４月８日.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "kegids =[\"C00002\", \"C00003\", \"C00004\", \"C00005\", \n",
    "         \"C00006\", \"C00007\", \"C00008\", \"C00009\", \"C00010\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import urllib\n",
    "for id in kegids:\n",
    "   url = \"http://www.kegg.jp/dbget-bin/www_bget?-f+m+compound+{0}\".format(id)\n",
    "   fn = \"{0}.mol\".format(id)\n",
    "   urllib.urlretrieve(url,\"{0}\".format(fn))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from rdkit import Chem\n",
    "ms = [Chem.MolFromMolFile(\"{0}.mol\".format(id)) for id in kegids]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from rdkit.Chem import AllChem\n",
    "for m in ms: tmp=AllChem.Compute2DCoords(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from rdkit.Chem import Draw\n",
    "Draw.MolToFile(ms[0],'{0}.png'.format(ms[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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/OWLp+VHHj8eZM7hzB2vX4pNPUKvUmhDP8+gOLpc1cVA1wCHUExMTk759+4bJ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\nIWOCcQgZE4xDyJhgHELGBPv/4yN2k4YNFmIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='{0}.png'.format(ms[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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aNGkCZ2dnNGnSBCEhIYiKisK7d+8QFhaGyMhIhIaGIjo6Gt7e3gmPOTg4JMyi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\nPzJ7DMZ79g8OAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img=Draw.MolsToGridImage(ms[:8],molsPerRow=4,subImgSize=(200,200))\n",
    "img.save('molgrid.png')\n",
    "Image(filename=\"molgrid.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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aNGkCZ2dnNGnSBCEhIYiKisK7d+8QFhaGyMhIhIaGIjo6Gt7e3gmPOTg4JMyi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AAAADCGAAIAAADAGAIIAAAAAGMIIAAAAACMIYAAAAAAMIYAAgAAAMAYAggAAAAAYwggAAAAAIwh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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img=Draw.MolsToGridImage(ms,molsPerRow=4,subImgSize=(200,200))\n",
    "img.save('molgrid.png')\n",
    "Image(filename=\"molgrid.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6PdGhoYjOkwemOXOmj2VC6VS6enebNm0aSpcujWPHjqFBgwZwdXVFgwYNEBgY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\nrkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img=Draw.MolsToGridImage(ms,molsPerRow=4,subImgSize=(200,200), legends=kegids)\n",
    "img.save('molgrid.png')\n",
    "Image(filename=\"molgrid.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 True\n",
      "1 True\n",
      "2 True\n",
      "3 True\n",
      "4 True\n",
      "5 False\n",
      "6 True\n",
      "7 False\n",
      "8 True\n"
     ]
    }
   ],
   "source": [
    "for i, m in enumerate(ms):\n",
    "   print i, m.HasSubstructMatch(Chem.MolFromSmarts('ncn'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00002 True\n",
      "C00003 True\n",
      "C00004 True\n",
      "C00005 True\n",
      "C00006 True\n",
      "C00007 False\n",
      "C00008 True\n",
      "C00009 False\n",
      "C00010 True\n"
     ]
    }
   ],
   "source": [
    "for id, m in zip(kegids, ms):\n",
    "   print id, m.HasSubstructMatch(Chem.MolFromSmarts('ncn'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00002\n",
      "  Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)OP(=O)(O)O)C(O)C1O\n",
