recap_brics_decompose_build.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 通过Recap和BRICS对分子拆解与合成"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.Recap拆解\n",
    "另一个与化学反应相关的功能是Recap，Recap可以模仿实验室中的正向合成过程来进行逆向操作，对分子进行一系列的转换与分解，最终得到一组合理的分子片段。Recap可以对拆解过程进行追踪，并形成类似树的数据结构。原始分子记为根节点（root），被拆解的分子记为父节点（parent），拆解得到的分子记为子节点(children)，某节点下的所有分支节点为子孙节点(all children)，某节点上的所有父节点为祖先节点（ultimate parents），无法继续拆解分子记为叶子节点(leaves)。所有英文翻译对应recap中的属性或方法名。\n",
    "\n",
    " - Recap算法拆解分子：Recap.RecapDecompose(mol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rdkit.Chem import Recap\n",
    "from rdkit import Chem\n",
    "from rdkit.Chem import AllChem as Chem\n",
    "m = Chem.MolFromSmiles('c1ccccc1OCCOC(=O)CC')\n",
    "hierarch = Recap.RecapDecompose(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以从节点对象通过函数获取其叶子节点、子孙节点，得到的都是字典，键为节点的smiles，值为节点对象。\n",
    " - 叶子节点函数：hierarch.GetLeaves()\n",
    " - 子孙节点函数：hierarch.GetAllChildren()\n",
    " - 祖先节点函数，返回列表：getUltimateParents()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['*C(=O)CC', '*CCO*', '*c1ccccc1', '*CCOc1ccccc1'])\n",
      "dict_keys(['*C(=O)CC', '*OCCOc1ccccc1', '*CCO*', '*c1ccccc1', '*CCOC(=O)CC', '*CCOc1ccccc1'])\n",
      "CCC(=O)OCCOc1ccccc1\n"
     ]
    }
   ],
   "source": [
    "print(hierarch.GetLeaves().keys())\n",
    "print(hierarch.GetAllChildren().keys())\n",
    "print(hierarch.getUltimateParents()[0].smiles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "还可以查看节点的如下属性：\n",
    " - smiles：smiles（字符串）\n",
    " - 子节点：children（字典）\n",
    " - 父节点：parents（字典）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "*OCCOc1ccccc1\n",
      "dict_keys(['*CCO*', '*c1ccccc1'])\n",
      "dict_keys(['CCC(=O)OCCOc1ccccc1'])\n"
     ]
    }
   ],
   "source": [
    "child = hierarch.children['*OCCOc1ccccc1']\n",
    "print(child.smiles)\n",
    "print(child.children.keys())\n",
    "print(child.parents.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - 查看下叶子节点的分子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x200 at 0x647D9C8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "leaves = list(hierarch.GetLeaves().values())\n",
    "img = Chem.Draw.MolsToGridImage([x.mol for x in leaves], molsPerRow=4, subImgSize=(200, 200))\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "img.save('data/recap_brics_1.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.BRICS拆解\n",
    "Rdkit中还有一种BRICS算法，同样可以用于拆解分子。与recap不同，该算法是根据键是否能够合成来进行拆解。该方法返回一个经过去重的列表，在原子上的序号对应一种特定的反应类型。\n",
    "\n",
    "- BRICS算法拆解分子：BRICS.BRICSDecompose(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'[1*]C(=O)CC', '[16*]c1ccccc1', '[3*]O[3*]', '[4*]CC[4*]'}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from rdkit.Chem import BRICS\n",
    "m = Chem.MolFromSmiles('c1ccccc1OCCOC(=O)CC')\n",
    "BRICS.BRICSDecompose(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - 对一组分子生成片段"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "90\n",
      "['NS(=O)(=O)c1ccc(N/N=C2\\\\C(=O)Nc3ccc(Br)cc32)cc1', '[1*]C(=O)C(C)C', '[1*]C(=O)NN(C)C']\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from rdkit.Chem import RDConfig\n",
    "cdk_file = os.path.join(RDConfig.RDDocsDir, 'Book\\data\\cdk2.sdf')\n",
    "cdk2mols = Chem.SDMolSupplier(cdk_file)\n",
    "allfrags = set()\n",
    "for m in cdk2mols:\n",
    "    pieces = BRICS.BRICSDecompose(m)\n",
    "    allfrags.update(pieces)\n",
    "print(len(allfrags))\n",
    "print(sorted(allfrags)[:3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.BRICS合成\n",
    " - BRICS模块除了支持拆解分子，也可以对一组片段进行合成：BRICS.BRICSBuild()\n",
    " - 返回一个生成器，可以通过next()来获取元素\n",
    " - 生成的分子也是未经过核对的，可以对分子重新计算一下隐式化合价、环相关等属性，并做更新：UpdatePropertyCache()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x200 at 0x7AB8108>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fragms = [Chem.MolFromSmiles(x) for x in sorted(allfrags)]\n",
    "ms = BRICS.BRICSBuild(fragms)\n",
    "prods = [next(ms) for x in range(4)]\n",
    "[prod.UpdatePropertyCache(strict=False) for prod in prods]\n",
    "img = Chem.Draw.MolsToGridImage(prods, molsPerRow=4, subImgSize=(200, 200))\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "img.save('data/recap_brics_2.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以通过设置随机种子或设置scrambleReagents参数来保证可重复性\n",
    " - 在BRICSBuild执行前设置随机种子"
   ]
  },
  {
   "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=800x200 at 0x7ABE708>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import random\n",
    "random.seed(100)\n",
    "fragms = [Chem.MolFromSmiles(x) for x in sorted(allfrags)]\n",
    "ms = BRICS.BRICSBuild(fragms)\n",
    "prods = [next(ms) for x in range(4)]\n",
    "[prod.UpdatePropertyCache(strict=False) for prod in prods]\n",
    "img = Chem.Draw.MolsToGridImage(prods, molsPerRow=4, subImgSize=(200, 200))\n",
    "img"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "img.save('data/recap_brics_3.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " - 设置scrambleReagents参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.PngImagePlugin.PngImageFile image mode=RGB size=800x200 at 0x7AA9388>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fragms = [Chem.MolFromSmiles(x) for x in sorted(allfrags)]\n",
    "ms = BRICS.BRICSBuild(fragms, scrambleReagents=False)\n",
    "prods = [next(ms) for x in range(4)]\n",
    "[prod.UpdatePropertyCache(strict=False) for prod in prods]\n",
    "Chem.Draw.MolsToGridImage(prods, molsPerRow=4, subImgSize=(200, 200))"
   ]
  }
 ],
 "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
}