Morgan_Fingerprints_generate_visualize.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、摩根分子指纹计算\n",
    "## 1.简介\n",
    "摩根分子指纹（Morgan Fingerprints），是一种圆形指纹，也属于拓扑型指纹，是通过对标准的摩根算法进行改造后得到。可以大致等同于扩展连通性指纹（Extended-Connectivity Fingerprints，ECFPs）。\n",
    "\n",
    "这类指纹有诸多优点，例如计算速度快、没有经过预定义（可以表示无穷多种不同的分子特征）、可以包含手性信息、指纹中的每个元素代表一种特定子结构、可以方便地进行分析和解释、可以根据不同的需要进行相应的修改等。这类指纹设计的最初目的是用于搜索与活性相关的分子特征，而非子结构搜索。此外也可以用于相似性搜索、聚类、虚拟筛选等方向。指纹的生成过程大致分为以下几个步骤：\n",
    " - 原子初始化。为每个重原子分配一个整数标识符\n",
    " - 迭代更新。以每个重原子为中心，将周围一圈的重原子合并进来，直到到达指定半径。\n",
    " - 特征生成。对子结构进行运算，并生成特征列表。\n",
    " \n",
    "更多内容可以[参考ChemAxon的介绍](https://blog.csdn.net/dreadlesss/article/details/105590719)，还有[ECFPs的文章](http://pubs.acs.org/doi/abs/10.1021/ci100050t)。\n",
    "\n",
    "ECFPs可以捕捉到精确的子结构细节，相对应的，功能基指纹（Functional class fingerprints，FCFPs）则更为泛化，可以将同一类功能基作为一种特征结构。在rdkit中两种特征都可以通过GetMorganFingerprint实现。\n",
    "\n",
    "* 初始化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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da/kMZQfJsbpLjJJduBFKXZ4TYzSSjQ4T03R00kPJsiha7CB1GQ66+KPdBSshV6EwF7V09E67q2RMzyfkOxQQyRVIId9kBynWOShGiYhikRN36omIYghjlIhICmOUiEjK/wBw57lLwgWdsgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=450x150 at 0x782E2C8>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from rdkit import Chem\n",
    "from rdkit import DataStructs\n",
    "from rdkit.Chem import AllChem\n",
    "from rdkit.Chem import Draw\n",
    "m1 = Chem.MolFromSmiles('ClC1=COCNC1')\n",
    "m2 = Chem.MolFromSmiles('BrC1=COCNC1')\n",
    "img = Draw.MolsToGridImage([m1, m2], subImgSize=(150, 150), legends=['ClC1CNCOC1', 'BrC1CNCOC1'])\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "img.save('data/morgan_sample.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.SparseIntVects\n",
    "* 以SparseIntVects方式生成ECFPs指纹：GetMorganFingerprint(mol, radius, ...)<br />\n",
    "或者称为SparseBitVects<br />\n",
    "mol：mol对象<br />\n",
    "radius：考虑半径"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fp1 = AllChem.GetMorganFingerprint(m1, 2)\n",
    "fp2 = AllChem.GetMorganFingerprint(m2, 2)\n",
    "DataStructs.DiceSimilarity(fp1, fp2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 查看长度：GetLength()<br />\n",
    "返回指纹的长度\n",
    "* 查看非空元素：GetNonzeroElements()<br />\n",
    "返回值是一个字典，键对应非空指纹的位数，值是指纹出现的频数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4294967295\n",
      "{39328034: 1, 211414882: 1, 362715007: 1, 397705891: 1, 718785834: 1, 1016841875: 1, 1078999752: 1, 1289643292: 1, 2132511834: 1, 2626911012: 1, 2968968094: 2, 3145053355: 1, 3189457552: 1, 3217380708: 1, 3218693969: 1, 3452535345: 1, 3916672621: 1, 4196496269: 1, 4217154750: 1}\n"
     ]
    }
   ],
   "source": [
    "print(fp1.GetLength())\n",
    "print(fp1.GetNonzeroElements())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.ExplicitBitVects\n",
    "* 以ExplicitBitVects方式生成ECFPs指纹：GetMorganFingerprintAsBitVect(mol, radius, nBits, ...)<br />\n",
    "radius：考虑半径<br />\n",
    "nBits：长度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6842105263157895"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fp1 = AllChem.GetMorganFingerprintAsBitVect(m1, 2, nBits=1024)\n",
