1 10 1 0\\n'\n",
" ' 3 11 1 0\\n'\n",
" ' 4 12 1 0\\n'\n",
" ' 5 13 1 0\\n'\n",
" ' 6 14 1 0\\n'\n",
" ' 7 15 1 0\\n'\n",
" 'M END\\n')\n"
]
}
],
"source": [
"mblock = Chem.MolToMolBlock(mol)\n",
"pprint.pprint(mblock)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"rxn = rdChemReactions.ReactionFromSmarts('[c:1][H]>>[n:1]')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"ps = rxn.RunReactants((mol,))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<rdkit.Chem.rdchem.Mol at 0x1088d9138>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ps[0][0]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('\\n'\n",
" ' RDKit 3D\\n'\n",
" '\\n'\n",
" ' 14 14 0 0 0 0 0 0 0 0999 V2000\\n'\n",
" ' 0.0761 1.1546 0.1011 N 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.7133 -0.0733 0.0106 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.2976 1.2884 0.0602 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.1985 -0.1426 0.0619 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -0.0700 -1.1998 -0.1256 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0772 0.1594 -0.0761 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.7313 2.2955 0.1378 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.4632 -0.5975 1.0482 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6208 0.8583 0.0206 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6037 -0.8414 -0.7013 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.4454 -1.0663 -0.1665 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.4286 -2.1575 -0.1960 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -3.1580 0.2587 -0.1088 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0514 -1.9718 -0.2751 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2 1 2 0\\n'\n",
" ' 1 3 1 0\\n'\n",
" ' 4 2 1 0\\n'\n",
" ' 5 2 1 0\\n'\n",
" ' 3 6 2 0\\n'\n",
" ' 3 7 1 0\\n'\n",
" ' 4 8 1 0\\n'\n",
" ' 4 9 1 0\\n'\n",
" ' 4 10 1 0\\n'\n",
" ' 11 5 2 0\\n'\n",
" ' 5 12 1 0\\n'\n",
" ' 6 11 1 0\\n'\n",
" ' 6 13 1 0\\n'\n",
" ' 11 14 1 0\\n'\n",
" 'M END\\n')\n"
]
}
],
"source": [
"pprint.pprint(Chem.MolToMolBlock(ps[0][0]))"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"rxn2 = rdChemReactions.ReactionFromSmarts('[H:1]([c:2])>>[F:1]([c:2])')"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"ps2 = rxn2.RunReactants((mol,))"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<rdkit.Chem.rdchem.Mol at 0x11a970d98>"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ps2[0][0]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('\\n'\n",
" ' RDKit 3D\\n'\n",
" '\\n'\n",
" ' 15 15 0 0 0 0 0 0 0 0999 V2000\\n'\n",
" ' 0.7267 2.0352 0.2090 F 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.0761 1.1546 0.1011 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.7133 -0.0733 0.0106 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.2976 1.2884 0.0602 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.1985 -0.1426 0.0619 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -0.0700 -1.1998 -0.1256 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0772 0.1594 -0.0761 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.7313 2.2955 0.1378 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.4632 -0.5975 1.0482 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6208 0.8583 0.0206 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6037 -0.8414 -0.7013 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.4454 -1.0663 -0.1665 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.4286 -2.1575 -0.1960 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -3.1580 0.2587 -0.1088 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0514 -1.9718 -0.2751 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2 1 1 0\\n'\n",
" ' 3 2 2 0\\n'\n",
" ' 2 4 1 0\\n'\n",
" ' 5 3 1 0\\n'\n",
" ' 6 3 1 0\\n'\n",
" ' 4 7 2 0\\n'\n",
" ' 4 8 1 0\\n'\n",
" ' 5 9 1 0\\n'\n",
" ' 5 10 1 0\\n'\n",
" ' 5 11 1 0\\n'\n",
" ' 12 6 2 0\\n'\n",
" ' 6 13 1 0\\n'\n",
" ' 7 12 1 0\\n'\n",
" ' 7 14 1 0\\n'\n",
" ' 12 15 1 0\\n'\n",
" 'M END\\n')\n"
]
}
],
"source": [
"pprint.pprint(Chem.MolToMolBlock(ps2[0][0]))"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('\\n'\n",
" ' RDKit 3D\\n'\n",
" '\\n'\n",
" ' 15 15 0 0 0 0 0 0 0 0999 V2000\\n'\n",
" ' 2.1985 -0.1426 0.0619 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.7133 -0.0733 0.0106 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.0761 1.1546 0.1011 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.2976 1.2884 0.0602 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0772 0.1594 -0.0761 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.4454 -1.0663 -0.1665 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -0.0700 -1.1998 -0.1256 C 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.4632 -0.5975 1.0482 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6208 0.8583 0.0206 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 2.6037 -0.8414 -0.7013 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.7267 2.0352 0.2090 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -1.7313 2.2955 0.1378 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -3.1580 0.2587 -0.1088 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' -2.0514 -1.9718 -0.2751 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 0.4286 -2.1575 -0.1960 H 0 0 0 0 0 0 0 0 0 0 0 0\\n'\n",
" ' 1 2 1 0\\n'\n",
" ' 2 3 2 0\\n'\n",
" ' 3 4 1 0\\n'\n",
" ' 4 5 2 0\\n'\n",
" ' 5 6 1 0\\n'\n",
" ' 6 7 2 0\\n'\n",
" ' 7 2 1 0\\n'\n",
" ' 1 8 1 0\\n'\n",
" ' 1 9 1 0\\n'\n",
" ' 1 10 1 0\\n'\n",
" ' 3 11 1 0\\n'\n",
" ' 4 12 1 0\\n'\n",
" ' 5 13 1 0\\n'\n",
" ' 6 14 1 0\\n'\n",
" ' 7 15 1 0\\n'\n",
" 'M END\\n')\n"
]
}
],
"source": [
"pprint.pprint(Chem.MolToMolBlock(mol))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.6.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment