{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rdkit import Chem\n",
    "from rdkit.Chem import Draw\n",
    "from rdkit.Chem import rdMolTransforms\n",
    "from rdkit.Chem import rdMolAlign\n",
    "from rdkit.Chem import AllChem\n",
    "from rdkit.Chem.Draw import IPythonConsole\n",
    "import numpy as np\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaf = Chem.MolFromSmiles('c1cc(C)ccc1')\n",
    "AllChem.Compute2DCoords(scaf)\n",
    "scaf\n",
    "tm = np.zeros((4,4), np.double)\n",
    "for i in range(3):\n",
    "    tm[i,i] = 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "rdMolTransforms.TransformConformer(scaf.GetConformer(), tm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x11cec88f0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "writer = Chem.SDWriter('scaf.sdf')\n",
    "writer.write(scaf)\n",
    "writer.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "mol = Chem.MolFromSmiles('Nc1ccc(C)cc1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcIAAACWCAIAAADCEh9HAAAABmJLR0QA/wD/AP+gvaeTAAAZqElEQVR4nO3daVgUV9YH8IOiogIGNKJGElHoZlGJbIqARgQkiwsqETUujAajUbsbWmTRIO57JDrGGTeeaOJEE6OOGU1c0VEwiTAqgjSKCyrLAD3QQNNb1fuhHDJZ3pnuhurbVXV+Dx+wH4/+weRw6tbtWzY0TQNCCCFzdSAdACGEuA3bKEIItQm2UYQQahNsowgh1Ca2pAMgq6NQKNRqNekUltCpUydvb2/SKRDnYRtFP6MoauvWrdnZ2cXFxaSzWIKLi4tMJpPJZJ07dyadBXGYDW54Qq2ys7Pj4+N79Ojx2muvkc5iCeXl5UqlcsuWLXK5nHQWxGHYRtELKpVKLBZXVFQcPnx45syZpONYwvnz5yMjIx0cHEpKSvr27Us6DuIqvMWEXli3bl1FRUVwcPCMGTNIZ7GQiIiId955R6VSffTRR6SzIA7DaRQBAJSVlfn4+Gg0mry8vKCgINJxLOfBgwc+Pj46ne7GjRsBAQGk4yBOwmkUAQAkJSW1tLTMmTNHUD0UAAYNGrR48WKKoiQSCY4UyDw4jSK4ePHi2LFj7e3tS0pK+vXrRzqOpalUKpFIVFlZ+Ze//GXatGmk4yDuwWlU6AwGg1QqBYD09HQB9lAAcHBwWL16NQDI5fKmpibScRD3YBsVuj179ty5c2fgwIFMMxWmefPmBQQEPH36dNu2baSzIO7Bi3pBUyqVIpGopqbmm2++mTRpEuk4JF2/fj00NNTOzq64uFgg22ZRe8FpVNAyMjJqamrCw8MF3kMBYOTIkbGxsWq1Oi0tjXQWxDE4jQpXcXGxr68vRVH5+flDhw4lHYe88vJyT09PtVqdk5MTFhZGOg7iDJxGhUsmk+l0ug8++AB7KMPV1VUul9M0LZFIKIoiHQdxBk6jAnXy5MlJkyY5OTkpFIpevXqRjmMt1Gq1l5fX48eP9+/f/4c//IF0HMQNOI0KkVarTU5OBoDMzEzsof+pa9eu69evB4DU1NT6+nrScRA34DQqRJs3b16+fLmXl9etW7c6depkajlN01lZWWwEa18JCQndunUztYqm6dGjR1+9enX58uUbN25kIxjiGWyjglNdXS0Sierr68+cORMdHW3Gn6DX681ovpZXUVHRp08fMwrz8/MDAwNtbW3v3LkjEonaPRjiGTy2WXCYy9UJEyaY10MBoEOHDhKJpH1TsaF79+7mFfr5+c2ZM+fgwYPJycknTpxo31SIf3AaFZaCgoKAgACcs/6nqqoqsVhcX19/9uzZcePGkY6DrBreYhIWZiuPVCrFHvrfubi4pKamwr+3hZGOg6waTqMCcuTIkRkzZvTu3VuhUPTo0YN0HGun