gninaworkshop.ipynb

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      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/satishgaurav/Molecule-Classification/blob/main/gninaworkshop.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qhgslkr9RQVD"
      },
      "source": [
        "# Getting Setup"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5xipLWWMiG8i",
        "outputId": "1b83fd6e-b4cc-4a5e-e8c0-04d3c2a72f93",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!apt install openbabel"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "The following additional packages will be installed:\n",
            "  libinchi1 libmaeparser1 libopenbabel7\n",
            "The following NEW packages will be installed:\n",
            "  libinchi1 libmaeparser1 libopenbabel7 openbabel\n",
            "0 upgraded, 4 newly installed, 0 to remove and 45 not upgraded.\n",
            "Need to get 3,903 kB of archives.\n",
            "After this operation, 16.9 MB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libinchi1 amd64 1.03+dfsg-4 [455 kB]\n",
            "Get:2 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libmaeparser1 amd64 1.2.4-1build1 [88.2 kB]\n",
            "Get:3 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libopenbabel7 amd64 3.1.1+dfsg-6ubuntu5 [3,231 kB]\n",
            "Get:4 http://archive.ubuntu.com/ubuntu jammy/universe amd64 openbabel amd64 3.1.1+dfsg-6ubuntu5 [128 kB]\n",
            "Fetched 3,903 kB in 1s (3,702 kB/s)\n",
            "Selecting previously unselected package libinchi1.\n",
            "(Reading database ... 121752 files and directories currently installed.)\n",
            "Preparing to unpack .../libinchi1_1.03+dfsg-4_amd64.deb ...\n",
            "Unpacking libinchi1 (1.03+dfsg-4) ...\n",
            "Selecting previously unselected package libmaeparser1:amd64.\n",
            "Preparing to unpack .../libmaeparser1_1.2.4-1build1_amd64.deb ...\n",
            "Unpacking libmaeparser1:amd64 (1.2.4-1build1) ...\n",
            "Selecting previously unselected package libopenbabel7.\n",
            "Preparing to unpack .../libopenbabel7_3.1.1+dfsg-6ubuntu5_amd64.deb ...\n",
            "Unpacking libopenbabel7 (3.1.1+dfsg-6ubuntu5) ...\n",
            "Selecting previously unselected package openbabel.\n",
            "Preparing to unpack .../openbabel_3.1.1+dfsg-6ubuntu5_amd64.deb ...\n",
            "Unpacking openbabel (3.1.1+dfsg-6ubuntu5) ...\n",
            "Setting up libmaeparser1:amd64 (1.2.4-1build1) ...\n",
            "Setting up libinchi1 (1.03+dfsg-4) ...\n",
            "Setting up libopenbabel7 (3.1.1+dfsg-6ubuntu5) ...\n",
            "Setting up openbabel (3.1.1+dfsg-6ubuntu5) ...\n",
            "Processing triggers for libc-bin (2.35-0ubuntu3.4) ...\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc.so.2 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_0.so.3 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc_proxy.so.2 is not a symbolic link\n",
            "\n",
            "/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_5.so.3 is not a symbolic link\n",
            "\n",
            "Processing triggers for man-db (2.10.2-1) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WepFi9Iq3SpR",
        "outputId": "303c11a6-63fd-4081-fbcc-663126e6373a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!wget -c https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
        "!chmod +x Miniconda3-latest-Linux-x86_64.sh\n",
        "!bash ./Miniconda3-latest-Linux-x86_64.sh -b -f -p /usr/local"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-04-18 03:48:34--  https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
            "Resolving repo.continuum.io (repo.continuum.io)... 104.18.176.84, 104.18.177.84, 2606:4700::6812:b054, ...\n",
            "Connecting to repo.continuum.io (repo.continuum.io)|104.18.176.84|:443... connected.\n",
            "HTTP request sent, awaiting response... 301 Moved Permanently\n",
            "Location: https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh [following]\n",
            "--2024-04-18 03:48:34--  https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
            "Resolving repo.anaconda.com (repo.anaconda.com)... 104.16.191.158, 104.16.32.241, 2606:4700::6810:bf9e, ...\n",
            "Connecting to repo.anaconda.com (repo.anaconda.com)|104.16.191.158|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 143351488 (137M) [application/octet-stream]\n",
            "Saving to: ‘Miniconda3-latest-Linux-x86_64.sh’\n",
            "\n",
            "Miniconda3-latest-L 100%[===================>] 136.71M   338MB/s    in 0.4s    \n",
            "\n",
            "2024-04-18 03:48:35 (338 MB/s) - ‘Miniconda3-latest-Linux-x86_64.sh’ saved [143351488/143351488]\n",
            "\n",
            "PREFIX=/usr/local\n",
            "Unpacking payload ...\n",
            "\n",
            "Installing base environment...\n",
            "\n",
            "Preparing transaction: ...working... done\n",
            "Executing transaction: ...working... done\n",
            "installation finished.\n",
            "WARNING:\n",
            "    You currently have a PYTHONPATH environment variable set. This may cause\n",
            "    unexpected behavior when running the Python interpreter in Miniconda3.\n",