      "  O=P(O)(O)OP(=O)(O)OP(=O)(O)OCC1OCC(O)C1O.ccN\n",
      "\n",
      "\n",
      "C00003\n",
      "  NC(=O)c1ccc[n+](C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(O)C3O)C(O)C2O)c1\n",
      "  NC(=O)c1ccc[n+](c1)C1OC(COP(=O)(O)OP(=O)(O)OCC2OCC(O)C2O)C(O)C1O.ccN\n",
      "\n",
      "\n",
      "C00004\n",
      "  NC(=O)C1=CN(C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(O)C3O)C(O)C2O)C=CC1\n",
      "  NC(=O)C1=CN(C=CC1)C1OC(COP(=O)(O)OP(=O)(O)OCC2OCC(O)C2O)C(O)C1O.ccN\n",
      "\n",
      "\n",
      "C00005\n",
      "  NC(=O)C1=CN(C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(OP(=O)(O)O)C3O)C(O)C2O)C=CC1\n",
      "  NC(=O)C1=CN(C=CC1)C1OC(COP(=O)(O)OP(=O)(O)OCC2OCC(OP(=O)(O)O)C2O)C(O)C1O.ccN\n",
      "\n",
      "\n",
      "C00006\n",
      "  NC(=O)c1ccc[n+](C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(OP(=O)(O)O)C3O)C(O)C2O)c1\n",
      "  NC(=O)c1ccc[n+](c1)C1OC(COP(=O)(O)OP(=O)(O)OCC2OCC(OP(=O)(O)O)C2O)C(O)C1O.ccN\n",
      "\n",
      "\n",
      "C00007\n",
      "  O=O\n",
      "  O=O\n",
      "\n",
      "\n",
      "C00008\n",
      "  Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)O)C(O)C1O\n",
      "  O=P(O)(O)OP(=O)(O)OCC1OCC(O)C1O.ccN\n",
      "\n",
      "\n",
      "C00009\n",
      "  O=P(O)(O)O\n",
      "  O=P(O)(O)O\n",
      "\n",
      "\n",
      "C00010\n",
      "  CC(C)(COP(=O)(O)OP(=O)(O)OCC1OC(n2cnc3c(N)ncnc32)C(O)C1OP(=O)(O)O)C(O)C(=O)NCCC(=O)NCCS\n",
      "  CC(C)(COP(=O)(O)OP(=O)(O)OCC1OCC(O)C1OP(=O)(O)O)C(O)C(=O)NCCC(=O)NCCS.ccN\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for id, m in zip(kegids, ms):\n",
    "    print id\n",
    "    print \" \", Chem.MolToSmiles(m)\n",
    "    m = AllChem.DeleteSubstructs(m,Chem.MolFromSmarts('ncn'))\n",
    "    print \" \", Chem.MolToSmiles(m)\n",
    "    print \"\\n\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BW7sAjuOki1Veh8hCZ0fBWrduHSZMmAB/f38kJCSgdOnSWL9+PTrz7CG/jFWv8fHA/v2f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\nbffu3RMrV64UQgjx+++/iw4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mxQohKlWKF2/evM1RmXfu3BHGxsbi7Nmzws7OTmzfvl2p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\nAExDAAEAAABgmv8HKZalj0pa2xAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img=Draw.MolsToGridImage(\n",
    "    [AllChem.DeleteSubstructs(m,Chem.MolFromSmarts('ncn')) for m in ms],\n",
    "    molsPerRow=4,subImgSize=(200,200), legends=kegids)\n",
    "img.save('molgrid.png')\n",
    "Image(filename=\"molgrid.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00002\n",
      "  Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)OP(=O)(O)O)C(O)C1O\n",
      "  CC(=O)Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)OP(=O)(O)O)C(O)C1O\n",
      "\n",
      "\n",
      "C00003\n",
      "  NC(=O)c1ccc[n+](C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(O)C3O)C(O)C2O)c1\n",
      "  CC(=O)NC(=O)c1ccc[n+](c1)C1OC(COP(=O)(O)OP(=O)(O)OCC2OC(C(O)C2O)n2cnc3c(N)ncnc32)C(O)C1O\n",
      "\n",
      "\n",
      "C00004\n",
      "  NC(=O)C1=CN(C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(O)C3O)C(O)C2O)C=CC1\n",
      "  CC(=O)Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)OCC2OC(C(O)C2O)N2C=CCC(=C2)C(N)=O)C(O)C1O\n",
      "\n",
      "\n",
      "C00005\n",
      "  NC(=O)C1=CN(C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(OP(=O)(O)O)C3O)C(O)C2O)C=CC1\n",