    "fp2 = AllChem.GetMorganFingerprintAsBitVect(m2, 2, nBits=1024)\n",
    "DataStructs.DiceSimilarity(fp1, fp2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.FCFPs\n",
    "* 通过设置useFeatures=True生成FCFPs <br /> \n",
    "可以看到ffp1和ffp2完全一致，即Cl和Br在特征上被归为一类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ffp1 = AllChem.GetMorganFingerprint(m1, 2, useFeatures=True)\n",
    "ffp2 = AllChem.GetMorganFingerprint(m2, 2, useFeatures=True)\n",
    "DataStructs.DiceSimilarity(ffp1, ffp2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ffp1 = AllChem.GetMorganFingerprintAsBitVect(m1, 2, nBits=10, useFeatures=True)\n",
    "ffp2 = AllChem.GetMorganFingerprintAsBitVect(m2, 2, nBits=10, useFeatures=True)\n",
    "DataStructs.DiceSimilarity(ffp1, ffp2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 查看向量长度：GetNumBits()\n",
    "* 将指纹转成字符串：ToBitString()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "1111101111\n"
     ]
    }
   ],
   "source": [
    "print(ffp1.GetNumBits())\n",
    "print(ffp1.ToBitString())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.更多泛化\n",
    "* 通过设置invariants，忽略原子类型，关注分子骨架"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m2 = Chem.MolFromSmiles('BrC1=CCCCC1')\n",
    "m3 = Chem.MolFromSmiles('BrC1CCCCC1')\n",
    "Draw.MolsToGridImage([m1, m2, m3], subImgSize=(200, 150))\n",
    "fp1 = AllChem.GetMorganFingerprint(m1, 2, invariants=[1]*m1.GetNumAtoms())\n",
    "fp2 = AllChem.GetMorganFingerprint(m2, 2, invariants=[1]*m2.GetNumAtoms())\n",
    "fp3 = AllChem.GetMorganFingerprint(m3, 2, invariants=[1]*m3.GetNumAtoms())\n",
    "fp1 == fp2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=600x150 at 0x78EAC08>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img = Draw.MolsToGridImage([m1, m2, m3], subImgSize=(200, 150), legends=['m1', 'm2', 'm3'])\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "img.save('data/morgan_sample2.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 可以看到指纹忽略了N和C的差异，fp1和fp2指纹一致，但这个时候还会考虑键的信息。例如比较fp1和fp3，它们是不相等的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fp1 == fp3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 通过设置useBondTypes，忽略键的类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fp1 = AllChem.GetMorganFingerprint(m1, 2, invariants=[1]*m1.GetNumAtoms(), useBondTypes=False)\n",
    "fp3 = AllChem.GetMorganFingerprint(m1, 2, invariants=[1]*m3.GetNumAtoms(), useBondTypes=False)\n",
    "fp1 == fp3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、摩根分子指纹提取\n",
    "* 在生成分子指纹过程中，通过向参数bitInfo传入字典，可以获取所有非空指纹信息 <br /> \n",
    "字典info键表示位的索引，值为原子索引、半径构成的元组，出现多个元组时，表示子结构出现了多次<br />\n",
    "键为2968968094的值中含有多个元组，表示原子索引为4,6，半径为0的子结构相同，都记录在这一位上"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{39328034: ((1, 1),),\n",
       " 211414882: ((5, 2),),\n",
       " 362715007: ((6, 1),),\n",
       " 397705891: ((4, 1),),\n",
       " 718785834: ((1, 2),),\n",
       " 1016841875: ((0, 0),),\n",
       " 1078999752: ((3, 1),),\n",
       " 1289643292: ((5, 1),),\n",
       " 2132511834: ((5, 0),),\n",
       " 2626911012: ((4, 2),),\n",
       " 2968968094: ((4, 0), (6, 0)),\n",