            "    For best results, please verify that your PYTHONPATH only points to\n",
            "    directories of packages that are compatible with the Python interpreter\n",
            "    in Miniconda3: /usr/local\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G1_Jjh8ShtRn",
        "outputId": "60d2245b-b54d-49a6-b187-5248cfcf08cd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!conda install -q -y -c conda-forge openbabel"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Channels:\n",
            " - conda-forge\n",
            " - defaults\n",
            "Platform: linux-64\n",
            "Collecting package metadata (repodata.json): ...working... done\n",
            "Solving environment: ...working... done\n",
            "\n",
            "## Package Plan ##\n",
            "\n",
            "  environment location: /usr/local\n",
            "\n",
            "  added / updated specs:\n",
            "    - openbabel\n",
            "\n",
            "\n",
            "The following packages will be downloaded:\n",
            "\n",
            "    package                    |            build\n",
            "    ---------------------------|-----------------\n",
            "    _libgcc_mutex-0.1          |      conda_forge           3 KB  conda-forge\n",
            "    _openmp_mutex-4.5          |            2_gnu          23 KB  conda-forge\n",
            "    cairo-1.18.0               |       h3faef2a_0         959 KB  conda-forge\n",
            "    certifi-2024.2.2           |     pyhd8ed1ab_0         157 KB  conda-forge\n",
            "    conda-24.3.0               |  py312h7900ff3_0         1.1 MB  conda-forge\n",
            "    font-ttf-dejavu-sans-mono-2.37|       hab24e00_0         388 KB  conda-forge\n",
            "    font-ttf-inconsolata-3.000 |       h77eed37_0          94 KB  conda-forge\n",
            "    font-ttf-source-code-pro-2.038|       h77eed37_0         684 KB  conda-forge\n",
            "    font-ttf-ubuntu-0.83       |       h77eed37_1         1.5 MB  conda-forge\n",
            "    fontconfig-2.14.2          |       h14ed4e7_0         266 KB  conda-forge\n",
            "    fonts-conda-ecosystem-1    |                0           4 KB  conda-forge\n",
            "    fonts-conda-forge-1        |                0           4 KB  conda-forge\n",
            "    freetype-2.12.1            |       h267a509_2         620 KB  conda-forge\n",
            "    gettext-0.22.5             |       h59595ed_2         464 KB  conda-forge\n",
            "    gettext-tools-0.22.5       |       h59595ed_2         2.6 MB  conda-forge\n",
            "    icu-73.2                   |       h59595ed_0        11.5 MB  conda-forge\n",
            "    libarchive-3.6.2           |       h039dbb9_1         824 KB  conda-forge\n",
            "    libasprintf-0.22.5         |       h661eb56_2          42 KB  conda-forge\n",
            "    libasprintf-devel-0.22.5   |       h661eb56_2          33 KB  conda-forge\n",
            "    libexpat-2.5.0             |       hcb278e6_1          76 KB  conda-forge\n",
            "    libgcc-ng-13.2.0           |       h807b86a_5         752 KB  conda-forge\n",
            "    libgettextpo-0.22.5        |       h59595ed_2         167 KB  conda-forge\n",
            "    libgettextpo-devel-0.22.5  |       h59595ed_2          36 KB  conda-forge\n",
            "    libglib-2.78.4             |       h783c2da_0         2.6 MB  conda-forge\n",
            "    libgomp-13.2.0             |       h807b86a_5         410 KB  conda-forge\n",
            "    libiconv-1.17              |       hd590300_2         689 KB  conda-forge\n",
            "    libnsl-2.0.1               |       hd590300_0          33 KB  conda-forge\n",
            "    libpng-1.6.43              |       h2797004_0         281 KB  conda-forge\n",
            "    libsqlite-3.45.3           |       h2797004_0         840 KB  conda-forge\n",
            "    libstdcxx-ng-13.2.0        |       h7e041cc_5         3.7 MB  conda-forge\n",
            "    libuuid-2.38.1             |       h0b41bf4_0          33 KB  conda-forge\n",
            "    libxcb-1.15                |       h0b41bf4_0         375 KB  conda-forge\n",
            "    libxcrypt-4.4.36           |       hd590300_1          98 KB  conda-forge\n",
            "    libxml2-2.12.6             |       h232c23b_2         688 KB  conda-forge\n",
            "    libzlib-1.2.13             |       hd590300_5          60 KB  conda-forge\n",
            "    lzo-2.10                   |    h516909a_1000         314 KB  conda-forge\n",
            "    openbabel-3.1.1            |  py312hbfe4552_9         5.0 MB  conda-forge\n",
            "    openssl-3.2.1              |       hd590300_1         2.7 MB  conda-forge\n",
            "    pixman-0.43.2              |       h59595ed_0         378 KB  conda-forge\n",
            "    pthread-stubs-0.4          |    h36c2ea0_1001           5 KB  conda-forge\n",
            "    python-3.12.2              |hab00c5b_0_cpython        30.8 MB  conda-forge\n",
            "    python_abi-3.12            |          4_cp312           6 KB  conda-forge\n",
            "    tk-8.6.13                  |noxft_h4845f30_101         3.2 MB  conda-forge\n",