      "  CC(=O)Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)OCC2OC(C(O)C2O)N2C=CCC(=C2)C(N)=O)C(O)C1OP(=O)(O)O\n",
      "\n",
      "\n",
      "C00006\n",
      "  NC(=O)c1ccc[n+](C2OC(COP(=O)(O)OP(=O)(O)OCC3OC(n4cnc5c(N)ncnc54)C(OP(=O)(O)O)C3O)C(O)C2O)c1\n",
      "  CC(=O)Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)OCC2OC(C(O)C2O)[n+]2cccc(c2)C(N)=O)C(O)C1OP(=O)(O)O\n",
      "\n",
      "\n",
      "C00007\n",
      "  O=O\n",
      "  O=O\n",
      "\n",
      "\n",
      "C00008\n",
      "  Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)O)C(O)C1O\n",
      "  CC(=O)Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)O)C(O)C1O\n",
      "\n",
      "\n",
      "C00009\n",
      "  O=P(O)(O)O\n",
      "  O=P(O)(O)O\n",
      "\n",
      "\n",
      "C00010\n",
      "  CC(C)(COP(=O)(O)OP(=O)(O)OCC1OC(n2cnc3c(N)ncnc32)C(O)C1OP(=O)(O)O)C(O)C(=O)NCCC(=O)NCCS\n",
      "  CC(=O)Nc1ncnc2c1ncn2C1OC(COP(=O)(O)OP(=O)(O)OCC(C)(C)C(O)C(=O)NCCC(=O)NCCS)C(OP(=O)(O)O)C1O\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for id, m in zip(kegids, ms):\n",
    "    print id\n",
    "    print \" \", Chem.MolToSmiles(m)\n",
    "    m = AllChem.ReplaceSubstructs(m,\n",
    "                                  Chem.MolFromSmarts('N'), \n",
    "                                  Chem.MolFromSmiles('NC(=O)C'))\n",
    "    print \" \", Chem.MolToSmiles(m[0])\n",
    "    print \"\\n\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ePHlClSpVdG6jf//+nDx5kmPHjhmwZ5qIiAi6d+/OhAkTuHnzJlWqVKFPnz5v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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ms2 = []\n",
    "for id, m in zip(kegids, ms):\n",
    "    m = AllChem.ReplaceSubstructs(m,\n",
    "                                  Chem.MolFromSmarts('N'), \n",
    "                                  Chem.MolFromSmiles('NC(=O)C'))\n",
    "    ms2.append(m[0])\n",
    "for m in ms2: tmp=AllChem.Compute2DCoords(m)\n",
    "img=Draw.MolsToGridImage(ms2,\n",
    "                         molsPerRow=4,subImgSize=(200,200), legends=kegids)\n",
    "img.save('molgrid.png')\n",
    "Image(filename=\"molgrid.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from rdkit.Chem import rdFMCS\n",
    "res=rdFMCS.FindMCS(ms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.numAtoms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "res=rdFMCS.FindMCS(ms[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.numAtoms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.numBonds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[#7]1(:[#6]2:[#6](:[#6](:[#7]:[#6]:[#7]:2)-[#7]):[#7]:[#6]:1)-[#6]1-[#8]-[#6](-[#6]-[#8]-[#15](-[#8]-[#15](-[#8])(-[#8])=[#8])(-[#8])=[#8])-[#6](-[#6]-1-[#8])-[#8]'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.smartsString"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from rdkit import DataStructs\n",
    "from rdkit.Chem.Fingerprints import FingerprintMols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.873454545455\n",
      "C00004 C00002 0.818305084746\n",
      "C00004 C00003 0.795788130185\n",
      "C00005 C00002 0.790058862001\n",
      "C00005 C00003 0.774273345702\n",
      "C00005 C00004 0.963696369637\n",
      "C00006 C00002 0.831258644537\n",
      "C00006 C00003 0.94950911641\n",
      "C00006 C00004 0.784786641929\n",
      "C00006 C00005 0.818800247372\n",
