{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Molecule\n",
    "\n",
    "The central class to construct a molecule from different chemical input formats. This class is built on top of the RDKit and OpenBabel python APIs. We join the forces and strengths of these two cheminformatic libraries for a consistent user experience. \n",
    "\n",
    "Several methods are available in this module to facilitate the manipulation of chemical data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from chemml.chem import Molecule\n",
    "\n",
    "caffeine_smiles = 'CN1C=NC2=C1C(=O)N(C(=O)N2C)C'\n",
    "caffeine_smarts = '[#6]-[#7]1:[#6]:[#7]:[#6]2:[#6]:1:[#6](=[#8]):[#7](:[#6](=[#8]):[#7]:2-[#6])-[#6]'\n",
    "caffeine_inchi = 'InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Construct a molecule using SMILES\n",
    "\n",
    "You can always see a representation of the available attributes and chemical formats. The creator shows you how this molecule was originally constructed. The rdkit and pybel molecule objects are also accessible if they have been used to create the molecule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<chemml.chem.Molecule(\n",
      "        rdkit_molecule : <rdkit.Chem.rdchem.Mol object at 0x7ff612682ee0>,\n",
      "        pybel_molecule : None,\n",
      "        creator        : ('SMILES', 'CN1C=NC2=C1C(=O)N(C(=O)N2C)C'),\n",
      "        smiles         : 'Cn1c(=O)c2c(ncn2C)n(C)c1=O',\n",
      "        smarts         : None,\n",
      "        inchi          : None,\n",
      "        xyz            : None)>\n",
      "Cn1c(=O)c2c(ncn2C)n(C)c1=O\n",
      "('SMILES', 'CN1C=NC2=C1C(=O)N(C(=O)N2C)C')\n"
     ]
    }
   ],
   "source": [
    "mol = Molecule(caffeine_smiles, input_type='smiles')\n",
    "print(mol)\n",
    "print(mol.smiles)\n",
    "print(mol.creator)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Construct a molecule using 3D atomic coordinates\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<chemml.chem.Molecule(\n",
       "        rdkit_molecule : None,\n",
       "        pybel_molecule : <openbabel.pybel.Molecule object at 0x7ff61268cd60>,\n",
       "        creator        : ('XYZ', 'images/1_opt.xyz'),\n",
       "        smiles         : None,\n",
       "        smarts         : None,\n",
       "        inchi          : None,\n",
       "        xyz            : <XYZ(geometry: (28, 3), atomic_numbers: (28, 1), atomic_symbols: (28, 1))>)>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol = Molecule('images/1_opt.xyz', 'xyz')\n",
    "mol"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Construct a molecule using InChi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<chemml.chem.Molecule(\n",