            "    xorg-kbproto-1.0.7         |    h7f98852_1002          27 KB  conda-forge\n",
            "    xorg-libice-1.1.1          |       hd590300_0          57 KB  conda-forge\n",
            "    xorg-libsm-1.2.4           |       h7391055_0          27 KB  conda-forge\n",
            "    xorg-libx11-1.8.9          |       h8ee46fc_0         809 KB  conda-forge\n",
            "    xorg-libxau-1.0.11         |       hd590300_0          14 KB  conda-forge\n",
            "    xorg-libxdmcp-1.1.3        |       h7f98852_0          19 KB  conda-forge\n",
            "    xorg-libxext-1.3.4         |       h0b41bf4_2          49 KB  conda-forge\n",
            "    xorg-libxrender-0.9.11     |       hd590300_0          37 KB  conda-forge\n",
            "    xorg-renderproto-0.11.1    |    h7f98852_1002           9 KB  conda-forge\n",
            "    xorg-xextproto-7.3.0       |    h0b41bf4_1003          30 KB  conda-forge\n",
            "    xorg-xproto-7.0.31         |    h7f98852_1007          73 KB  conda-forge\n",
            "    zlib-1.2.13                |       hd590300_5          91 KB  conda-forge\n",
            "    ------------------------------------------------------------\n",
            "                                           Total:        75.5 MB\n",
            "\n",
            "The following NEW packages will be INSTALLED:\n",
            "\n",
            "  cairo              conda-forge/linux-64::cairo-1.18.0-h3faef2a_0 \n",
            "  font-ttf-dejavu-s~ conda-forge/noarch::font-ttf-dejavu-sans-mono-2.37-hab24e00_0 \n",
            "  font-ttf-inconsol~ conda-forge/noarch::font-ttf-inconsolata-3.000-h77eed37_0 \n",
            "  font-ttf-source-c~ conda-forge/noarch::font-ttf-source-code-pro-2.038-h77eed37_0 \n",
            "  font-ttf-ubuntu    conda-forge/noarch::font-ttf-ubuntu-0.83-h77eed37_1 \n",
            "  fontconfig         conda-forge/linux-64::fontconfig-2.14.2-h14ed4e7_0 \n",
            "  fonts-conda-ecosy~ conda-forge/noarch::fonts-conda-ecosystem-1-0 \n",
            "  fonts-conda-forge  conda-forge/noarch::fonts-conda-forge-1-0 \n",
            "  freetype           conda-forge/linux-64::freetype-2.12.1-h267a509_2 \n",
            "  gettext            conda-forge/linux-64::gettext-0.22.5-h59595ed_2 \n",
            "  gettext-tools      conda-forge/linux-64::gettext-tools-0.22.5-h59595ed_2 \n",
            "  libasprintf        conda-forge/linux-64::libasprintf-0.22.5-h661eb56_2 \n",
            "  libasprintf-devel  conda-forge/linux-64::libasprintf-devel-0.22.5-h661eb56_2 \n",
            "  libexpat           conda-forge/linux-64::libexpat-2.5.0-hcb278e6_1 \n",
            "  libgettextpo       conda-forge/linux-64::libgettextpo-0.22.5-h59595ed_2 \n",
            "  libgettextpo-devel conda-forge/linux-64::libgettextpo-devel-0.22.5-h59595ed_2 \n",
            "  libglib            conda-forge/linux-64::libglib-2.78.4-h783c2da_0 \n",
            "  libiconv           conda-forge/linux-64::libiconv-1.17-hd590300_2 \n",
            "  libnsl             conda-forge/linux-64::libnsl-2.0.1-hd590300_0 \n",
            "  libpng             conda-forge/linux-64::libpng-1.6.43-h2797004_0 \n",
            "  libsqlite          conda-forge/linux-64::libsqlite-3.45.3-h2797004_0 \n",
            "  libxcb             conda-forge/linux-64::libxcb-1.15-h0b41bf4_0 \n",
            "  libxcrypt          conda-forge/linux-64::libxcrypt-4.4.36-hd590300_1 \n",
            "  libzlib            conda-forge/linux-64::libzlib-1.2.13-hd590300_5 \n",
            "  lzo                conda-forge/linux-64::lzo-2.10-h516909a_1000 \n",
            "  openbabel          conda-forge/linux-64::openbabel-3.1.1-py312hbfe4552_9 \n",
            "  pixman             conda-forge/linux-64::pixman-0.43.2-h59595ed_0 \n",
            "  pthread-stubs      conda-forge/linux-64::pthread-stubs-0.4-h36c2ea0_1001 \n",
            "  python_abi         conda-forge/linux-64::python_abi-3.12-4_cp312 \n",
            "  xorg-kbproto       conda-forge/linux-64::xorg-kbproto-1.0.7-h7f98852_1002 \n",
            "  xorg-libice        conda-forge/linux-64::xorg-libice-1.1.1-hd590300_0 \n",
            "  xorg-libsm         conda-forge/linux-64::xorg-libsm-1.2.4-h7391055_0 \n",
            "  xorg-libx11        conda-forge/linux-64::xorg-libx11-1.8.9-h8ee46fc_0 \n",
            "  xorg-libxau        conda-forge/linux-64::xorg-libxau-1.0.11-hd590300_0 \n",
            "  xorg-libxdmcp      conda-forge/linux-64::xorg-libxdmcp-1.1.3-h7f98852_0 \n",
            "  xorg-libxext       conda-forge/linux-64::xorg-libxext-1.3.4-h0b41bf4_2 \n",
            "  xorg-libxrender    conda-forge/linux-64::xorg-libxrender-0.9.11-hd590300_0 \n",
            "  xorg-renderproto   conda-forge/linux-64::xorg-renderproto-0.11.1-h7f98852_1002 \n",
            "  xorg-xextproto     conda-forge/linux-64::xorg-xextproto-7.3.0-h0b41bf4_1003 \n",
            "  xorg-xproto        conda-forge/linux-64::xorg-xproto-7.0.31-h7f98852_1007 \n",
            "\n",
            "The following packages will be UPDATED:\n",
            "\n",
            "  icu                        pkgs/main::icu-73.1-h6a678d5_0 --> conda-forge::icu-73.2-h59595ed_0 \n",
            "  libgcc-ng          pkgs/main::libgcc-ng-11.2.0-h1234567_1 --> conda-forge::libgcc-ng-13.2.0-h807b86a_5 \n",