1WoHDx5cWlq6c+fOxYsXk46DrBe2UaFo3RG5b9++efPmkY7DDSdOnIiJicHdtei/w4t6odi0adPjx4+HDRsWHx9POgtnTJo0ady4cUqlMjMzk3QWZL1wGhWEp0+fenp6NjU15eTkjBo1inQcLikqKnr99dcpiiooKBgyZAjpOMga4TQqCMyBxNOnT8ceaipvb+8FCxa0Hm6N0G/hNMp/eJJmGymVSg8Pj9ra2hMnTkycOJF0HGR1cBrlOWZ7E03TycnJ2EPN4+TklJGRAQCJiYkajYZ0HGR1sI3y3IEDB3788cf+/fsvW7aMdBYOW7Ro0ZAhQ8rKynbs2EE6C7I6eFHPZyqVSiwWV1RUHDlyJC4ujnQcbmOen+rg4FBSUtK3b1/ScZAVwWmUz1avXl1RUTFy5Eh8bnDbhYeHT5w4UaVSpaenk86CrAtOo7z14MEDHx8fnU6Xl5cXGBhIOg4flJWVeXt763S63NzcoKAg0nGQtcBplLdkMplGo4mPj8ce2l4GDhzYeigBzh+oFU6j/HThwoWIiAhcyGt3rcvNn3/++YwZM0jHQVYBp1Ee0uv1zF7xlStXYg9tXw4ODmvXrgWA5OTkpqYm0nGQVcA2ykO7d+8uLCwcNGjQ0qVLSWfhoblz5wYFBT179mzz5s2ksyCrgBf1fFNXVycSiWpra0+dOjV+/HjScfgpNzc3JCTEzs6uqKhowIABpOMgwnAa5ZuVK1fW1taOHTsWeyh7goOD4+Li1Gp1SkoK6SyIPJxGeaWoqMjX1xcA8vPz8TgiVrUemnX58uXRo0eTjoNIwmmUV2QymV6vZ965SDoLz7W+v1YqlRoMBtJxEEk4jfLH8ePHp0yZ4uzsrFAoevbsSToO/6nVam9v70ePHv35z39+//33ScdBxOA0yhNarZZZp1uzZg32UMvo2rXrxo0bAWDFihX19fWk4yBisI3yxLZt20pLS729vRMSEkhnEZBp06aNGjWqurqa2UyKhAkv6vmgqqpKJBI1NDR89913UVFRpOMIS0FBQWBgYMeOHW/fvi0Wi0nHQQTgNMoHy5cvb2hoiImJwR5qecxTArVarVwuJ50FkYHTKOfdvHkzKCjI1ta2sLDQw8ODdBwhqq6uFolE9fX1f/vb3958803ScZCl4TTKbTRNS6VSiqKSkpKwh5LSu3fvFStWAEBiYqJOpyMdB1kaTqPcdvjw4VmzZrm4uCgUCkdHR9JxhEur1Q4ZMkShUOzYsUMikZCOgywK2yiHNTc3e3l5PXny5ODBg3PnziUdR+j++te/TpgwwcnJSaFQ9OrVi3QcZDl4Uc9hGzZsePLkiZ+f3+zZs0lnQTB+/Pjo6GilUvnRRx+RzoIsCqdRriovL/f09FSr1VeuXAkNDSUdBwEAFBcX+/r6UhR18+ZN5nADJAQ4jXJVYmJic3PzzJkzsYdaDy8vr0WLFhkMBplMRjoLshycRjnp2rVrYWFhdnZ29+7de/XVV0nHQT9TKpUikaimpubrr7+ePHky6TjIEnAa5R6KoiQSCU3Tqamp2EOtjZOTU2ZmJgDI5fKWlhbScZAlYBvlnr179968edPV1TUpKYl0FvQ7FixYMHTo0IcPH27fvp10FmQJeFHPMQ0NDWKxuLKy8ujRo7GxsaTjoN936dKl8PBwe3v7kpKSfv36kY6D2IXTKMesWrWqsrIyJCRk6tSppLOg/9eYMWMmT57c2NiYmppKOgtiHU6jXHL//v3BgwfrdLoffvjB39+fdBz03zx8+NDb21uj0eTm5g4fPpx0HMQinEa5RCKRaDSa+fPnYw+1fm5ubjKZjDn0AIcVfsNplDPOnTsXFRXl6OhYUlLSp08f0nHQ/9bY2CgWi58/f/7ZZ5/NmjWLdBzEFpxGuUGv1zM7ujMyMrCHcoW9vf369esBIDk5uaGhgXQcxBZso9ywc+fOu3fvuru7f/jhh6SzIBPMnj17+PDhlZWVmzdvJp0FsQUv6jmgrq7Ow8Ojrq7u22+/feutt0jHQabJy8sbOXJk586dCwsL3d3dScdB7Q+nUQ5IS0urq6uLiIjAHspFI0aMmDlzpkajwc1PfIXTqLW7deuWv7+/jY3NP/7xDx8fH9JxkDmePXvm6enZ2Nj4/fffR0ZGko6D2hlOo9ZOKpUaDIYlS5ZgD+WuV155Zfny5QAgk8n0ej3pOO3jpZfAxgYuXvzFiyNGQFjYi8/79oXf/sjw8QH+7dbDNmrVvvrqq8uXLzs7OzOP+kHcJZfL3dzc7t69u3//ftJZ2gdzHbtoEWi1v3ix9fqWpoGifl1FUcC/C2Bso9arpaUlOTkZANavX+/s7Ew6DmoTOzs75mY9s9JNOk67KSmBTZtIhyAN26j12rp168OHD318fObNm0c6C2oHU6dOfeONN+rq6tauXUs6S/uYPh08PWH9enjw4OcX+Tds/k+2pAOYrFevXrW1taRTWEL37t0BYOfOnba23PtnQr9rx44dfn5+e/fu/fjjj9n7W4KD43Jzj7D35wNAUxMAQJcusHcvjBoFixfDmTO/89tqauD06V+8olJB166sRiMA//9ECJkvNBQWLoTdu+HYMfjtwY23b8P48b9+sXdvy0SzHO5d1NfU1NDCwGwzXLJkiXn3drX/ufKP2pVOp6PNunaVSCQURSUkJLD6X87160eYWz3sfXTr9vMXtXEjuLqCVAoq1a+/3pEjobz8Fx+DBrXh+26tuNdGhUMul7u7u9+9e3ffvn0mFZaWlkZFRUkkEpaCodWrV4eGht6+fdukqmPHjuXk5Lz88ssrV65kKRgRDg7w6afw/Dn89suys4P+/X/x0akTiYgswzZqvbp06bJx40YASE9PN2k5WK/XX758ee/evbdu3WItnXCVl5dv3749NzfXpNNGWvddrF279qWXXmItHRlvvw3Tp8OuXVBURDoKCdhGrdqUKVMiIyNNvbeLj/lllXmPtt6yZcujR498fX35uu8iKwteegkaG0nnIILVNRrUdoWFhba2tra2tnfu3DG+qq6urlevXgDw1VdfsZdNgK5evWpjY9OtW7fHjx8bX/X06VNm38WlS5dYi2ZpPXrQ8fG/eOXQIRqADgl58cs+feixY39d5eVF+/m9+HzdOrpfP/rll2mJhK6oYDkum7CNcsAHH3wAABERESZV7d69GwDc3NzUajVLwYTGYDAwzx1Ys2aNSYUzZ84EgNjYWJaCcdH163T37vTOnfSdO7S/P52cTDpQG2Ab5YDa2tqePXsCwOnTp42v0uv1Q4cOBYB169axl01Q9uzZAwCurq5NTU3GV+Xm5trY2NjZ2T18+JC1aNzz6ad0XNyLzzMy6OBgomnaBtsoNzC7td3d3VtaWoyvunjxIgDY29s/e/aMvWwCUV9fzzx34OjRo8ZXURQVFBQEACtWrGAvG6cpFPSAAfQnn5DO0QbYRrlBp9MxJzxt3brVpMLJkycDwOzZs1kKJhzM/bqQkBCKooyvOnjwIAC88sorKpWKvWwcZTDQ69bRDg50YiJtynhgdbCNcsa5c+cAwMHBocKU1fiysjI7OzsbG5u8vDz2svFeaWlp586dO3To8NNPPxlfpVKp+vXrBwCHDh1iLxtH6XT09Om0vz9tynfUSmEb5ZK3334bAN5//32TqtLS0gDA39/fYDCwFIz33nzzTQBYsGCBSVUpKSkAMGLECJMGWIHYv5/u359+/pxWKmmlkub0sI5tlEtKS0u7dOnSoUOHH3/80fiq1pnos88+Yy8bj33//fcA4OjoaNJ1wIMHD5jrgBs3brCXjbvi42mAnz98fUkHagNsoxyTmJhoxgpddnY2APTp06e+vp69bLyk1WrFYjEAbNu2zaTCmJgYAJgzZw47uZAVwTbKMa33i7/88kvjqyiKGj58OACkp6ezl42Xtm3bZsYeiQsXLuAeCeHANso9f/rTn8zevdilS5fS0lL2svFMdXU18/73b7/91viq1h2769evZy8bsh7YRrnHYDAEBAQAQGZmpkmFs2bNAoApU6awFIx/EhISACAyMtKkql27dgHAwIED8f1jAoEPWOaka9euhYWF2dnZ3bt379VXXzWyCh/zaxLzHm2tVCpFIlFNTc3x48eZ5VHEe3jCEyeFhIRMnTpVrVYzm5mMxMvH/LLHvEdbr1q1qqamZsyYMdhDBYT0OIzM9OTJk27dutnY2Fy5csX4KrVa7ebmBgCffvope9l44OjRowDg7OxcW1trfFVRUVGnTp06dux469Yt9rIha4NtlMOYQ9T9/PxM2ld/7NgxpkEI53EsplKr1QMGDACAPXv2mFQYHR0NAIsWLWIpGLJO2EY5rLm5mVkYPXDggEmFzMKoVCplKRjXrVmzBgB8fHyYZy4Z6eTJkwDg5OT0z3/+k71syAphG+W2w4cPA4CLi4tJ++pbj4IuLCxkLxtHPX361N7eHkw8Ylmj0YhEIgDIyspiLRqyUniLidtmzJgRGhpaVVW1YcMG46t8fHzmzZun1+ulUil72TgqJSWlsbFx6tSpb7zxhvFVWVlZCoXCy8tr4cKFrEVDVgo3PHFefn5+YGAgM1p6eHgYWVVXV+fh4VFXV3f69GnmxBMEAHl5eSNHjuzSpUtRURFzL84Y1dXVIpGovr7+zJkzzPIoEhScRjnPz89v9uzZWq2WefCkkZydnVesWAEAUqlUo9Gwlo5LaJqWSCQ0TcvlcuN7KACkpaXV19ePHz8ee6hAEV5UQO2hsrLS0dERAM6ePWt8VetR0KYeusFXzAEuph6xnJ+f36FDh86dO5eUlLCXDVkzbKM8wayNent7m3RzmTkK2tQj4HjJ7COWR40aBQDLli1jKRiyfthGeUKj0TALo7t27TKp8K233gKAhIQEloJxRWpqKph+xPKRI0cAoHfv3v/617/Yy4asHLZR/jh+/DgAODk5mbSv3ryjoHmm9Yhlkx610tzc/NprrwHA3r172cuGrB/eYuKPmJiYqKgopVKZmZlpfJW7u/uHH35IURSzG5+9eNZMLpe3tLTMnj2bOZXVSJs2bXr8+PGwYcPi4+PZy4asH2544pWioiJfX1+apgsKCoYMGWJkVUNDg1gsrqysPHr0aGxsLKsJrdClS5fCw8Pt7e1LSkqY5VFjPH361NPTs6mpKScnh1keRYKF0yiveHt7L1iwwGAwmLSv3tHRkRlgk5KSmpubWUtnjVq/V2lpacb3UABYtmxZU1NTXFwc9lCEa6N8U1dX17NnTwA4efKk8VUGg8Hf3x8AVq9ezV42K/THP/4RANzc3Ew6Yvn69es2NjZdu3Z99OgRe9kQV2Ab5aFPPvkEAAYNGmTS44P+/ve/M63h8ePH7GWzKnV1db169QKAr7/+2vgqg8EQGBgIABkZGaxFQ1yCbZSHdDodszC6adMmkwqZhdGZM2eyFMzaLF26FADGjBljUtW+ffsAoH///o2NjSwFQ9yCt5j46cKFCxEREQ4ODiUlJX379jWyqry83NPTU61WX7lyJTQ0lNWExBUXF/v6+lIUlZ+fzzyBzhgqlUosFldUVHzxxRfTp09nNSHiCrzFxE9jx46dMGGCSqVi3jhvJFdX18TERJqmJRIJRVHsxbMGiYmJOp0uISHB+B4KAGvWrKmoqAgODo6Li2MvG+IY0uMwYsv9+/eZffU//PCD8VVNTU3MUdAHDx5kLRp5p06dAtOPWDbvW4p4D6dR3ho0aNDSpUspimJOLTKyqlu3buvWrQOAlJSUhoYGNgMSo9Vq5XI5AGRkZDC3mIyUmJio0Wjmzp3L3GJC6AXSfRyxqKGhgVkY/eKLL4yvoiiKWRhNSUlhLxtBmzdvBgAvLy+tVmt81fnz5wHAwcHh+fPn7GVDXIRtlOfMu6188+ZN5vA3hULBXjYiqqqqevToAQBnzpwxvsrszQ9ICLCN8pzZmxznzJkDADExMezkImb+/PkA8M4775hUlZWVBaZvxUUCgRue+C83NzckJMTOzq64uJg5kcgYVVVVIpGooaHhu+++i4qKYjWhxRQUFAQGBnbs2PH27dtisdjIKqVS6eHhUVtbe/LkyQkTJrCaEHER3mLiv+Dg4GnTpqnV6pSUFOOrXFxcmN8vk8n0ej1r6SxKKpUaDIalS5ca30MBYOXKlbW1teHh4dhD0e8jPQ4jSygvL+/evTsA5OTkGF9l9lHQ1sm8I5bv3r1ra2vLDLDsZUOchm1UKDIyMgBg2LBher3e+CrzjoK2QmYfscwsaCxZsoSlYIgHsI0KRRv7yNKlS1kKZhmrVq0CgNdff12YP0UQq7CNCkhbrmptbW25e1XbuqZx+fJl46t4tqaB2IO3mASEOWO4urqaeZ+Skby9vRMSEvR6PdOFuejo0aNNTU3vvvvu6NGjja/avn17aWkpcxI2e9kQD+CGJ2EpKCgICAiwtbW9c+eOSCQysqq2tvbq1auTJk1iNRurzp07JxKJzNjvdfbs2XHjxrGaDXEdtlHBmT9//v79+8ePH88cz4F+V3x8fHZ29qRJk7755hvSWZC1wzYqONXV1SKRqL6+/syZM9HR0aTjWKP8/PzAwEBbW9vCwkJmeRSh/wLXRgWnd+/e6enp8O8DN0nHsTr0v49bTUxMxB6KjIHTqBBptdohQ4YoFIqsrCzmQRqo1eeff/7ee++5uLgoFApHR0fScRAHYBsVqFOnTk2cONHJyUmhUJh05ia/qdVqT0/PJ0+eHDhwID4+nnQcxA14US9QEyZMiI6OViqVzLubEGPDhg1Pnjzx8/NjDrhCyBg4jQqXec9047HWJ/rl5OSEhYWRjoM4A6dR4fLy8lq4cKHBYJBKpaSzWIWkpKTm5uYZM2ZgD0UmwWlU0JRKpUgkqqmpOX78eExMDOk4JF27di0sLMzOzu7evXvMQ/0QMhJOo4Lm5OSUmZkJAHK5vKWlhXQcYiiKkkqlNE2npqZiD0WmwjYqdAsWLBg6dGhZWdnHH39MOgsx+/bt++mnn1xdXZOSkkhnQdyDF/UILl68OHbsWHt7+5KSkn79+pGOY2kNDQ1isbiysvLLL7989913ScdB3IPTKILw8PCYmJjGxsa0tDTSWQjIzMysrKwMCQmJjY0lnQVxEk6jCACgrKzMx8dHo9Hk5eUFBQWRjmM59+/fHzx4sE6nu3HjRkBAAOk4iJNwGkUAAAMHDmTusUgkEkH9ZJVKpRqNZt68edhDkdlwGkUvNDY2isXi58+fHzp06L333iMdxxLOnz8fGRnp4OCgUCj69OlDOg7iKmyj6GfZ2dnx8fE9evQw/nhjTisvL1cqlVu2bJHL5aSzIA7DNop+RlHU1q1bs7Ozi4uLSWexBBcXF5lMJpPJOnfuTDoL4jBso+jXFAqFWq0mncISOnXq5O3tTToF4jxsowgh1CZ4px4hhNoE2yhCCLUJtlGEEGoTbKMIIdQm/wd/V4vBxk2XmgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x119ffe990>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaf = Chem.SDMolSupplier('scaf.sdf')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x11d73d3a0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bondnormalize(mol, temp):\n",
    "    AllChem.Compute2DCoords(mol)\n",
    "    ref_bond = mol.GetBonds()[0]\n",
    "    ref_length = rdMolTransforms.GetBondLength(mol.GetConformer(), ref_bond.GetBeginAtomIdx(),ref_bond.GetEndAtomIdx() )\n",
    "    prob_bond = temp.GetBonds()[0]\n",
    "    prob_length = rdMolTransforms.GetBondLength(temp.GetConformer(), prob_bond.GetBeginAtomIdx(),prob_bond.GetEndAtomIdx() )\n",
    "    ratio = ref_length / prob_length\n",
    "    tm = np.zeros((4,4), np.double)\n",
    "    for i in range(3):\n",
    "        tm[i,i] = ratio\n",
    "    rdMolTransforms.TransformConformer(temp.GetConformer(), tm)\n",
    "    AllChem.GenerateDepictionMatching2DStructure(mol, temp)\n",
    "    return mol\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "cpmol = copy.deepcopy(mol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "AllChem.GenerateDepictionMatching2DStructure(cpmol, scaf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KCho4cGBKSsrRo0dJZ0Evyc/Pj4+PV1dXj4+PV1NTa/d7mPf1zDIsxCcso+hP+vr6ERERALBmzZrGxkbScdCf/Pz8mpubFy1a1MHzlvnz54tEojNnzlRXV/OZDWEZRS9hflEfP368detW0lnQC1euXDl9+nTrH7lXGTRo0KRJk6RSKfHOh6oGyyh6SettY3R0dEFBAek4CORyuVgshv89cun4mxcsWAB4X887LKOoLScnJ09PT4lEwrzTQGTt2bPn3r17Q4cO9fHxee03z5kzR09P7/r16/n5+TxkQwwso6gdW7du1dXVPX78ONPOEpHy9OlTpgtJbGystrb2a79fV1eX2Qhw5MgR7tOhF7CMonYYGxsHBgYCgFgslsvlpOOorpCQkKqqqsmTJ8+ePbuTP8Lc1yckJNC4JJwvuPwetU8ikVhbWxcUFOzbt2/p0qWk46iirKwsW1tbiqJu3brFND3oDIqiTE1NHz9+nJqaOnbsWE4TIgbORlH7evfuvXnzZgAIDg6ura0lHUcV+fr6trS0LFu2rPM1FADU1dXnzZsH+KKJRzgbRR1hTvvx9/ePiYkhnUW1nD59evbs2YqdlIUbQ3mGs1HUkfj4eJFItH379uzsbNJZVIhUKmWeTYeFhSlw2qCtra2NjU1NTc2vv/7KQTrUFpZR1BE7Oztvb++WlhamgRDiR1xcXE5OjpWV1bJlyxS7Am4M5RPe1KPXqKysNDc3r6ur++WXX6ZPn871cDExMSUlJVyPorAtW7ZoaWlxOkRFRYWFhUVdXd358+eZo1sVUFpaampqKhKJSktL33jjDXYToraINkZB3UN0dDQAWFpaSqVSrseys7Mj/TvRER6OXVq8eDEAzJo1S8nrTJ06FfDEUF7gbBS9nlQqtbGxyc7OjouLYzYmcufo0aOVlZWcDqGMFStWcPrS5tatW46OjhoaGvfu3TM3N1fmUocPH164cKGLi0tycjJb8VC7sIyiTjl79uzMmTP79u2bk5PDaXNiVUbT9IQJE5KTkwMDA7ds2aLk1RobGwcMGNDY2Jibmzt06FBWEqJ24Ssm1CkzZsyYPn16bW1tSEgI6Sw91rFjx5KTk42MjNavX6/81XBjKG9wNoo668GDBzY2NhRFpaen29rako7T00gkEisrq8LCwgMHDnh7e7NyzcTExGnTppmZmeXk5Lyq2TNSHs5GUWdZWlquWLFCLpf7+vqSztIDbd68ubCw0N7enjlqlBVubm7Gxsa5ubk3b95k65ror7CMoi4IDQ3t16/fb7/9ho2B2VVSUhIbGwsA27ZtU1dn7bcSN4byA8so6gIDA4Pw8HAAWL169fPnz0nH6TkCAgIaGxs9PT1dXV3ZvfKCBYtcXZfevu0llbJ7YfQnfDaKukYulzs4ONy5cyciIoKVNyHoxo0bLi4u2traWVlZb731FuvXt7WFu3fh1CmYNYv1ayMAnI2irhKJRHFxcQAQERFRXFxMOk63R1GUj48PTdNr1qzhooYCgJcXAADe1nMHyyjqskmTJrm7uzc1NQUHB5PO0u0dOHAgLS3NxMQkICCAoyHmzweRCH7+GfDAUI5gGUWKiImJ0dbWPnz48LVr10hn6cbq6+uZdbgxMTG6urocjTJoEEyeDFIp4HtBjmAZRYoYMmSIn58fTdNisZiiKNJxuqvw8PDy8nJnZ+e5c+dyOtCCBQB4X88ZfMWEFNTQ0GBhYVFaWpqQkMCc/4O6JC8vb/jw4S0tLampqaNHj+Z0rMZGGDAAGhshNxdwXyjrcDaKFKSnpxcVFQUAgYGBz549Ix2n+xGLxc3Nzd7e3lzXUADQ1YXZs4GmAfeFcgHLKFLcggULxo4dW15evnXrVtJZuplLly6dPXtWX1+fWYfLA+aGISEB8P6TdXhTj5SSmprq7OysqamZkZFhZmZGOk73IJPJ7O3tMzIyoqOjuXtB3wZFgakpPH4MqamAB4ayC2ejSCnjxo3z8vJqbm5eu3Yt6Szdxq5duzIyMoYNG7Zq1SreBlVXh3nzAPBFEwdwNoqU9fjxY0tLy4aGhsTERKbjOupATU2Nubl5dXX1mTNnZs6cyefQd+6AnR0YGkJpKXB8EopqwdkoUpaxsTEzFfX19ZXJZKTjCF1wcHB1dfWUKVN4rqEAYGsLNjZQUwPnz/M8cg+HZRSxICAgwMzMLDMz85tvviGdRdAyMzP379+voaERHx9PJABuDOUCllHEAi0tLWbxU1BQUDVuOXw1ZsK+cuXKESNGEAmAG0O5gGUUscPDw2Pq1Kk1NTWbNm0inUWgTp48efHiRUNDww0bNpDKgBtDuYBlFLEmLi5OQ0Nj586dmZmZpLMIjlQqZZ4gb9q0iezB8bgxlHVYRhFrhg8fvmTJEplMxvUhzN1RTEzMw4cPra2tly5dSjaJuzvo6cH165CfTzZIz4FlFLEpMjLS0NDw0qVL586dI51FQCoqKpgDk5kJO9kwuDGUdVhGEZsMDQ2ZJqTMhnHScYSCaTvg7u7+zjvvkM4CgBtD2YbL7xHLZDKZnZ1dZmZmTEyMv78/6TjkpaenjxkzRkNDIyMj4+233yYdBwA3hrINZ6OIZa2LIsPCwsrLy0nHIay1Jau/v79AaijgxlC2YRlF7HNzc3vvvffq6+tDQ0NJZyHs22+/vXbtWv/+/YXWc4C5rz92DPDRi/Lwph5xIjc3d8SIES0tLX/88YejoyPpOGQ0NTVZWVkVFRUdOnRo0aJFpOO0hSeGsgVno4gTZmZmK1eupChKLBar7J/qyMjIoqIiBwcHYZ4OgBtD2YKzUcSVZ8+eWVhYlJeXf//991yfNSRARUVFVlZWEokkKSnJxcWFdJx2lJaCqSmIRFBaCkQ3BHR7OBtFXOnTp09YWBgABAQENDU1kY7DNz8/v6amJi8vL2HWUMCNoezBMoo49Omnnzo4OBQXF8fGxpLOwqtr166dPHlSR0dH4B0GcGMoK/CmHnHr+vXrrq6u2traDx48MDU1JR2HDxRFjRkzJj09fePGjcxmBMHCE0NZgbNRxK3x48d7eHhIJJL169eTzsKTffv2paenDx482M/Pj3SW18CNoazA2SjiXHFxsaWlpUQiuXr1qqurK+k43KqtrTU3N3/y5MmJEyc8PDxIx3m9xESYNg3MzCAnB9TUSKfpnnA2ijg3ePBgf3//1v08pONwKyws7MmTJy4uLnPmzCGdpVPc3MDYGHJz4eZN0lG6LZyNIj5IJBJLS8uioqLFixePHz+edByulJeX/+Mf/6Ao6ubNmw4ODqTjdFZgIKSkQFQUCHVNgdBhGUU8OXLkSERERFZWFukg3Bo1apSjo+PevXtJB+kCigJ1vC9VApZRxBOapisqKoKCgkgH4Za3t/fYsWOJNxVFfMIyipBK6NsX6urg8mWYPPnPD8eNg169IDkZAGDgQBgxAi5efOmnhg8HbW1IT+c1areDU3mEVAIzX1qxAqTSlz5snUfRNPz1/R9FYWvn18MyipAKyc6GLVtIh+hxsIwipCo8PcHSEiIjIS/vzw9xsqk8fBCOkKrQ0oL9++Hvf4cvvoBff23nG6qq4OzZlz6pr4fevflJ141hGUVIhbi4wPLlsHs3nDgBH37Y9qt378LMmW0/NDLiJ1o3hjf1CKmWzZth8GAQi6G+vu2XnJ2huPil/4YNIxGxu8HZKEKqRV8f9uyBGTNgw4a2X9LWBhOTlz7p1Yu3XN0YzkYRUjnvvw+enrBzJ9y/TzpKj4BlFCFVtG0b9O0LDQ1d+JHISDA2BiMjEItB5U/OfgmWUYRUgpraS33w3nwT4uNffN7uN7T5MCUFIiNh3Tq4cgWuXYO4OB4idxv/Ba1Ztq0ZhWhcAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x11d71b670>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cpmol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "m=bondnormalize(mol, scaf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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eUTIZJZNRLS2kA/UAtlE26eFM9NlnnzGXjcP0uw6oqqrC64Df8PrrFMBPX56epAP1ALZRlunJHboRI0a0trYyl42T9L4r/ac//QkAFi1axFAwZDywjbKM3s+L/f39AWD9+vXMZeMk/dZIXL58GddI8Ae2UfbpyepFS0vLqqoq5rJxTA9X7G7ZsoW5bMh4YBtlH7Va7evri+/SGMAbb7yB74+h/wsPWGal7777btKkSZaWlmVlZc8995yWVQ8fPnRxcWlra8NjfrVRXFzs7e0NADodbS2TyQQCQUNDwxdffEHfHkWchzs8sVJAQEBERIRCoVi3bp32VSNGjFizZg1w65hf5tDfpZUrV+p0tPWmTZsaGhqmTp2KPZRHSI/DSE/379+3trY2MTG5du2a9lUKhWLUqFEA8OGHHzKXjQOOHz8OAA4ODg0NDdpXlZSUmJub9+nTp6CggLlsyNhgG2WxDRs2AMD48ePVarX2VceOHaMbBH+OY9FVR0eHs7MzAOzdu1enwpkzZwLA8uXLGQqGjBO2URZrb2+nb4xmZWXpVPiHP/wBAMRiMTO5WI/eJNvd3Z0+c0lLZ86cAQB7e/snT54wlw0ZIWyj7Hbo0CEAGDJkiE47XxQUFPTp08fMzKyoqIi5bCxVW1trZ2cHOm6x3NnZKRAIAGDXrl3MZUPGCdsou2k0msDAQABITk7WqVC/pTx8EB0dDQDh4eE6Vb3zzjsA4OLi0tXVxVAwZLRwwRPr5efn+/n50aPl2LFjtax68uSJQCBoamr66quv6H03EADk5uZOnDjRwsKiqKiIvj2qjfr6eoFA0NzcfO7cuVmzZjGaEBkhXPDEeuPHj1+0aFFXVxd98KSWBg8eTD+hio+P7+zsZCwdm1AUJRKJKIqij7bWvjAlJaW5ufmll17CHspThKdh1Bvq6uro23kXLlzQvqp70413332XuWws8umnn4LuWyzn5+f36dPHwsKirKyMuWzImGEb5YitW7cCgJubm04Ply9evAgAdnZ2Om0Bx0l6b7E8efJkAEhMTGQoGDJ+2EY5orOzk74x+v777+tUqN+GxNxDvw/m4+Oj0yLco0ePAoCjo2NTUxNz2ZCRwzbKHV9++SUA2Nvb6/TiTfdW0Dc5cJiDvrq3WL5+/br2Ve3t7fQrYR9//DFz2ZDxw0dM3DF37tzp06fLZLJNmzZpX+Xs7LxixQqNRhMfH0/xddlGYmJiR0dHdHQ0vXpMSzt27Lh37563t3dsbCxz2ZDxwwVPnFJSUuLl5QUA+fn5Hh4eWla1tLQIhcK6urpjx47NmzePyYDG6JtvvgkKCrK2ti4rK3NyctKy6sGDBy4uLnK5/MqVK1OmTGE0ITJyOI1yipub29KlS1UqlVgs1r7Kzs5u48aNAJCQkNDe3s5UOKOkVqvp71VKSor2PRQAkpKS5HL5ggULsIcivDfKNY2NjQMHDgSA06dPa1+lVqt9fHxA962g2e6DDz4A3bdYvnHjhomJiZWV1d27dxmLhlgD2ygHvffeewAwZswYnY4P+vbbb+nWUF1dzVw2o/L06dNBgwYBwIkTJ7SvUqvV9MFWqampzGVDLIJtlIOUSiV9Y3THjh06FUZERADAq6++ylAwYxMfHw8AU6dO1anqwIEDADBixIi2tjaGgiF2wUdM3JSdnR0SEmJra1teXj5s2DAtq2pqalxcXBQKxbVr13R6Zs1GZWVlnp6eGo0mLy+Pfi6njdbWVqFQWFtb+/nnny9cuJDRhIgt8BETNwUHB8+ZM6e1tZV+cV5LTk5OEomEoqj4+HiNRsNcPGMgkUiUSuWSJUu076EAsHnz5tra2gkTJkRGRjKXDbEM6XEYMeXHH3+k19X/8MMP2lfJ5XL9toJml7///e8AMGDAgPr6eu2rKisr6W/p999/z1w2xDo4jXLWmDFjVq1apeu6emtr6y1btgBAcnJyS0sLkwGJ6erqSkxMBIC0tLTBgwdrXyiRSDo7O2NiYuhHTAg9Q7qPIwa1tLTQN0aPHDmifZXeW0GzhX5bLGdnZwOAra3to0ePmMuG2AjbKMft378fAEaOHKnTY+W8vDxTU1MLCwupVMpcNiIeP37cv39/ADh37pz2VSqVil78sH37duayIZbCNspxarXaz88PANLS0nQqjImJAYC5c+cyk4uYJUuWAMDs2bN1qsrMzASA0aNH67QUF/EELnjivhs3bgQGBlpaWpaWlj7//PNaVj1+/FggELS0tFy4cGH69OmMJjSYgoICX19fU1PTwsJCoVCoZZVMJhs7dmxjY+OpU6dCQ0MZTYjYCB8xcd/EiRMXLFigUCiSk5O1rxoyZAj988VisUqlYiydQYlEIrVavWrVKu17KACkpqY2NjYGBQVhD0W/jvQ4jAyhpqamX79+AHD16lXtq7q3gt6zZw9z2Qyme4tlmUymfVVxcbG5uXmfPn3u3LnDXDbEathG+SItLQ0Axo0bp9Pu7vRW0A4ODjptBW2E9N5iecaMGQCwcuVKhoIhDsA2yhft7e30jdH9+/frVEjfGF21ahVDwQyD3sra29tbpVJpX3Xy5EkAsLe3f/LkCXPZENthG+WRw4cPg+4HBxUXF5uZmZmZmbH3qvbBgwf0PY0rV65oX9V9T2P37t3MZUMcgI+YeCQyMnLy5Mn19fX0e0pa6t4K+siRI8xlY9SxY8fkcvm8efN02mJ5586dFRUVrq6ub7zxBnPZEAfggid+uXXrlq+vr5mZWWFhoUAg0LKqsbHx+vXrYWFhjGZj1KVLlwQCgU7rvYRCYXNz89dff03fHkXof8E2yjuLFy8+ePDgyy+/fPr0adJZjFdsbGxWVlZoaOipU6dIZ0HGDtso79TX1wsEgubm5vPnz8+cOZN0HGOUn5/v5+en68yOeAvvjfKOo6PjunXr4N8bbpKOY3QoihKJRBqNRiwWYw9F2sBplI+6uro8PDykUmlmZmZcXBzpOMbl8OHDUVFRjo6OUqmU3sQEod+GbZSnzpw5Exoaam9vL5VK6WPdEAAoFApXV9fq6uoDBw7ExsaSjoPYAS/qeerll1+eMWOGTCajT6hHtO3bt1dXV48bN+61114jnQWxBk6j/FVaWurl5aXRaPLz8z09PUnHIa/7RL+rV69OmjSJdBzEGjiN8perq+uyZcvUarVYLCadxSgkJia2t7dHRkZiD0U6wWmU12QymUAgaGhoOHnyJKtX1/ecfruyIgQ4jfKcvb09fW80ISGho6ODdBxiug/+S05Oxh6KdIVtlO+WLVvm4eFRVVW1a9cu0lmIOXDgwM2bN0eOHJmQkEA6C2IfvKhHcPny5eDgYBsbm/Ly8uHDh5OOY2itra0CgaCuru7o0aMLFiwgHQexD06jCIKCgsLCwtra2lJSUkhnIWDTpk11dXUTJ06cP38+6SyIlXAaRQAAVVVV7u7unZ2dubm5/v7+pOMYTmVlpbu7u1Kp/P777319fUnHQayE0ygCABg9ejT9jEUkEvHqT1aRSNTZ2RkbG4s9FOkNp1H0TGtrq1AorK2tPXToUFRUFOk4hvCPf/xj2rRptra25eXlw4YNIx0HsRW2UfSTrKys2NjY/v3782TRT01NjUwm27Fjx+rVq0lnQSyGbRT9RKPRZGRkZGVllZWVkc5iCI6OjhKJRCwWW1hYkM6CWAzbKPolqVSqUChIpzAEc3NzNzc30ikQ62EbRQihHsEn9Qgh1CPYRhFCqEewjSKEUI9gG0UIoR75F9LVlhoXyx3zAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x119ffe990>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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
}