      "C00007 C00002 0.03125\n",
      "C00007 C00003 0.03125\n",
      "C00007 C00004 0.03125\n",
      "C00007 C00005 0.03125\n",
      "C00007 C00006 0.03125\n",
      "C00008 C00002 0.97790507365\n",
      "C00008 C00003 0.882570162482\n",
      "C00008 C00004 0.818493150685\n",
      "C00008 C00005 0.788778877888\n",
      "C00008 C00006 0.838008415147\n",
      "C00008 C00007 0.03125\n",
      "C00009 C00002 0.1875\n",
      "C00009 C00003 0.1875\n",
      "C00009 C00004 0.1875\n",
      "C00009 C00005 0.1875\n",
      "C00009 C00006 0.1875\n",
      "C00009 C00007 0.0\n",
      "C00009 C00008 0.1875\n",
      "C00010 C00002 0.865370770338\n",
      "C00010 C00003 0.828744123573\n",
      "C00010 C00004 0.807667731629\n",
      "C00010 C00005 0.812696417348\n",
      "C00010 C00006 0.831585845347\n",
      "C00010 C00007 0.03125\n",
      "C00010 C00008 0.872899926954\n",
      "C00010 C00009 0.1875\n"
     ]
    }
   ],
   "source": [
    "#Topological Fingerprints\n",
    "fps = [FingerprintMols.FingerprintMol(m) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.FingerprintSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.930555555556\n",
      "C00004 C00002 0.893333333333\n",
      "C00004 C00003 0.933333333333\n",
      "C00005 C00002 0.906666666667\n",
      "C00005 C00003 0.921052631579\n",
      "C00005 C00004 0.986666666667\n",
      "C00006 C00002 0.944444444444\n",
      "C00006 C00003 0.986111111111\n",
      "C00006 C00004 0.921052631579\n",
      "C00006 C00005 0.934210526316\n",
      "C00007 C00002 0.0588235294118\n",
      "C00007 C00003 0.056338028169\n",
      "C00007 C00004 0.0540540540541\n",
      "C00007 C00005 0.0533333333333\n",
      "C00007 C00006 0.0555555555556\n",
      "C00008 C00002 1.0\n",
      "C00008 C00003 0.930555555556\n",
      "C00008 C00004 0.893333333333\n",
      "C00008 C00005 0.906666666667\n",
      "C00008 C00006 0.944444444444\n",
      "C00008 C00007 0.0588235294118\n",
      "C00009 C00002 0.235294117647\n",
      "C00009 C00003 0.208333333333\n",
      "C00009 C00004 0.2\n",
      "C00009 C00005 0.213333333333\n",
      "C00009 C00006 0.222222222222\n",
      "C00009 C00007 0.25\n",
      "C00009 C00008 0.235294117647\n",
      "C00010 C00002 0.809523809524\n",
      "C00010 C00003 0.802325581395\n",
      "C00010 C00004 0.775280898876\n",
      "C00010 C00005 0.786516853933\n",
      "C00010 C00006 0.813953488372\n",
      "C00010 C00007 0.047619047619\n",
      "C00010 C00008 0.809523809524\n",
      "C00010 C00009 0.190476190476\n"
     ]
    }
   ],
   "source": [
    "# MACCS Keys\n",
    "from rdkit.Chem import MACCSkeys\n",
    "fps = [MACCSkeys.GenMACCSKeys(m) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.FingerprintSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.930555555556\n",
      "C00004 C00002 0.893333333333\n",
      "C00004 C00003 0.933333333333\n",
      "C00005 C00002 0.906666666667\n",
      "C00005 C00003 0.921052631579\n",
      "C00005 C00004 0.986666666667\n",
      "C00006 C00002 0.944444444444\n",
      "C00006 C00003 0.986111111111\n",
      "C00006 C00004 0.921052631579\n",
      "C00006 C00005 0.934210526316\n",
      "C00007 C00002 0.0588235294118\n",
      "C00007 C00003 0.056338028169\n",
      "C00007 C00004 0.0540540540541\n",
      "C00007 C00005 0.0533333333333\n",
      "C00007 C00006 0.0555555555556\n",