            "  libgomp              pkgs/main::libgomp-11.2.0-h1234567_1 --> conda-forge::libgomp-13.2.0-h807b86a_5 \n",
            "  libstdcxx-ng       pkgs/main::libstdcxx-ng-11.2.0-h12345~ --> conda-forge::libstdcxx-ng-13.2.0-h7e041cc_5 \n",
            "  libuuid              pkgs/main::libuuid-1.41.5-h5eee18b_0 --> conda-forge::libuuid-2.38.1-h0b41bf4_0 \n",
            "  libxml2              pkgs/main::libxml2-2.10.4-hf1b16e4_1 --> conda-forge::libxml2-2.12.6-h232c23b_2 \n",
            "  openssl              pkgs/main::openssl-3.0.13-h7f8727e_0 --> conda-forge::openssl-3.2.1-hd590300_1 \n",
            "  tk                        pkgs/main::tk-8.6.12-h1ccaba5_0 --> conda-forge::tk-8.6.13-noxft_h4845f30_101 \n",
            "  zlib                    pkgs/main::zlib-1.2.13-h5eee18b_0 --> conda-forge::zlib-1.2.13-hd590300_5 \n",
            "\n",
            "The following packages will be SUPERSEDED by a higher-priority channel:\n",
            "\n",
            "  _libgcc_mutex           pkgs/main::_libgcc_mutex-0.1-main --> conda-forge::_libgcc_mutex-0.1-conda_forge \n",
            "  _openmp_mutex          pkgs/main::_openmp_mutex-5.1-1_gnu --> conda-forge::_openmp_mutex-4.5-2_gnu \n",
            "  certifi            pkgs/main/linux-64::certifi-2024.2.2-~ --> conda-forge/noarch::certifi-2024.2.2-pyhd8ed1ab_0 \n",
            "  conda              pkgs/main::conda-24.3.0-py312h06a4308~ --> conda-forge::conda-24.3.0-py312h7900ff3_0 \n",
            "  libarchive         pkgs/main::libarchive-3.6.2-h6ac8c49_2 --> conda-forge::libarchive-3.6.2-h039dbb9_1 \n",
            "  python                pkgs/main::python-3.12.2-h996f2a0_0 --> conda-forge::python-3.12.2-hab00c5b_0_cpython \n",
            "\n",
            "\n",
            "Preparing transaction: ...working... done\n",
            "Verifying transaction: ...working... done\n",
            "Executing transaction: ...working... done\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SWSwzgSsiBg3"
      },
      "source": [
        "import sys\n",
        "sys.path.append('/usr/local/lib/python3.8/site-packages/')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "61kJ7OKcKr9E",
        "outputId": "d374986f-4634-4d1a-d810-5c79c21b8b2f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!pip install py3Dmol"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: py3Dmol in /usr/local/lib/python3.12/site-packages (2.1.0)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
            "\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZcFPYBzaJDFQ",
        "outputId": "c0d08782-1690-4aaf-a8e3-30466ecde35a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!wget https://downloads.sourceforge.net/project/smina/smina.static"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-04-18 03:49:27--  https://downloads.sourceforge.net/project/smina/smina.static\n",
            "Resolving downloads.sourceforge.net (downloads.sourceforge.net)... 204.68.111.105\n",
            "Connecting to downloads.sourceforge.net (downloads.sourceforge.net)|204.68.111.105|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://unlimited.dl.sourceforge.net/project/smina/smina.static [following]\n",
            "--2024-04-18 03:49:27--  https://unlimited.dl.sourceforge.net/project/smina/smina.static\n",
            "Resolving unlimited.dl.sourceforge.net (unlimited.dl.sourceforge.net)... 185.119.90.247\n",
            "Connecting to unlimited.dl.sourceforge.net (unlimited.dl.sourceforge.net)|185.119.90.247|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 9853920 (9.4M) [application/octet-stream]\n",
            "Saving to: ‘smina.static’\n",
            "\n",
            "smina.static        100%[===================>]   9.40M  31.1MB/s    in 0.3s    \n",
            "\n",
            "2024-04-18 03:49:28 (31.1 MB/s) - ‘smina.static’ saved [9853920/9853920]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zkFD5W8bJkfd",
        "outputId": "5895ba06-e647-4b32-aefe-61d2cf006864",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!wget https://github.com/gnina/gnina/releases/download/v1.0.1/gnina"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-04-18 03:49:28--  https://github.com/gnina/gnina/releases/download/v1.0.1/gnina\n",
            "Resolving github.com (github.com)... 140.82.121.3\n",
            "Connecting to github.com (github.com)|140.82.121.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/45548146/47de2300-8bd4-11eb-8355-430c51e07fae?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAVCODYLSA53PQK4ZA%2F20240418%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240418T034928Z&X-Amz-Expires=300&X-Amz-Signature=ba063ac8b2ba69ad88a6b917f28ba47d224f236df52dc357360fd7ff16143f6b&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=45548146&response-content-disposition=attachment%3B%20filename%3Dgnina&response-content-type=application%2Foctet-stream [following]\n",
            "--2024-04-18 03:49:28--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/45548146/47de2300-8bd4-11eb-8355-430c51e07fae?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAVCODYLSA53PQK4ZA%2F20240418%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20240418T034928Z&X-Amz-Expires=300&X-Amz-Signature=ba063ac8b2ba69ad88a6b917f28ba47d224f236df52dc357360fd7ff16143f6b&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=45548146&response-content-disposition=attachment%3B%20filename%3Dgnina&response-content-type=application%2Foctet-stream\n",
