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ptosco/AddHsWithCoordsSp2BugFixed.ipynb

Created August 30, 2020 13:15
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AddHsWithCoordsSp2BugFixed
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AddHsWithCoordsSp2BugFixed.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "9301e65277f143a2bd6ddd3458b5d1ef",
"version_major": 2,
"version_minor": 0
},
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from rdkit import Chem\n",
"from rdkit.Chem.Draw import IPythonConsole, rdMolDraw2D\n",
"from IPython.display import SVG\n",
"from rdkit.Chem import rdCoordGen, rdDepictor, rdMolTransforms, rdDistGeom\n",
"import numpy as np\n",
"import nglview as nv"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"use_coordgen = True"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def add_coords(m, use_coordgen=False):\n",
" if use_coordgen:\n",
" rdCoordGen.AddCoords(m)\n",
" else:\n",
" rdDepictor.Compute2DCoords(m)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"m = Chem.MolFromSmiles('Nc1nnc2n1CCS2')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<rdkit.Chem.rdchem.Mol at 0x7fdd89d21d00>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now I call my `add_coords` function to add a 2D conformation to the molecule:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"add_coords(m, use_coordgen)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m.GetNumConformers()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<rdkit.Chem.rdchem.Mol at 0x7fdd89d21d00>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"scale = np.array([[2, 0, 0, 0], [0, 2, 0, 0], [0, 0, 1, 0], [0, 0, 0, 1]], dtype=np.double)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[2., 0., 0., 0.],\n",
" [0., 2., 0., 0.],\n",
" [0., 0., 1., 0.],\n",
" [0., 0., 0., 1.]])"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"scale"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"rdMolTransforms.TransformConformer(m.GetConformer(), scale)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m.GetConformer().Is3D()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"m = rdMolDraw2D.PrepareMolForDrawing(m)\n",
"m = Chem.AddHs(m, addCoords=True)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"draw_opt = rdMolDraw2D.MolDrawOptions()\n",
"draw_opt.addAtomIndices = True\n",
"drawer = rdMolDraw2D.MolDraw2DSVG(400, 400)\n",
"drawer.SetDrawOptions(draw_opt)\n",
"drawer.DrawMolecule(m)\n",
"drawer.FinishDrawing()\n",
"svg = drawer.GetDrawingText()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
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"<path class=\"note\" d=\"M 104.162 128.078 L 106.136 128.078 L 106.136 121.343 L 103.959 122.017 L 103.666 121.266 L 106.429 120.031 L 107.333 120.184 L 107.333 128.078 L 109.102 128.078 L 109.102 129.097 L 104.162 129.097 L 104.162 128.078 \" fill=\"#000000\"/>\n",
"<path class=\"note\" d=\"M 110.287 128.078 L 112.26 128.078 L 112.26 121.343 L 110.083 122.017 L 109.79 121.266 L 112.553 120.031 L 113.457 120.184 L 113.457 128.078 L 115.227 128.078 L 115.227 129.097 L 110.287 129.097 L 110.287 128.078 \" fill=\"#000000\"/>\n",
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"<path class=\"note\" d=\"M 66.2258 172.369 Q 66.5569 171.516, 67.3463 171.045 Q 68.1357 170.561, 69.2307 170.561 Q 70.5931 170.561, 71.357 171.299 Q 72.121 172.038, 72.121 173.349 Q 72.121 174.686, 71.1278 175.934 Q 70.1474 177.182, 68.1102 178.659 L 72.2738 178.659 L 72.2738 179.677 L 66.2004 179.677 L 66.2004 178.824 Q 67.881 177.627, 68.8742 176.736 Q 69.8801 175.845, 70.3639 175.043 Q 70.8477 174.241, 70.8477 173.413 Q 70.8477 172.547, 70.4148 172.063 Q 69.9819 171.579, 69.2307 171.579 Q 68.5049 171.579, 68.0211 171.872 Q 67.5373 172.165, 67.1935 172.815 L 66.2258 172.369 \" fill=\"#000000\"/>\n",
"<path class=\"note\" d=\"M 9.94386 257.257 L 11.9174 257.257 L 11.9174 250.521 L 9.74014 251.196 L 9.44729 250.445 L 12.2103 249.21 L 13.1143 249.363 L 13.1143 257.257 L 14.8841 257.257 L 14.8841 258.275 L 9.94386 258.275 L 9.94386 257.257 \" fill=\"#000000\"/>\n",