      "C00008 C00002 1.0\n",
      "C00008 C00003 0.930555555556\n",
      "C00008 C00004 0.893333333333\n",
      "C00008 C00005 0.906666666667\n",
      "C00008 C00006 0.944444444444\n",
      "C00008 C00007 0.0588235294118\n",
      "C00009 C00002 0.235294117647\n",
      "C00009 C00003 0.208333333333\n",
      "C00009 C00004 0.2\n",
      "C00009 C00005 0.213333333333\n",
      "C00009 C00006 0.222222222222\n",
      "C00009 C00007 0.25\n",
      "C00009 C00008 0.235294117647\n",
      "C00010 C00002 0.809523809524\n",
      "C00010 C00003 0.802325581395\n",
      "C00010 C00004 0.775280898876\n",
      "C00010 C00005 0.786516853933\n",
      "C00010 C00006 0.813953488372\n",
      "C00010 C00007 0.047619047619\n",
      "C00010 C00008 0.809523809524\n",
      "C00010 C00009 0.190476190476\n"
     ]
    }
   ],
   "source": [
    "#Atom-pair descriptors\n",
    "from rdkit.Chem.AtomPairs import Pairs\n",
    "pairFps = [Pairs.GetAtomPairFingerprint(m) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.FingerprintSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.704512372635\n",
      "C00004 C00002 0.647137150466\n",
      "C00004 C00003 0.907449209932\n",
      "C00005 C00002 0.589371980676\n",
      "C00005 C00003 0.82450674974\n",
      "C00005 C00004 0.911392405063\n",
      "C00006 C00002 0.632944228275\n",
      "C00006 C00003 0.898454746137\n",
      "C00006 C00004 0.830927835052\n",
      "C00006 C00005 0.913085004776\n",
      "C00007 C00002 0.0\n",
      "C00007 C00003 0.0\n",
      "C00007 C00004 0.0\n",
      "C00007 C00005 0.0\n",
      "C00007 C00006 0.0\n",
      "C00008 C00002 0.89378757515\n",
      "C00008 C00003 0.700315457413\n",
      "C00008 C00004 0.636103151862\n",
      "C00008 C00005 0.567741935484\n",
      "C00008 C00006 0.615598885794\n",
      "C00008 C00007 0.0\n",
      "C00009 C00002 0.0285714285714\n",
      "C00009 C00003 0.0144578313253\n",
      "C00009 C00004 0.0125260960334\n",
      "C00009 C00005 0.0143884892086\n",
      "C00009 C00006 0.0160320641283\n",
      "C00009 C00007 0.0\n",
      "C00009 C00008 0.0352422907489\n",
      "C00010 C00002 0.497482376636\n",
      "C00010 C00003 0.570921985816\n",
      "C00010 C00004 0.578859060403\n",
      "C00010 C00005 0.568951930654\n",
      "C00010 C00006 0.564356435644\n",
      "C00010 C00007 0.0\n",
      "C00010 C00008 0.463829787234\n",
      "C00010 C00009 0.0110957004161\n"
     ]
    }
   ],
   "source": [
    "#atom-pair descriptors encoded as a standard bit vector fingerprint\n",
    "from rdkit.Chem.AtomPairs import Pairs\n",
    "fps = [Pairs.GetAtomPairFingerprintAsBitVect(m) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.DiceSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.705128205128\n",
      "C00004 C00002 0.705128205128\n",
      "C00004 C00003 0.8\n",
      "C00005 C00002 0.670807453416\n",
      "C00005 C00003 0.748717948718\n",
      "C00005 C00004 0.94358974359\n",
      "C00006 C00002 0.683229813665\n",
      "C00006 C00003 0.94358974359\n",
      "C00006 C00004 0.758974358974\n",
      "C00006 C00005 0.81\n",
      "C00007 C00002 0.0\n",
      "C00007 C00003 0.0\n",
      "C00007 C00004 0.0\n",
      "C00007 C00005 0.0\n",
      "C00007 C00006 0.0\n",
      "C00008 C00002 0.948275862069\n",
      "C00008 C00003 0.72\n",
      "C00008 C00004 0.72\n",
      "C00008 C00005 0.683870967742\n",