            "Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 562802104 (537M) [application/octet-stream]\n",
            "Saving to: ‘gnina’\n",
            "\n",
            "gnina               100%[===================>] 536.73M   258MB/s    in 2.1s    \n",
            "\n",
            "2024-04-18 03:49:31 (258 MB/s) - ‘gnina’ saved [562802104/562802104]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fh6kIim8J_kS"
      },
      "source": [
        "!chmod +x gnina"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Bihh7ZKKBnC",
        "outputId": "a524eaee-9ed7-4d4a-d711-b5db996b4128",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!./gnina"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Missing receptor.\n",
            "\n",
            "Correct usage:\n",
            "\n",
            "Input:\n",
            "  -r [ --receptor ] arg            rigid part of the receptor\n",
            "  --flex arg                       flexible side chains, if any (PDBQT)\n",
            "  -l [ --ligand ] arg              ligand(s)\n",
            "  --flexres arg                    flexible side chains specified by comma \n",
            "                                   separated list of chain:resid\n",
            "  --flexdist_ligand arg            Ligand to use for flexdist\n",
            "  --flexdist arg                   set all side chains within specified \n",
            "                                   distance to flexdist_ligand to flexible\n",
            "  --flex_limit arg                 Hard limit for the number of flexible \n",
            "                                   residues\n",
            "  --flex_max arg                   Retain at at most the closest flex_max \n",
            "                                   flexible residues\n",
            "\n",
            "Search space (required):\n",
            "  --center_x arg                   X coordinate of the center\n",
            "  --center_y arg                   Y coordinate of the center\n",
            "  --center_z arg                   Z coordinate of the center\n",
            "  --size_x arg                     size in the X dimension (Angstroms)\n",
            "  --size_y arg                     size in the Y dimension (Angstroms)\n",
            "  --size_z arg                     size in the Z dimension (Angstroms)\n",
            "  --autobox_ligand arg             Ligand to use for autobox\n",
            "  --autobox_add arg                Amount of buffer space to add to \n",
            "                                   auto-generated box (default +4 on all six \n",
            "                                   sides)\n",
            "  --autobox_extend arg (=1)        Expand the autobox if needed to ensure the \n",
            "                                   input conformation of the ligand being \n",
            "                                   docked can freely rotate within the box.\n",
            "  --no_lig                         no ligand; for sampling/minimizing flexible \n",
            "                                   residues\n",
            "\n",
            "Scoring and minimization options:\n",
            "  --scoring arg                    specify alternative built-in scoring \n",
            "                                   function: ad4_scoring default dkoes_fast \n",
            "                                   dkoes_scoring dkoes_scoring_old vina vinardo\n",
            "  --custom_scoring arg             custom scoring function file\n",
            "  --custom_atoms arg               custom atom type parameters file\n",
            "  --score_only                     score provided ligand pose\n",
            "  --local_only                     local search only using autobox (you \n",
            "                                   probably want to use --minimize)\n",
            "  --minimize                       energy minimization\n",
            "  --randomize_only                 generate random poses, attempting to avoid \n",
            "                                   clashes\n",
            "  --num_mc_steps arg               number of monte carlo steps to take in each \n",
            "                                   chain\n",
            "  --num_mc_saved arg               number of top poses saved in each monte \n",
            "                                   carlo chain\n",
            "  --minimize_iters arg (=0)        number iterations of steepest descent; \n",
            "                                   default scales with rotors and usually isn't\n",
            "                                   sufficient for convergence\n",
            "  --accurate_line                  use accurate line search\n",
            "  --simple_ascent                  use simple gradient ascent\n",
            "  --minimize_early_term            Stop minimization before convergence \n",
            "                                   conditions are fully met.\n",
            "  --minimize_single_full           During docking perform a single full \n",