       "        rdkit_molecule : <rdkit.Chem.rdchem.Mol object at 0x7ff61240b660>,\n",
       "        pybel_molecule : None,\n",
       "        creator        : ('InChi', 'InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3'),\n",
       "        smiles         : None,\n",
       "        smarts         : None,\n",
       "        inchi          : 'InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3',\n",
       "        xyz            : None)>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol = Molecule(caffeine_inchi, 'inchi')\n",
    "mol"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize the molecule\n",
    "\n",
    "The visualize method shows or allows us to save a molecule image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300 at 0x7FF6C07E2940>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add or remove hydrogens\n",
    "\n",
    "You may need to add hydrogens if you want to optimize the geometry of this molecule to get the spatial information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BMeLc9xUFjUbz5ptvAijpU0+pVAoXUaWXY5EI4eFkZkZyOZ0+zTpKCQgSWlhYWBVDeLxGEhKS9DxUqVQ9evSoegYKCNNwnJycnpXQdyxfvhxAl1Jm5UuD3Fzq0EHqVVQFCf/SNrW6T58+EpKQpORh1TaQiDQazVtvvYWSH5ZQqVTCBLxDhw6JnK1cCBU86tcnKdWdKIohSUiFPNy4caOeTvFKqryBAvv27QNQp06djIwMrQ1WrVoFoH379pJdpCE6mqysCKDDh1lHKRUDk5CI/u///o+hh0ZioICwWN+aNWu07s3MzKxbty6A//3vfyIHKwtqNb3zjmHUqTI8CYmdh0ZlID1/stfR0VGpVGptEBQUBKBdu3YS7AzXryeA6tSh//5jHeVVGKSExMJDlUrl7u4ujN0bg4EC3bp1A7BixQqtezMzM4XZW3/++ae4uV7NnTvk7k579rDOUQYMVUIq5OGmTZv0fa7CBt69e1ffp5MOf//9N4CaNWuWVFFz/fr1AFq2bKkuaSKi3khMpKNH6dQpLbsuXaKjR0naS0W84ObNmwcPHnz69GnxXZcuXTp48GBJX8tLR6Tiv8J8fH17aLQGCgi/+9KlS7Xuzc7ObtCgAYCQkBCRg+3eTQABtG9f0V3Ct8EKTQCqOohXgVvfHqpUqnfeecdoDSSi0NBQAA4ODiWViA8ODra3t9+8ebO4uV5I6OxMRb60cglJ5DL4godyuXz79u26PTI3UEB4MGjBggVa9+bk5KSkpIgciZ5L2LEjATRz5ku7uIREJCOtRSz1xpo1a2bOnCmXy7///vtRo0bp5Jjp6em9evW6cOGCs7PziRMnGjVqpJPDGiJnz57t1q2bvb19bGxsjRo1AFy4cOHUqVMLFiywsrKytLSs/pzSXwpb7O3tdVLsaM8eeHhg1SqEhODqVYSFoXXr/F3u7jh9GgoF7O0rfx5DpXzV1irP119/DWDmzJlC8azKe1jYwJMnTzZs2FAHKQ2Wrl27fvDBB0ePHg0KClq0aFFaWtrgwYNTUlKysrKEyh0JCQllP5pcLre3t+/RY1dMTF9bW9jaws4ODg6wsUHhl8LPNjYvXmqdgiSTYe1adO2K8eNx/jxEK2UmfcSWEDr1MC0trXfv3tzAwixatOjo0aPBwcHz5s2bOXPm48ePO3Xq9M8//6Snp2dlZWVmZqY+55UvFQpFampqaqrNjRvly2BpmW+mgwOmTIGtbf72Ll3g6Ykff8TWrXhew4XDQkK87KFMJhs5cmQFDsIN1Ernzp2/++67gQMHnj9/ftu2bRYWFtu2bbOxsREWFSsXeXl5SqVSoZCnp0OphFIJlQqpqfk/C/8UCqSnQ6V66WVWFrKykJQEAKmpLyQEsHIl9u+Hry8GDkTlFpWoQjD8Pio802hiYrJjx47yvlehUHTu3BlA/fr1Y41mpeiyk5GR0aRJEwBLlixhcXZ68oRiYujyZYqPzx+YWb06f++33xJAY8YQ8YEZImK+SGjFPFQoFJ06deIGlsK0adMAtG7dOicnh3WWohKq1dSxI8nldPEil5CIuYRUfg+5ga/kwoULJiYmpqamly5dYp2FqJiERHTpEsnl1L07de/OJZSAhFTIwx9//LH0ltzAV5Kdne3m5gbA19eXdZZ8iktIzxc1tbbmEkpDQiJauXLlKz0sbGBcXJyI6QwJPz8/AM2aNStprr34aJXwv/+oVq38J2m4hFKhdA+5gWUhPDzczMxMLpefllKdFq0S0vNy/lxCCUlIJXuoUCiEeavcwFLIzc0VVmOfIrE6LVFRFBhI//5bdLtGQ0FBFBhIJRSLMxakJSERrVixQvBw586dwpYCAxs0aMANLIXAwEAAzs7OJc1mkiAxMTR+PLF4oFVCSE5CetlDbmAZiY6OtrKyguQLOhWhTx8CaN481jmYIkUJqZCHjRs35ga+ErVaLUwiGS39Oi0vc+kSyWRkY0PaJsoaCxKVkIh8fX0BmJmZ1alT5+HDh6zjSBph1nydOnX+k36dlmL07UsASeZ+CgMk+ih7amrq0aNHAeTm5iYnJ589e5Z1Iuny4MGDOXPmAFi/fr0wfcmwWLQIMhm+/RZPn7KOwgrWnwJaSE1NFQraNm3adO7cuQBMTEx27drFOpdE6d27N4DBgwezDlJxPv5Yy3xf40FyEhY28NGjR/R80I97qBVhSSYHB4fHjx+zzlJxrl8nuZwsLcmQf4mKIy0JixsoEBAQwD0sztOnT4X1XiowDUVqDBpEAE2bxjoHCyQkYUkGCnAPi/Ppp58CeP/99yVY0re8RETkd4ZGOAYnFQlLN1CgwMOffvpJ5HgSZP/+/QCqVatWZQpbDRki9VWZ9IQkJExNTRWet2rWrFlJBgrMnz+fe0hECoXi9ddfR8krExoiN2+SXE7m5mRst4TZS1jYwLKMLnAPiUgozNOlSxfxy2nrlWHDCKCJE1nnEBfGEqakpJTLQIECD3/++We9xpMmx44dk8lkFhYWt27dYp1Fx9y+TaamZGZGRjVXlKWEFTNQwGg9VKlUQmHVktZ+MXRGjiSAxo1jnUNEmElYGQMF/P39jdDDL7/8EkCbNm2kUDxGH8TEkJkZmZhQhRY4MkjYSJiSktK+fXsAzZs3r8xdZmPz8Ny5c3K53NTUNCwsjHUWPTJ2rGGsGaorGEioKwMFCjz85ZdfdBJPsmRlZbm6ugLw9/dnnUW/3LtH5uZkYkKRkayjiILYEurWQAE/Pz8TE/Pu3WOqtoY+Pj4AXFxcMjMzWWfROxMmCMOkKtZBxEBUCZ8+fdq6dWvdGiiwYsU9gMzM6I8/dHhUCXHt2jWheMyZM2dYZxGDBw/I3X2rmZnlzZs3WWfRO+JJqD8DBfz8qKp6mJub265dOwDTp09nnUU8hCGozz77jHUQvSOShE+fPm3VqpVgYHx8vJ7OUlU9XLx4MYAGDRooiyyxWaWJj4+3srKSyWTXrl1jnUW/iCGhOAYKzJuX7+Gff+r1POIRFRVlaWkpk8n+/vtv1lnE5quvvgLw6aefsg6iX/QuYYGBLi4u+jZQoCp5qFaru3XrBmD8+PGsszAgISHB2tpaJpNdvXqVdRY9ol8JxTdQoMp4+M033wBwcnJissy1FBBW0RswYADrIHpEjxKyMlCgCngYFxcnLCr4p+H+DpUmKSnJ1tYWwMWLF1ln0Rf6kpCtgQJz5xqwhxqN5sMPPwTw+eefs87CGOEGab9+/VgH0Rd6kTAxMZG5gQKCh+bmhufhli1bANSsWTMxMZF1FsYkJyfb2dkBOH/+POssekH3EiYmJrZs2VIwMCEhQefHLy8FHu7dyzpKmYmPj69evToAI3km9pUIS019+OGHrIPoBR1LKDUDBQzOw08++QRA3759WQeRCqmpqcKn0qlTp1hn0T26lLDAwBYtWkjHQIE5cwzAw7S0tH///XfSpEkA7OzsHjx4wDqRhBAqDL333nvCy8TExCrz6IKMiCpVPPg5wqNVERERrVq1OnbsmFCKT1LMnIk1a2Bujj/+QL9+rNMAqampN2/evHXrVmxsrPCDsN4GgNq1aw8bNky4P8ERSEtLa9SoUUpKyokTJ3r06GFvb5+eng7A0tKyevXqVlZWwg8Cr3wp9KsSoawS7t27d8aMGdOnT586dWqRXWvXrl27dm1QUNCzZ8+WLl169OjROnXq6CGqDpg7Fxs34u+/sW4dIiMxYAD8/V9qcP06xozBp59izhxdnjcnJycmJiYyMjI6OjoyMjIqKio6OlqpVBZpZmlp6eLiQkTh4eEdOnT4999/ZTKZLnMYOEuWLPH39+/atWtoaOjrr7+enp6ekZFRgeNccHfvdOoULC1RvTqqV4eV1Yufi78svMXREebmLx3r2jUcPoyHD6FWo25dvPsuuncvbx7TMrZTKpVxcXGpqanFd6WkpMTFxSmVyuHDhw8ePNjUtKzHFJ9lyzBxIpydERWFsDCEh6N/f7Rt+6KBSoWwMLz1VqXOolDgzp3bERFnBdkiIyNjY2Pz8vKKNKtVq1aLFi2aN2/u4uLSokULFxeX+vXry+XyrKysxo0bX758+a+//uonhS5bMkybNm3dunVnz549duxYfHw8AI1Gk5aWlpaWplQqlUqlSqUq5aVSqUxPT09LS7MXPtqyspCQgISE8oVwc0NEBACkpWH0aOzdCwBWVjAxgUqFgAC8/TZ++QXOzmU/pI6FkbKBAgX/58jlMDfH5Mk4exbySqyLk5qKmzdx61b+/8bGIi4O77wTeerUmMLNnJyc3NzcGjVq5Orq6ubm5ubm5uTkpPWAlpaWs2bNmj59+vz58/v27cs7wwJsbGxmzJgxZ86c+fPn9+zZE4BcLheuMCtyuMxMpKbm/8vKKtPL5OT8njAvD3374tw5fPwxlixBq1YAEBeHpUuxbRvc3XH1KhwcyhhE6s7oD7kc06Zh2TJs3oyJE8v0luxsREcjOhpRUYiMzP+5+AVRtWqoW7fZ559/7urqKnR0zZo1s7CwKHu2iRMnrlmz5sqVK/v27Rs4cGDZ31jlmTp1alBQ0Pnz5w8fPiyshFNxrKxgZYW6dcv3rsxMAAgOxrlz6N8ff/754iO8YUNs3QozM2zahAULEBRUxkMar4QAfH3xww/w9cXHH2v5b5GaitjYF/3bzZuIjoZaXbRZ9epo1AiurnBzy//fBg0gl7cAfq5wMEtLSx8fn6lTp/r7+3/88cfyyvTUVYtq1ap9/PHH+/btY3aBYGUFAFu2AMDy5VouopYuxfbt2L4dq1ejbBeG5ZMwJydHpVIV2Zibm1uug0gHW1ssW4YvvsDs2di166Vdf/+NXr2Ktjc1RbNmaNECLi5o3hyurmjevOwXHeXDy8trzZo1ERERf/zxx+DBg/VyDgNEqVQePnz46dOnjx49YhYiPR03bqBuXbRsqWVvjRro2BGnT+PGjZfGG0qhjLcyfvzxx9KPY1jrtHToQKamREQaDXXpQgAdPUpEdPZsfgXo2FiysCBXV/LwoIAACgmhy5fp2TNRQ27cuBGAm5tbFSuzXRmEm6hvvfVWXl4esxC3bhFA3bqV2GD0aAJo374yHq98PWGPHj2EtdELc+rUqVOnTpXrONJBJsOGDXjrLXz5JW7ceLG9YUNkZbGLBQAYO3bsypUrb968GRISMnToUMZpJMC5c+eCg4NNTU2Dg4NNTEyY5RD+Mkr5ki9csj57VsbjlU/Cd999Vyh9XZiAgADDlRBAmzaYPBnr1mHtWnTtyjpNIczMzObOnTt+/PiAgACJ3/sRgezs7HHjxmk0Gn9/f7VavWnTJtvn2NnZOTg42NjY2NraWltb6z2KnR0ApKeX2EChAMBHR8vH4sXYvRtLlmDHDjYBiEjrSMMXX3yxatWq27dv//rrryNGjBA/mHTw9/ePjIxs0aLFnDlz1qxZM2/ePK3NTExMBCdtbW0FLQteClscHRxG29nB1vbFPwcH2NrCzKysUZydYWWFqCio1dDaId+8CQAuLmU8HpcQAOzssHo1hg/H4sVin5qI1q1bt2HDhvPnz9eoUaPIXhMTkzlz5nzxxRcLFy4cOnSo0XaGV69eDQoKksvlW7dutbCwaN++vZeXV8EteJVKlZqaKvyclZWVmpqq9akSgaY1aoxOSdGyw9Iy38nq1V/4aWPz0ktbW3TtCicnuLvj8GH8/Tf69Cl6nKgo3LiBpk3RoEEZfzsj/Y9anGHDsG0bjh8X+7wymezw4cO3b99es2bN0qVLizfw9PQMDAyMjo7etWvX6NGjxc4nAfLy8saOHZubmztz5sy3334bQK9evXoVH7wGAOTm5iqVSoVCoSyEQqFIT09XqVRKpdJBrUZ8PNLToVRCqYRKBYUC6enIykJWFpKSXpEmJAQeHpg2DYcPY+ZMdO6Mwo8KZGdj8mQQYcaMsv+CXMIXbNyI1q2RnS32eZcsWXLkyJG1a9d+9dVXtWvXLrLXxMTEz8/P09Nz4cKFw4YNMy/y7KIRsGzZsqtXrzZs2HDBggWvbGxmZlajRo3i1xSv5tmzfC3T0pCWBpXqpZfCz0plfv/WqxcmT8aGDejQAXPmoEsXyOW4fh0rV+LKFfTrBy+vcpy6jKOo+/fvd3Nz27hxY/Fd3333nZub24EDB8p4KCnw7rtUq5aW7X5+VL06zZghdp7+/fsDmD17tta9arVaqFSwZcsWkYMxJzIyUqj4eFS4iSQdNBpatYrs7Ql48c/Sknx8KDu7XEfS2VQmA4UIUng288qVKx06dLC2tr579+5rr71WvMFvv/02dOhQZ2fn27dvl+sJOINGo9F079793LlzEyZM2LRpE+s42sjKwrlzuH8fGg3q1kX37rCxKfdB9PMpYRhoNFSjBrVqRVJYYUV4RnRGCb2wRqN58803AWzYsEHkYAxZs2YNgLp166amprLOokeMWsJ79wigOnVY5yAiohs3bsjlcktLy0ePHmltsGfPHuEv8pnIT+4wIjY2Vqj4uFfK1RB0gVE/GRwZCQAtWrDOAQBo2bLloEGDsrKyVq5cqbXBoEGD2rRpEx8fv3XrVpGziQ8ReXl5qVSq4cOHDxgwgHUcPcP6U4Al//d/BNDkyaxzPOfmzZtyudzCwqKk6jJ79+4F4OTklJGRIXI2kQkODgbg6OhoDBUfeU8olZ4QgKur62effZadnb18+XKtDQYMGNCxY8eEhAThb7SqEh8fLxT8Xb9+ffF7NlUQ1p8CLOnenQD65x/WOQpx+/ZtU1NTMzOz2NhYrQ0OHDgAoFatWlWm1lhxpkz518LC7uOPP2YdRCSMWkJHRwKohHEQZnh6eqLUZZg6d+4MYOXKlWKmEo2ffyaA2rR59uiR7leSlSbGK2FyMgFkZ0caDesoL3Pnzh2hM7x7967WBocPHwbg6OiYnp4ucjZ9k5REtWsTQFu3so4iIsb7nfDWLQBwcZHEzfrCNGnSxNPTMzc3d8mSJVob9OrV65133klOTl6/fr3I2fTN1Kl4+hTvvosxY17duOrA+lOAGcHBBNCoUaxzaOPevXvm5uYmJiZRUVFaG/zzzz8AHBwcqtJd7AMHCCBra4qJYR1FXIy3J5Ta0Ghh6tevP2rUKLVarXVeBYD333+/R48eCoXi22+/FTmbnkhPz695t2wZGjdmnUZkWH8KMKN373LVARGb+/fvW1hYmJiY3Lp1S2uD0NBQAPb29lVjEd9x4wigTp2IYe0YVvCekHWOEnB2dh4zZoxarV5cwkTjbt269ezZMy0tLajM9S0ly8mT2LYNFhbYtk37VPUqDutPATZkZJBcTubmlJvLOkrJxMfHW1lZyeXy8PBwrQ3OnTsHwM7O7r///hM5mw7JyKAmTQigJUtYR2GEkfaEUVHQaNC0aRmrs7LByclp/PjxGo2mpM6wS5cuvXv3Tk9PF2YbGCjz5iEmBq1bY/Zs1lFYwfpTgA27dhFAgwezzvEqEhISrK2tZTLZ1atXtTa4fPmyTCarVq2agT5jeeECmZiQqSldusQ6CjuMtCeU+BfCAurUqTNx4kQiWrhwodYG7du379evX0ZGhiF2hjk5GDsWajVmzkSHDqzTMIT1pwAbBg0igAxiQfikpCRhWt2///6rtUFYWJjQGT558kTkbJXE358AatZM7NLmUsNIe8KoKMAQekIAjo6OkydPBrBo0SKtDdq1azdgwICMjIySJiJKk+vXsWIF5HJs3Zpfsdp4Yf0pwIDc3Dxn5zy5nAxlUl5ycrKtrS2ACxcuaG3wyln5UiM3lzp0IICmTGEdRQIYY094927MgwemLi6dRKiYrhNq1qwprFJeUs2/V87Klxpr1uDyZTg7Y9ky1lGkAOtPAQb8+eefAPr06cM6SDlITU11cHAAcPr0aa0NIiIihFn5Dx8+FDlbeVEqqWZNAujQIdZRpIEx9oSRkZEAWhjEN8LnODg4fPXVVwBKGiZ1c3MbMmRIKbPypYONDS5exOrVqORKu1UGY5QwKioKhiYhgOnTp9eoUePYsWMnT57U2mDhwoWmpqZbtmyJi4sTN5oWli7FhAnYs6fo9pgYTJiAixfx9dcsYkkSY5TQEHtCAPb29tOmTQPg5+entUGzZs2GDh2am5sbGBgoajJt/PEHNm/G2LF4/Pil7U+eYPNmnD3LKJYkMToJiSg6OhqAS5lXrpIOX3311Ztvvjl8+HAqoW56QECAqanpDz/8EBsbK3K24shkUKkwfTrrHJLH6CR8/Phxenp6rVq1atasyTpLubGzs7t27dqkSZO0LmaIQrPyJ02a9M8//1y6dCkqKurRo0dpaWkiRwVgZoYRI7B7Nw4eFP/khoSEn1/WDwZ6LVp2+vXr99NPP50/f/6DDz4ossve3r5grUx7e/uCl0UWu7W1tbW3f8fe3kRYkK8yd9KXLMGePfD2xnvvGf0d+ZLhElYpzp8/P2bMmJycnCZNmghLOAiL8gmkpaWVsUu0tdUolfk/m5jAzi5/Ndsii9sW/BMW0rSxyX/ZsGH+e+vVg48PAgKwdClKqJjDMT4JDXRotCycP39emNk0ZMiQn376qfiyvgXL2QpmFrwsstitSpWhUslSUpCeDpUKWVlITUXJS98WRSZDbu6Ll7NmYccOrFqF4cMN4zlB8TE6CYWe0BBHZUrnlQYCqF69evXCy8qWjdxcKJX5q9kWWdy2YOXMtLQXLzWal2bHW1lh3Tr0749Jk3DiRGV+xSqLkUpYxXrCc+fO9enTp3QDK4yZGWrUQAWWvi2gXz8MGIB9+xASgtdf112yqoJxjY4qFIrExMRq1arVq1ePdRadUWDgZ599pnMDdcXatbC2xuzZyMxkHUV6GJeEt27dAuDi4qJ1iD8hIWHIkCHXr18XPVfFKWzgrl27pGkggPr1MW8eHjzA2rWso0gP45Kw9FGZVatW7d69u23btkOGDBF0lTjnzp0TvgdK3ECBmTPh4sLvGWrBuCQsfVRm7ty5Pj4+FhYWu3fvbtWq1ZAhQ4Rna6SJYKBSqTQIAwGYm2PTJsktOiAJWE/jEJV+/foB+P3330tpk5iY6OPjY2lpCUAul3t4eNy+fVu0hGXkzJkzwjRf4WFR1nG00K4dmZtr2T50qLQWZpUCxiVho0aNAJRU07owDx488Pb2trCwAGBmZubp6RkjmRUSpG8gEaWlkdbK4NnZlJKifZfRYkQSZmZmmpiYmJmZZWdnl/Et9+/f9/LyEq70zMzMvLy8mNePKGxgngGWjI+Lo379qF8/1jmkhLFIGBsbO2LEiFq1allYWAQGBmZmZpb9vbdv3x4xYoRcLgdgaWk5a9Z8VmXNDN1AIkpOJltbAuj8edZRJEPVl/DOnTuenp4mJiYAzM3NhW/C9erVCw4OzsnJKftxbt26JRzH3X2/tTV5e1NCgv5SayE09KJQ+1BYsEnUc+uUefMIoF69WOeQDFVZwnv37hW+mPT09Lx79+7Ro0fbt28vqOjs7BwcHFyur1Xh4eGenpkyGQFka0vz5on09SY0lF5/Xe3qOurzzz830D6wgNRUcnAggE6dYh1FGlRNCUsfVtFoNPv372/Tpo2gYoMGDYKDg8v1l339Onl4kKCijQ35+JBe1+o8dYpsbAigiROzDboPLCAggAB6/33WOaRBVZOw7DcY1Gp1SEhI8+bNBRVbtGixY8eOcql44QL1708AAVSjBgUEUFqajn6NQoSG5n+J+uILqhICEhEpFFSjBgF04gTrKBKg6kj49OlTHx8fKyurAv1KWmu6MIKKTZs2FVR0c3MLCQnRaDRlP+/Zs/T++/kqOjpSYKAuawqHhub3gVXJQIFFiwigrl1Z5yiZHTt27Ny5s/j2rKyszZs379Pd+rJVQcKkpCQfHx9ra2tBv/79+1+7dq1cR8jJydmxY0fj58s0t2rVqrwqhoZSjx75KtaqRYGBOlhfoQobSERKJdWqRQD98w/rKCVgb2/v6OhYfHtSUhKATp066epEhi1hcnJyQECAnZ0dAJlM1r9//ytXrlT4aDk5OcHBwa8/n2zTqVOn/fv3l+sIf/2VX90dIC+vCgchquoGCixbRgC9/TbrHCXAJXwF6enpgYGB9vb2gjA9e/a8fPmyTo6cnZ0dHBzs5OQkHPntt9/+pzyf1RoN7d1L7dpRRETFM5w+nW/gmDFV1kAiUqmodm0C6PBh1lG0wSUsEUE/oSa8oF9Ja4ZVBpVKtWLFCkdHR+EsXl7nz57V+Um0YyQGCqxaRQB16EDlufYXCS6hFpRKZWBgYEGBhq5du57S850mlUoVGBjYuHGnatU0APXsSRcv6vWExmUgEWVmUt26BND//sc6SjFEk1BGJZSRlRQZGRlbt25dvnx5YmIigK5duy5evPjdd98V5+wKheabb+RBQUhPh0yGjz7CwoV4fpdRl4SGom9fqFQYMwZbtkBuHPPMgoIwfTratcPly9Ka6OTg4JCdnT1u3Lgi27OysrZu3dqpU6cLFy7o5ky6sllPZGRkBAUF1alTR0jbtWvXcn1D0yH//UcBAWRnRwDJZNS/P1ViDEgLxtYHFpCZSW+8QQD9+SfrKC8jjDiYaQNGcjkqDJDUrVtX0K9Lly7lHavUB0lJ5OND1tYEkFxOHh4UGamDwxqtgQLffksAtWwprd/dqL8TCvpV5laBvnn6lHx8yMrqhYqVmfdb8FTa2LHS+isUjexsatCAANq9m3UUIiISHpyqIhImJSXdv39f6xPS8fHx9+/fL7JRuGkuTL1FhW6ai8nDh+TtTZaWBJCZGXl6UgXm/V69mt+vjh8vxRFC0di4kQByc2P8MRQbG+vl5TVgwACqMhL2798fQKS2Kzah0EvBZCJBvyZNmgj6tWzZUsr6Feb+ffLyIlPTFyrGxr7Y+8svBJCpKRV/hufttwkghYKGDzfePrAAoTNs2TJ9z54zTALExMSMGjVKmPJmYWHx4MEDI5KwyNObrq6uO3bsMLi5AnFxL1Q0NycvL3r8mOi5hAB161a0oxMkVCopN9eo+8ACdu48BsDFxUXkuVpF6icIU97IeHrCp0+fNmvWTNCvRYsWv/zyi8HpV5jISBo6lORyAsjamhYvzpewXj0CaNu2lxoXSMgRyMvLE/4YtD42rQ+KT3m7c+dOwV5jkTAnJ6dXr14VmNEnZW7eJE9Pkstp2bJ8CZcuJScnqlmTkpJeNOMSFmf79u0AmjRpou8CVmWZ8nbo0KEjR44Uf292dvb+/ftDQ0N1FYa9hImJiZItGVYZrlwhpTJfwm++oe3b85/GLoBLWJy8vDzhD+OHH37Q0ykqNuVNr4hRMfbkyZMxMTFFNqpUKuGH2rVri5BBfNq2fenlyJHYuBHbt2PUKLi7M8okeUxMTPz8/EaMGLFw4cJhw4YV1ATSCcnJyatXr/7222+fPXsmzLlZvHhxG308+lRe9Kq40BOWQrlKLRkiBT0hEYWFkYkJNWtGWVlEvCcsAbVa3apVKwCbN2/W1TGLT3kLCwvT1cErjxg94Y4dO4qvgjR69OgHDx6IcHbp0K4dJk7Ed98hKAg+PqzTSBW5XD5v3ryhQ4cuWbJk5MiRwqhJhVEqlRs2bFi+fLmwRHHPnj0DAwMLKn1JBb0qXvb7hFWVwj0hEaWlkZMT2dhQfDzvCUtEo9G8+eabADZs2FDhgwhzbvQ95U0nGMeD+pLBzg4rVkClgr8/6ygSRiaT+fv7A1iyZElm+Rc0FOaC1q9f39fXV6FQdO3a9eTJk0ePHn3rrbf0EFYHcAnFZsQIuLtj+3bExrKOImEGDRrUpk2b+Pj4rVu3lv1dGRkZa9eubdKkia+vb0pKSteuXY8fP37mzBl3aQ+FcQnFRibDhg2Qy/HkCesoEkYmky1YsADA8uXLnz179sr22dnZmzdvbtq06bRp0xITE4WiJGfOnBFt0mll4BIywNUV06axDiF5BgwY0LFjx4SEhODg4FKa5eTkbN68uVGjRhMmTEhISOjcufP+/fvPnj37/vvvixa1kuh3dLR///7169cvKEhRmOHDhz958kR4XrYK4+wMDw88fzLvBfPnIz4eOTmQ/NqeLJk/f37//v2XL18+fvx4YR2OwuTk5Gzfvn3RokWPHz8G0Lp1az8/Pw8PDxZJKwfrkSEOpzQ6d+4MYOXKlYU3GtaUt1fCJeRImsOHDwNwdHRMT0+n5xXTC6a8VaBiugQxjEJPHGPG3d399OnTS5cubdq0qZ+f3+3btwG4urr6+PgMHz68Cnyj4RJypM6xY8d69uxpYmKiVqsBNG/efP78+UOHDpVXlXJ0fFiAI12I6MCBA/PnzwdgaWlpZma2YsWKMWPGmFat4SzeE3KkCBHt3bt3wYIF169fB+Dk5JSQkGBvbx8XF6d1sN2gqSIdOqcq8c8//3Ts2HHQoEHXr1+vV69eUFBQXFzc+++/n5aWtnbtWtbp9ADTYSEO5yWOHj3asWNH4S+zdu3agYGBmZmZwq5z584BsLOz+++//9iG1DlcQo4kCA0NLXjCs1atWoGBgc+KrfDYu3dvAHPnzmWSUH9wCTmMCQ0Nfe+99wT9HB0dAwMDM0pY6/jy5csymaxatWqJiYkih9QrXEIOM86ePVtQe6FmzZoBAQFpaWmlv0VoP3v2bHESigOXkMOA8+fPF+hna2vr4+OjUCjK8sawsDChM3zy5Im+Q4oGl5AjKuHh4R4eHjKZrEC/1NTUch1h4MCBAGbMmKGfgAzgEnJE4saNGwX62djY+Pj4pKSkVOw4crnc0tLy0aNHOg/JBC4hR+9EREQU6FetWjVvb+9KXkwOHjwYgLe3t64SsoVLyNEjt27d8vT0FJ6xtra29vb2TkhIqPxhIyIi5HK