      "C00008 C00006 0.696774193548\n",
      "C00008 C00007 0.0\n",
      "C00009 C00002 0.0\n",
      "C00009 C00003 0.0\n",
      "C00009 C00004 0.0\n",
      "C00009 C00005 0.0\n",
      "C00009 C00006 0.0\n",
      "C00009 C00007 0.0\n",
      "C00009 C00008 0.0\n",
      "C00010 C00002 0.702702702703\n",
      "C00010 C00003 0.615384615385\n",
      "C00010 C00004 0.615384615385\n",
      "C00010 C00005 0.652406417112\n",
      "C00010 C00006 0.663101604278\n",
      "C00010 C00007 0.0\n",
      "C00010 C00008 0.718309859155\n",
      "C00010 C00009 0.0\n"
     ]
    }
   ],
   "source": [
    "# Topological torsion descriptors\n",
    "from rdkit.Chem.AtomPairs import Torsions\n",
    "fps = [Torsions.GetTopologicalTorsionFingerprintAsIntVect(m) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.DiceSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.725490196078\n",
      "C00004 C00002 0.725490196078\n",
      "C00004 C00003 0.842975206612\n",
      "C00005 C00002 0.728971962617\n",
      "C00005 C00003 0.777777777778\n",
      "C00005 C00004 0.920634920635\n",
      "C00006 C00002 0.719626168224\n",
      "C00006 C00003 0.920634920635\n",
      "C00006 C00004 0.769841269841\n",
      "C00006 C00005 0.854961832061\n",
      "C00007 C00002 0.046511627907\n",
      "C00007 C00003 0.0322580645161\n",
      "C00007 C00004 0.0322580645161\n",
      "C00007 C00005 0.0298507462687\n",
      "C00007 C00006 0.0298507462687\n",
      "C00008 C00002 0.935897435897\n",
      "C00008 C00003 0.711340206186\n",
      "C00008 C00004 0.711340206186\n",
      "C00008 C00005 0.686274509804\n",
      "C00008 C00006 0.676470588235\n",
      "C00008 C00007 0.0526315789474\n",
      "C00009 C00002 0.193548387097\n",
      "C00009 C00003 0.12213740458\n",
      "C00009 C00004 0.12213740458\n",
      "C00009 C00005 0.127659574468\n",
      "C00009 C00006 0.127659574468\n",
      "C00009 C00007 0.153846153846\n",
      "C00009 C00008 0.21686746988\n",
      "C00010 C00002 0.698113207547\n",
      "C00010 C00003 0.592\n",
      "C00010 C00004 0.592\n",
      "C00010 C00005 0.646153846154\n",
      "C00010 C00006 0.646153846154\n",
      "C00010 C00007 0.030303030303\n",
      "C00010 C00008 0.653465346535\n",
      "C00010 C00009 0.129496402878\n"
     ]
    }
   ],
   "source": [
    "# Morgan Fingerprints (Circular Fingerprints)\n",
    "fps = [AllChem.GetMorganFingerprint(m,2) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.DiceSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.813559322034\n",
      "C00004 C00002 0.820512820513\n",
      "C00004 C00003 0.766917293233\n",
      "C00005 C00002 0.790322580645\n",
      "C00005 C00003 0.728571428571\n",
      "C00005 C00004 0.94964028777\n",
      "C00006 C00002 0.768\n",
      "C00006 C00003 0.936170212766\n",
      "C00006 C00004 0.728571428571\n",
      "C00006 C00005 0.789115646259\n",
      "C00007 C00002 0.0377358490566\n",
      "C00007 C00003 0.0289855072464\n",
      "C00007 C00004 0.0294117647059\n",
      "C00007 C00005 0.0266666666667\n",
      "C00007 C00006 0.0263157894737\n",
      "C00008 C00002 0.990099009901\n",
      "C00008 C00003 0.803418803419\n",
      "C00008 C00004 0.810344827586\n",
      "C00008 C00005 0.780487804878\n",
      "C00008 C00006 0.758064516129\n",
      "C00008 C00007 0.0384615384615\n",
      "C00009 C00002 0.175438596491\n",
      "C00009 C00003 0.13698630137\n",