            "                                   minimization instead of a truncated \n",
            "                                   pre-evaluate followed by a full.\n",
            "  --approximation arg              approximation (linear, spline, or exact) to \n",
            "                                   use\n",
            "  --factor arg                     approximation factor: higher results in a \n",
            "                                   finer-grained approximation\n",
            "  --force_cap arg                  max allowed force; lower values more gently \n",
            "                                   minimize clashing structures\n",
            "  --user_grid arg                  Autodock map file for user grid data based \n",
            "                                   calculations\n",
            "  --user_grid_lambda arg (=-1)     Scales user_grid and functional scoring\n",
            "  --print_terms                    Print all available terms with default \n",
            "                                   parameterizations\n",
            "  --print_atom_types               Print all available atom types\n",
            "\n",
            "Convolutional neural net (CNN) scoring:\n",
            "  --cnn_scoring arg (=1)           Amount of CNN scoring: none, rescore \n",
            "                                   (default), refinement, all\n",
            "  --cnn arg                        built-in model to use, specify \n",
            "                                   PREFIX_ensemble to evaluate an ensemble of \n",
            "                                   models starting with PREFIX: \n",
            "                                   crossdock_default2018 crossdock_default2018_\n",
            "                                   1 crossdock_default2018_2 \n",
            "                                   crossdock_default2018_3 \n",
            "                                   crossdock_default2018_4 default2017 dense \n",
            "                                   dense_1 dense_2 dense_3 dense_4 \n",
            "                                   general_default2018 general_default2018_1 \n",
            "                                   general_default2018_2 general_default2018_3 \n",
            "                                   general_default2018_4 redock_default2018 \n",
            "                                   redock_default2018_1 redock_default2018_2 \n",
            "                                   redock_default2018_3 redock_default2018_4\n",
            "  --cnn_model arg                  caffe cnn model file; if not specified a \n",
            "                                   default model will be used\n",
            "  --cnn_weights arg                caffe cnn weights file (*.caffemodel); if \n",
            "                                   not specified default weights (trained on \n",
            "                                   the default model) will be used\n",
            "  --cnn_resolution arg (=0.5)      resolution of grids, don't change unless you\n",
            "                                   really know what you are doing\n",
            "  --cnn_rotation arg (=0)          evaluate multiple rotations of pose (max 24)\n",
            "  --cnn_update_min_frame           During minimization, recenter coordinate \n",
            "                                   frame as ligand moves\n",
            "  --cnn_freeze_receptor            Don't move the receptor with respect to a \n",
            "                                   fixed coordinate system\n",
            "  --cnn_mix_emp_force              Merge CNN and empirical minus forces\n",
            "  --cnn_mix_emp_energy             Merge CNN and empirical energy\n",
            "  --cnn_empirical_weight arg (=1)  Weight for scaling and merging empirical \n",
            "                                   force and energy \n",
            "  --cnn_outputdx                   Dump .dx files of atom grid gradient.\n",
            "  --cnn_outputxyz                  Dump .xyz files of atom gradient.\n",
            "  --cnn_xyzprefix arg (=gradient)  Prefix for atom gradient .xyz files\n",
            "  --cnn_center_x arg               X coordinate of the CNN center\n",
            "  --cnn_center_y arg               Y coordinate of the CNN center\n",
            "  --cnn_center_z arg               Z coordinate of the CNN center\n",
            "  --cnn_verbose                    Enable verbose output for CNN debugging\n",
            "\n",
            "Output:\n",
            "  -o [ --out ] arg                 output file name, format taken from file \n",
            "                                   extension\n",
            "  --out_flex arg                   output file for flexible receptor residues\n",
            "  --log arg                        optionally, write log file\n",
            "  --atom_terms arg                 optionally write per-atom interaction term \n",
            "                                   values\n",
            "  --atom_term_data                 embedded per-atom interaction terms in \n",
            "                                   output sd data\n",
            "  --pose_sort_order arg (=0)       How to sort docking results: CNNscore \n",