5hYXFw4cPK3805nAJOXpBWGNM0M/c3NzLy+uxsESOjhg6dCiAyZMn6/CYrOAScnRMXFxcwSJHgn76+PIWHR1tampqZmYWW3glOsOES8jRGSWtMaYnRowYAcDLy0t/pxAHLiFHC48fP54yZcrWrVuL7woPD58yZcrevXsLbyx9jTE9cefOHaEz1KvqIsAl5GghPDwcwCeffFJ81x9//AFg1qxZwsuyrDGmP7744gsAXxRe7MoA4VOZOBUkKSnJ19e3QYMGK1asyMnJ8fDwuHXrVuFFl0UgICDA3Nz8xx9/jI6OFu2kOodLyKkg27ZtW7FiRXZ29meffXbjxo2QkJDmzZuLnKF+/fqjRo1Sq9VLly4V+dQ6hEvIqSBTpkwZNWrUtWvXfv31V1dXV1Yx/Pz8LCwsfv7558jISFYZKgmXkFNBbGxstm/fLqwlyBBnZ+cxY8ao1erFixezTVJhqlTBHI5uCQ0N7dGjR5GNycnJLLKUhp+f3/bt23/77TdfX9/WrVuzjlNueE/IKZG8vDxVMbKysljnKkrdunXHjRun0WiWLFnCOkuFYD08y5EiZb9FIRHi4+Otra1lMtm1a9dYZyk3vCfkVAWcnJwmTJhARAsXLmSdpdxwCTlVhDlz5tjY2Ozdu/fSpUuss5QPLiGnilCrVq1JkyYRkcENk3IJOVUHHx8fW1vb//3vfxcvXmSdpRxwCTlVh5o1a06dOhWAsNS2ocDXouBoITc39/Hjx9WqVatVq1aRXc+ePXv69Km9vb0014RQKBQNGzZUKBSnT5/u3r076zhlgveEHC2YmZk1aNCguIEArK2tGzRoIE0DATg4OHh7ewNYtGgR6yxlhfeEnKpGWlpaw4YNU1NTT548WVBaX8rwnpBT1bC3t582bRoAPz8/1lnKBO8JOVUQlUrVqFGjpKSkY8eOFSx0IVl4T8ipgtjY2Aidob+/P+ssr4bPouBUTby9vcPCwmbMmME6yKvhPSGnakJEAwcOzM7OLr4rPj5+586d0nm6jUvIqZo8efJk5MiRq1evLr4rPDx85MiRO3fuFD+VVriEHA5juIQcDmO4hBwOY7iEHA5j+C0KTlUmKipq1qxZRTbGxcUxCVMSXEJOVSYuLk7rAKmk4JejnKpMnz591MU4ePAg61wvwXtCThVHLi/a0wgLd0sH3hNyOIzhEnI4jOEScjiM4RJyOIzhAzOcqomTk1NISIiTk1PxXW3bthV5MdPS4TPrORzG8MtRDocxXEIOhzFcQg6HMVxCDocxXEIOhzFcQg6HMVxCDocxXEIOhzFcQg6HMVxCDocxXEIOhzFcQg6HMVxCDocxXEIOhzFcQg6HMVxCDocx/w9i6ySXVkE+vAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300 at 0x7FF6123E4BE0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol.hydrogens('add')\n",
    "mol.visualize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=300x300 at 0x7FF6123E4F70>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol.hydrogens('remove') # just for the sake of visualization: to fit the text inside the box\n",
    "mol.visualize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convert chemical formats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<chemml.chem.Molecule(\n",
       "        rdkit_molecule : <rdkit.Chem.rdchem.Mol object at 0x7ff6123e29a0>,\n",
       "        pybel_molecule : None,\n",
       "        creator        : ('InChi', 'InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3'),\n",
       "        smiles         : 'CN1C(=O)C2=C(N=CN2C)N(C)C1=O',\n",
       "        smarts         : '[#6H3]-[#7]1:[#6H]:[#7]:[#6]2:[#6]:1:[#6](:[#7](-[#6H3]):[#6](:[#7]:2-[#6H3])=[#8])=[#8]',\n",
       "        inchi          : 'InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3',\n",
       "        xyz            : None)>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol.to_smiles(kekuleSmiles=True) # although I already had it: just to make sure I have kekulized SMILES\n",
    "mol.to_smarts(isomericSmiles=False)\n",
    "mol.to_inchi()\n",
