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@jose-manuel
Created February 28, 2020 15:10
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Draw Murcko Scaffolds Extraction as Reaction with Kekulized Molecules
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Representing Kekulized Molecules in a Reaction"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import rdkit\n",
"from rdkit.Chem import AllChem as Chem\n",
"from rdkit.Chem import PandasTools\n",
"from rdkit.Chem import Draw\n",
"from rdkit.Chem import rdChemReactions\n",
"from rdkit.Chem.Draw import rdMolDraw2D\n",
"from rdkit.Chem.Draw import IPythonConsole\n",
"from rdkit.Chem.Scaffolds import MurckoScaffold\n",
"from IPython.display import SVG"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"RDKIT: 2019.03.4\n"
]
}
],
"source": [
"print('RDKIT:'.ljust(20) + f\"{rdkit.__version__}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I would like to represent the Murcko Scaffold extraction with an image (preferientially SVG). \n",
"To get started, I define an example molecule."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<rdkit.Chem.rdchem.Mol at 0x7f7e2b396d50>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"smi1 = 'OC1=CC=CC=C1'\n",
"mol1 = Chem.MolFromSmiles(smi1)\n",
"mol1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I extract the Murcko Scaffold from the molecule above (see below). \n",
"I kekulize the SMILES because I want the rendered image to show kekulized Molecules instead of the aromatic representation."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<rdkit.Chem.rdchem.Mol at 0x7f7e29c26c10>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mol2 = MurckoScaffold.GetScaffoldForMol(mol1)\n",
"Chem.Kekulize(mol2)\n",
"smi2 = Chem.MolToSmiles(mol2, kekuleSmiles=True)\n",
"mol2"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I compute the reaction from smarts (could not find any function for smiles). The useSmiles argument looks promising."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rxn_str=OC1=CC=CC=C1>>C1=CC=CC=C1\n"
]
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<rdkit.Chem.rdChemReactions.ChemicalReaction at 0x7f7e29c269e0>"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rxn_str = f\"{smi1}>>{smi2}\"\n",
"print(f\"rxn_str={rxn_str}\")\n",
"rxn = rdChemReactions.ReactionFromSmarts(rxn_str, useSmiles=True)\n",
"rxn"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The molecules are shown with anaromatic representation instead of a kekulized representation. \n",
"Am I missing something?"
]
}
],
"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": 4
}
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