            "                                   (default), CNNaffinity, Energy\n",
            "\n",
            "Misc (optional):\n",
            "  --cpu arg                        the number of CPUs to use (the default is to\n",
            "                                   try to detect the number of CPUs or, failing\n",
            "                                   that, use 1)\n",
            "  --seed arg                       explicit random seed\n",
            "  --exhaustiveness arg (=8)        exhaustiveness of the global search (roughly\n",
            "                                   proportional to time)\n",
            "  --num_modes arg (=9)             maximum number of binding modes to generate\n",
            "  --min_rmsd_filter arg (=1)       rmsd value used to filter final poses to \n",
            "                                   remove redundancy\n",
            "  -q [ --quiet ]                   Suppress output messages\n",
            "  --addH arg                       automatically add hydrogens in ligands (on \n",
            "                                   by default)\n",
            "  --stripH arg                     remove hydrogens from molecule _after_ \n",
            "                                   performing atom typing for efficiency (on by\n",
            "                                   default)\n",
            "  --device arg (=0)                GPU device to use\n",
            "  --no_gpu                         Disable GPU acceleration, even if available.\n",
            "\n",
            "Configuration file (optional):\n",
            "  --config arg                     the above options can be put here\n",
            "\n",
            "Information (optional):\n",
            "  --help                           display usage summary\n",
            "  --help_hidden                    display usage summary with hidden options\n",
            "  --version                        display program version\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nQ0kP3f2RePW"
      },
      "source": [
        "# Example"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5wUXrQyoKCls",
        "outputId": "5ea13b18-27cd-4ee5-bded-dfbb87cf025d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!wget http://files.rcsb.org/download/3ERK.pdb"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-04-18 03:54:03--  http://files.rcsb.org/download/3ERK.pdb\n",
            "Resolving files.rcsb.org (files.rcsb.org)... 128.6.159.157\n",
            "Connecting to files.rcsb.org (files.rcsb.org)|128.6.159.157|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: unspecified [application/octet-stream]\n",
            "Saving to: ‘3ERK.pdb’\n",
            "\n",
            "3ERK.pdb                [  <=>               ] 270.21K   666KB/s    in 0.4s    \n",
            "\n",
            "2024-04-18 03:54:04 (666 KB/s) - ‘3ERK.pdb’ saved [276696]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VyKx3tD6Ke_M",
        "outputId": "1be11f1f-8f97-454c-d633-c544aad977e0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "!grep ATOM 3ERK.pdb > rec.pdb\n",
        "!obabel rec.pdb -Orec.pdb"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "==============================\n",
            "*** Open Babel Warning  in PerceiveBondOrders\n",
            "  Failed to kekulize aromatic bonds in OBMol::PerceiveBondOrders (title is rec.pdb)\n",
            "\n",
            "1 molecule converted\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ScPGAtieKhSI"
      },
      "source": [
        "!grep SB4 3ERK.pdb > lig.pdb"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PjISBUUqKkpf",
        "outputId": "34ccdc65-f97a-4db4-b1ed-621321f7b07b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 393
        }
      },
      "source": [
        "import py3Dmol\n",
        "v = py3Dmol.view()\n",
        "v.addModel(open('rec.pdb').read())\n",
        "v.setStyle({'cartoon':{},'stick':{'radius':0.15}})\n",
        "v.addModel(open('lig.pdb').read())\n",
        "v.setStyle({'model':1},{'stick':{'colorscheme':'greenCarbon'}})\n",
        "v.zoomTo({'model':1})"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ModuleNotFoundError",
          "evalue": "No module named 'py3Dmol'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-15-0ca1eb7d4758>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mpy3Dmol\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpy3Dmol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mview\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maddModel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'rec.pdb'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetStyle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'cartoon'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'stick'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'radius'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m0.15\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maddModel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'lig.pdb'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'py3Dmol'",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
          ],
          "errorDetails": {
            "actions": [