    "mol"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optimize XYZ geometry\n",
    "\n",
    "You can optimize a molecule’s structure using force fields via to_xyz method. If the 3D info is not available you should specify a force field as an optimizer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<chemml.chem.Molecule(\n",
       "        rdkit_molecule : <rdkit.Chem.rdchem.Mol object at 0x7ff6123f9880>,\n",
       "        pybel_molecule : None,\n",
       "        creator        : ('InChi', 'InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3'),\n",
       "        smiles         : 'CN1C(=O)C2=C(N=CN2C)N(C)C1=O',\n",
       "        smarts         : '[#6H3]-[#7]1:[#6H]:[#7]:[#6]2:[#6]:1:[#6](:[#7](-[#6H3]):[#6](:[#7]:2-[#6H3])=[#8])=[#8]',\n",
       "        inchi          : 'InChI=1S/C8H10N4O2/c1-10-4-9-6-5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3',\n",
       "        xyz            : <XYZ(geometry: (24, 3), atomic_numbers: (24, 1), atomic_symbols: (24, 1))>)>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol.hydrogens('add')\n",
    "mol.to_xyz(optimizer='MMFF', mmffVariant='MMFF94s', maxIters=300) # 'UFF'\n",
    "mol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-2.36692757, -2.28335772,  0.53992304],\n",
       "       [ 0.32204937,  2.74601445, -1.37302266],\n",
       "       [ 2.90718619, -0.57551206,  1.14052643],\n",
       "       [-2.64477579, -0.11928699, -0.69453293],\n",
       "       [-0.63353949, -0.52418726,  0.09809813],\n",
       "       [-0.68417929,  0.67033406, -0.55384519],\n",
       "       [ 0.54691374, -1.030122  ,  0.70648171],\n",
       "       [ 1.6282777 ,  1.0716059 , -0.10505256],\n",
       "       [-1.92702632,  0.92861735, -1.04796252],\n",
       "       [-1.89831872, -1.03005027,  0.00546184],\n",
       "       [ 0.41948147,  1.48015768, -0.66959671],\n",
       "       [ 1.64071624, -0.17160277,  0.56192208],\n",
       "       [ 0.58191842, -2.10836174,  1.29188919],\n",
       "       [ 2.64977785,  1.76115728, -0.18017807],\n",
       "       [-1.79046003, -3.09291043,  0.0854339 ],\n",
       "       [-3.42660851, -2.40755161,  0.30241858],\n",
       "       [-2.23159667, -2.27174952,  1.62426683],\n",
       "       [ 0.0140735 ,  2.55773804, -2.40642947],\n",
       "       [-0.42450498,  3.37408335, -0.87662244],\n",
       "       [ 1.27541304,  3.2806427 , -1.38499594],\n",
       "       [ 3.22486349,  0.1822382 ,  1.8644061 ],\n",
       "       [ 3.65989367, -0.62754458,  0.3469081 ],\n",
       "       [ 2.85172564, -1.54480199,  1.64186973],\n",
       "       [-3.69435292, -0.26555006, -0.91736714]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol.xyz.geometry"
   ]
  }
 ],
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