"<path class=\"note\" d=\"M 19.7479 253.526 Q 20.6265 253.781, 21.0466 254.354 Q 21.4795 254.914, 21.4795 255.805 Q 21.4795 256.569, 21.0976 257.168 Q 20.7156 257.753, 20.0153 258.084 Q 19.315 258.403, 18.3983 258.403 Q 17.4306 258.403, 16.7048 258.072 Q 15.9918 257.728, 15.4189 257.04 L 16.1446 256.302 Q 16.7048 256.913, 17.1759 257.155 Q 17.6471 257.384, 18.3983 257.384 Q 19.2132 257.384, 19.7097 256.951 Q 20.2063 256.506, 20.2063 255.793 Q 20.2063 254.876, 19.6843 254.468 Q 19.175 254.048, 18.0672 254.048 L 17.4179 254.048 L 17.4179 253.132 L 17.9908 253.132 Q 18.9712 253.119, 19.4933 252.699 Q 20.0153 252.266, 20.0153 251.464 Q 20.0153 250.878, 19.5824 250.534 Q 19.1495 250.178, 18.411 250.178 Q 17.6598 250.178, 17.1887 250.445 Q 16.7303 250.712, 16.3738 251.387 L 15.4953 250.916 Q 15.8136 250.165, 16.5775 249.668 Q 17.3415 249.159, 18.411 249.159 Q 19.7352 249.159, 20.5119 249.783 Q 21.2886 250.407, 21.2886 251.464 Q 21.2886 252.189, 20.8939 252.711 Q 20.4991 253.233, 19.7479 253.526 \" fill=\"#000000\"/>\n",
"<path class=\"note\" d=\"M 44.3829 200.532 L 46.3565 200.532 L 46.3565 193.797 L 44.1792 194.472 L 43.8864 193.72 L 46.6493 192.485 L 47.5533 192.638 L 47.5533 200.532 L 49.3232 200.532 L 49.3232 201.551 L 44.3829 201.551 L 44.3829 200.532 \" fill=\"#000000\"/>\n",
"<path class=\"note\" d=\"M 55.5621 198.457 L 56.6444 198.457 L 56.6444 199.475 L 55.5621 199.475 L 55.5621 201.551 L 54.3652 201.551 L 54.3652 199.475 L 49.7051 199.475 L 49.7051 198.673 L 53.6522 192.536 L 55.5621 192.536 L 55.5621 198.457 M 51.1821 198.457 L 54.3652 198.457 L 54.3652 193.351 L 51.1821 198.457 \" fill=\"#000000\"/>\n",
"</svg>"
],
"text/plain": [
"<IPython.core.display.SVG object>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SVG(svg)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now the amine hydrogens have correctly drawn on the `xy` plane."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 N (2.242488750881619, 3.127111121283637, 0.0)\n",
"1 C (1.6228888363308378, 1.2255110846625432, 0.0)\n",
"2 N (2.7972888607449002, -0.3932888878716363, 0.0)\n",
"3 N (1.6204889339870878, -2.0104888237847223, 0.0)\n",
"4 C (-0.28111110263400585, -1.390888909233941, 0.0)\n",
"5 N (-0.2795110660129121, 0.6091110907660591, 0.0)\n",
"6 C (-2.1811111026340058, 1.2287110816107856, 0.0)\n",
"7 C (-3.3579110293918184, -0.3884888543023004, 0.0)\n",
"8 S (-2.183511081271701, -2.0072889031304255, 0.0)\n",
"9 H (1.5739706527928292, 3.8708069949630244, 0.0)\n",
"10 H (3.2208073192220263, 3.3342168402784926, 0.0)\n",
"11 H (-2.4893831549564998, 2.180009321784117, 0.0)\n",
"12 H (-3.168679828101494, 1.3858989070888434, 0.0)\n",
"13 H (-4.357910769803254, -0.38776831487957264, 0.0)\n",
"14 H (-3.8112496563876204, 0.5028495153831751, 0.0)\n"
]
}
],
"source": [
"for i, a in enumerate(m.GetAtoms()):\n",
" print(a.GetIdx(), a.GetSymbol(), tuple(m.GetConformer().GetAtomPosition(i)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Also when working with 3D conformations hydrogens are now placed in the same plane as the `sp2` system:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"m = Chem.MolFromSmiles(\"NC=C\")"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rdDistGeom.EmbedMolecule(m, useRandomCoords=True)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m.GetNumConformers()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"m = rdMolDraw2D.PrepareMolForDrawing(m)\n",
"m = Chem.AddHs(m, addCoords=True)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"draw_opt = rdMolDraw2D.MolDrawOptions()\n",
"draw_opt.addAtomIndices = True\n",
"drawer = rdMolDraw2D.MolDraw2DSVG(400, 400)\n",
"drawer.SetDrawOptions(draw_opt)\n",
"drawer.DrawMolecule(m)\n",
"drawer.FinishDrawing()\n",
"svg = drawer.GetDrawingText()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"view1 = nv.NGLWidget()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ac2cafe90645402eb11b28495c4b912b",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"NGLWidget()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"view1.add_structure(nv.RdkitStructure(m))\n",
"view1"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
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\">"
]
},
{
"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": "3.6.11"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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