      "C00009 C00004 0.138888888889\n",
      "C00009 C00005 0.126582278481\n",
      "C00009 C00006 0.125\n",
      "C00009 C00007 0.25\n",
      "C00009 C00008 0.178571428571\n",
      "C00010 C00002 0.71875\n",
      "C00010 C00003 0.638888888889\n",
      "C00010 C00004 0.657342657343\n",
      "C00010 C00005 0.68\n",
      "C00010 C00006 0.675496688742\n",
      "C00010 C00007 0.0253164556962\n",
      "C00010 C00008 0.708661417323\n",
      "C00010 C00009 0.120481927711\n"
     ]
    }
   ],
   "source": [
    "# Morgan Fingerprints (Circular Fingerprints) as bit vectors\n",
    "fps = [AllChem.GetMorganFingerprintAsBitVect(m,2,nBits=1024) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.DiceSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C00003 C00002 0.764705882353\n",
      "C00004 C00002 0.764705882353\n",
      "C00004 C00003 0.801652892562\n",
      "C00005 C00002 0.747663551402\n",
      "C00005 C00003 0.722222222222\n",
      "C00005 C00004 0.912698412698\n",
      "C00006 C00002 0.747663551402\n",
      "C00006 C00003 0.912698412698\n",
      "C00006 C00004 0.730158730159\n",
      "C00006 C00005 0.81679389313\n",
      "C00007 C00002 0.046511627907\n",
      "C00007 C00003 0.0322580645161\n",
      "C00007 C00004 0.0322580645161\n",
      "C00007 C00005 0.0298507462687\n",
      "C00007 C00006 0.0298507462687\n",
      "C00008 C00002 0.935897435897\n",
      "C00008 C00003 0.721649484536\n",
      "C00008 C00004 0.721649484536\n",
      "C00008 C00005 0.686274509804\n",
      "C00008 C00006 0.686274509804\n",
      "C00008 C00007 0.0526315789474\n",
      "C00009 C00002 0.193548387097\n",
      "C00009 C00003 0.137404580153\n",
      "C00009 C00004 0.137404580153\n",
      "C00009 C00005 0.127659574468\n",
      "C00009 C00006 0.127659574468\n",
      "C00009 C00007 0.153846153846\n",
      "C00009 C00008 0.21686746988\n",
      "C00010 C00002 0.745283018868\n",
      "C00010 C00003 0.696\n",
      "C00010 C00004 0.752\n",
      "C00010 C00005 0.792307692308\n",
      "C00010 C00006 0.738461538462\n",
      "C00010 C00007 0.030303030303\n",
      "C00010 C00008 0.683168316832\n",
      "C00010 C00009 0.129496402878\n"
     ]
    }
   ],
   "source": [
    "fps = [AllChem.GetMorganFingerprint(m,2,useFeatures=True) for m in ms]\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       print kegids[i], kegids[j], DataStructs.DiceSimilarity(fps[i],fps[j])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from rdkit.Chem.AtomPairs import Pairs\n",
    "fps1 = [Pairs.GetAtomPairFingerprint(m) for m in ms]\n",
    "x = []\n",
    "for i in range(1,len(fps)):\n",
    "    for j in range(i):\n",
    "       x.append(DataStructs.DiceSimilarity(fps1[i],fps1[j]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fps2 = [AllChem.GetMorganFingerprint(m,2,useFeatures=True) for m in ms]\n",
    "y = []\n",
    "for i in range(1,len(fps2)):\n",
    "    for j in range(i):\n",
    "       y.append(DataStructs.DiceSimilarity(fps2[i],fps2[j]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.5343727852586818, 0.7647058823529411)\n",
      "(0.5315379163713678, 0.7647058823529411)\n",
      "(0.9101479915433404, 0.8016528925619835)\n",
      "(0.48462021343377276, 0.7476635514018691)\n",
      "(0.8071359691417551, 0.7222222222222222)\n",
      "(0.8833172613307618, 0.9126984126984127)\n",
      "(0.4883866917765223, 0.7476635514018691)\n",