       " 3145053355: ((2, 1),),\n",
       " 3189457552: ((3, 0),),\n",
       " 3217380708: ((1, 0),),\n",
       " 3218693969: ((2, 0),),\n",
       " 3452535345: ((0, 1),),\n",
       " 3916672621: ((6, 2),),\n",
       " 4196496269: ((2, 2),),\n",
       " 4217154750: ((3, 2),)}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "info = {}\n",
    "fp_explain = AllChem.GetMorganFingerprint(m1, 2, bitInfo=info)\n",
    "info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.方法一\n",
    "* 以提取出211414882的结构为例，首先提取m1中，半径为2，第5个原子的结构 <br />\n",
    "submol接收提取出的子结构 <br />\n",
    "amap用于接收原子索引的映射关系，键为原始分子中的原子索引，值为子结构中的原子索引<br />\n",
    "env是被提取出的键的索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: 4, 3: 0, 4: 1, 5: 2, 6: 3}\n",
      "[4, 5, 3, 6]\n"
     ]
    }
   ],
   "source": [
    "amap = {}\n",
    "env = Chem.FindAtomEnvironmentOfRadiusN(m1, 2, 5)\n",
    "submol=Chem.PathToSubmol(m1, env, atomMap=amap)\n",
    "print(amap)\n",
    "print(list(env))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 用SMILES表示该子结构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'CCNCO'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Chem.MolToSmiles(submol)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 以第5个原子为中心，用SMILES表示该子结构，可以看出是氮原子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'N(CO)CC'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Chem.MolToSmiles(submol, rootedAtAtom=amap[5], canonical=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.方法二\n",
    "* 遍历env中的所有键，获取键连接的所有原子，保存在atoms中 <br />\n",
    "通过给定分子，及要提取的原子信息、键信息，获取子结构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'N(CC)CO'"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "atoms=set()\n",
    "for bidx in env: \n",
    "    atoms.add(m1.GetBondWithIdx(bidx).GetBeginAtomIdx())\n",
    "    atoms.add(m1.GetBondWithIdx(bidx).GetEndAtomIdx())\n",
    "Chem.MolFragmentToSmiles(m1, atomsToUse=list(atoms), bondsToUse=env, rootedAtAtom=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 三、指纹可视化\n",
    "查看211414882代表的子结构\n",
    "* 绘制子结构：DrawMorganBit(mol, bitId, bitInfo, ...)<br />\n",
    "mol：mol对象<br />\n",
    "bitId：要查看的bit id<br />\n",
    "bitInfo：指纹信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=150x150 at 0x7A541C8>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img = Draw.DrawMorganBit(m1, 211414882, info)\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "img.save('data/morgan_vis1.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 在ECFPs中的颜色的含义：<br />\n",
    "蓝色：表示中心原子<br />\n",
    "黄色：表示带有芳香性质的原子<br />\n",
    "灰色：表示在脂肪环中的原子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=150x150 at 0x7A5A888>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mol = Chem.MolFromSmiles('c1ccccc1CC1CC1')\n",
    "bi = {}\n",
    "fp = AllChem.GetMorganFingerprintAsBitVect(mol, radius=2, bitInfo=bi)\n",
    "img = Draw.DrawMorganBit(mol, 872, bi)\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "img.save('data/morgan_vis2.png')"
   ]
  }
 ],
 "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": "3.7.4"
  },
  "toc-autonumbering": false
 },
 "nbformat": 4,
 "nbformat_minor": 4
}