      "(0.8842815814850531, 0.9126984126984127)\n",
      "(0.8100289296046287, 0.7301587301587301)\n",
      "(0.9175531914893617, 0.816793893129771)\n",
      "(0.0, 0.046511627906976744)\n",
      "(0.0, 0.03225806451612903)\n",
      "(0.0, 0.03225806451612903)\n",
      "(0.0, 0.029850746268656716)\n",
      "(0.0, 0.029850746268656716)\n",
      "(0.8284313725490197, 0.9358974358974359)\n",
      "(0.5273708558211256, 0.7216494845360825)\n",
      "(0.5242868157286045, 0.7216494845360825)\n",
      "(0.45841784989858014, 0.6862745098039216)\n",
      "(0.46247464503042596, 0.6862745098039216)\n",
      "(0.0, 0.05263157894736842)\n",
      "(0.03368421052631579, 0.1935483870967742)\n",
      "(0.010460251046025104, 0.13740458015267176)\n",
      "(0.010460251046025104, 0.13740458015267176)\n",
      "(0.014059753954305799, 0.1276595744680851)\n",
      "(0.014059753954305799, 0.1276595744680851)\n",
      "(0.0, 0.15384615384615385)\n",
      "(0.0443213296398892, 0.21686746987951808)\n",
      "(0.47206528562460764, 0.7452830188679245)\n",
      "(0.5033751205400193, 0.696)\n",
      "(0.5245901639344263, 0.752)\n",
      "(0.5186170212765957, 0.7923076923076923)\n",
      "(0.500886524822695, 0.7384615384615385)\n",
      "(0.0, 0.030303030303030304)\n",
      "(0.44083840432724813, 0.6831683168316832)\n",
      "(0.014059753954305799, 0.12949640287769784)\n"
     ]
    }
   ],
   "source": [
    "for i, j in zip(x, y):\n",
    "    print (i, j)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DRwXD+vXrAXjuueTqq9cdte7rwMCAU4Vn8fGP/wUHDpzOTFf+tSum99jiVdvMtCiOU4Vf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\nryQV9v8BrCHh9WdQA2YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fa76850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import NullFormatter\n",
    "\n",
    "nullfmt = NullFormatter()         # no labels\n",
    "\n",
    "# definitions for the axes\n",
    "left, width = 0.1, 0.65\n",
    "bottom, height = 0.1, 0.65\n",
    "bottom_h = left_h = left + width + 0.02\n",
    "\n",
    "rect_scatter = [left, bottom, width, height]\n",
    "rect_histx = [left, bottom_h, width, 0.2]\n",
    "rect_histy = [left_h, bottom, 0.2, height]\n",
    "\n",
    "# start with a rectangular Figure\n",
    "plt.figure(1, figsize=(5, 5))\n",
    "\n",
    "axScatter = plt.axes(rect_scatter)\n",
    "axHistx = plt.axes(rect_histx)\n",
    "axHisty = plt.axes(rect_histy)\n",
    "\n",
    "# no labels\n",
    "axHistx.xaxis.set_major_formatter(nullfmt)\n",
    "axHisty.yaxis.set_major_formatter(nullfmt)\n",
    "\n",
    "# the scatter plot:\n",
    "axScatter.scatter(x, y)\n",
    "\n",
    "# now determine nice limits by hand:\n",
    "binwidth = 0.02\n",
    "xymax = np.max([np.max(np.fabs(x)), np.max(np.fabs(y))])\n",
    "lim = (int(xymax/binwidth) + 1) * binwidth\n",
    "\n",
    "#axScatter.set_xlim((-lim, lim))\n",
    "#axScatter.set_ylim((-lim, lim))\n",
    "axScatter.set_xlim((0, lim))\n",
    "axScatter.set_ylim((0, lim))\n",
    "\n",
    "bins = np.arange(-lim, lim + binwidth, binwidth)\n",
    "axHistx.hist(x, bins=bins)\n",
    "axHisty.hist(y, bins=bins, orientation='horizontal')\n",
    "\n",
    "axHistx.set_xlim(axScatter.get_xlim())\n",
    "axHisty.set_ylim(axScatter.get_ylim())\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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