              {
                "action": "open_url",
                "actionText": "Open Examples",
                "url": "/notebooks/snippets/importing_libraries.ipynb"
              }
            ]
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "353AUMS_KqQW"
      },
      "source": [
        "!obabel -:'C1CNCCC1n1cnc(c2ccc(cc2)F)c1c1ccnc(n1)N' -Ol2.sdf --gen2D"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Faye1n_fN7SK"
      },
      "source": [
        "v = py3Dmol.view()\n",
        "v.addModel(open('l2.sdf').read())\n",
        "v.setStyle({'stick':{'colorscheme':'greenCarbon'}})\n",
        "v.zoomTo()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OQlecrHbOgWn"
      },
      "source": [
        "!obabel -:'C1CNCCC1n1cnc(c2ccc(cc2)F)c1c1ccnc(n1)N' -Ol3.sdf --gen3D"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7DzqWcZn7U0A"
      },
      "source": [
        "v = py3Dmol.view()\n",
        "v.addModel(open('l3.sdf').read())\n",
        "v.setStyle({'stick':{'colorscheme':'greenCarbon'}})\n",
        "v.zoomTo()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nmMR0sbTRktT"
      },
      "source": [
        "# Simple Docking"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VuG4YDZQ7XIf"
      },
      "source": [
        "!./gnina -r rec.pdb -l lig.pdb --autobox_ligand lig.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BrgAAkFIEh5u"
      },
      "source": [
        "!./gnina -r rec.pdb -l lig.pdb --autobox_ligand lig.pdb --seed 0 -o docked.sdf.gz"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SOKVTi9eFEUx"
      },
      "source": [
        "!gunzip docked.sdf.gz #older openbabel has trouble with gzipped files"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gOhHgXp4Ek1U"
      },
      "source": [
        "!obrms -firstonly lig.pdb docked.sdf"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d7y8w1ncE0St"
      },
      "source": [
        "import gzip\n",
        "v = py3Dmol.view()\n",
        "v.addModel(open('rec.pdb').read())\n",
        "v.setStyle({'cartoon':{},'stick':{'radius':.1}})\n",
        "v.addModel(open('lig.pdb').read())\n",
        "v.setStyle({'model':1},{'stick':{'colorscheme':'dimgrayCarbon','radius':.125}})\n",
        "v.addModelsAsFrames(open('docked.sdf','rt').read())\n",
        "v.setStyle({'model':2},{'stick':{'colorscheme':'greenCarbon'}})\n",
        "v.animate({'interval':1000})\n",
        "v.zoomTo({'model':1})\n",
        "v.rotate(90)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ho6t5tn_GRyv"
      },
      "source": [
        ":Run the necessary commands to dock `l3.sdf`, which is a generated conformer, instead of `lig.pdb` which is the crystal conformer."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lyyNaz3gE_jc"
      },
      "source": [
        "!./gnina"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ub6H8i7AG025"
      },
      "source": [
        "Evaluate RMSD of docked poses to crystal."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PeBHGmyMGfIi"
      },
      "source": [
        "!obrms"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vnBtZrrHMAof"
      },
      "source": [
        "# Timing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ML6DZyabG8A0"
      },
      "source": [
        "%%time\n",
        "!./gnina -r rec.pdb -l lig.pdb --autobox_ligand lig.pdb --seed 0 --exhaustiveness 1 > /dev/null 2>&1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AmAF1SJLL-Ju"
      },
      "source": [
        "%%time\n",
        "!./gnina -r rec.pdb -l lig.pdb --autobox_ligand lig.pdb --seed 0 --exhaustiveness 4 > /dev/null 2>&1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pgvtd2W6MIRM"
      },
      "source": [
        "%%time\n",
        "!./gnina -r rec.pdb -l lig.pdb --autobox_ligand lig.pdb --seed 0 --exhaustiveness 4 --cpu 1 > /dev/null 2>&1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "utLd1N-vMOU6"
      },
      "source": [
        "!cat /proc/cpuinfo"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HiMDn-MlMsLT"
      },
      "source": [
        "# Scoring"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mL8ttmo7MiYO"
      },
      "source": [
        "!./gnina --score_only -r rec.pdb -l lig.pdb --verbosity=2"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pjzHUmQxMvuo"
      },
      "source": [
        "!./gnina --help | grep scoring | head -3"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fLQS6uGzMzp2"
      },
      "source": [
        "!./gnina --print_terms"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qcqJMzz9M7fP"
      },
      "source": [
        "open('everything.txt','wt').write('''\n",
        "1.0  ad4_solvation(d-sigma=3.6,_s/q=0.01097,_c=8)  desolvation, s/q is charge dependence\n",
        "1.0  ad4_solvation(d-sigma=3.6,_s/q=0.0,_c=8)\n",
        "1.0  electrostatic(i=1,_^=100,_c=8)\ti is the exponent of the distance, see everything.h for details\n",
        "1.0  electrostatic(i=2,_^=100,_c=8)\n",
        "1.0  gauss(o=0,_w=0.5,_c=8)\t\to is offset, w is width of gaussian\n",
        "1.0  gauss(o=3,_w=2,_c=8)\n",
        "1.0  repulsion(o=0,_c=8)\to is offset of squared distance repulsion\n",
        "1.0  hydrophobic(g=0.5,_b=1.5,_c=8)\t\tg is a good distance, b the bad distance\n",
        "1.0  non_hydrophobic(g=0.5,_b=1.5,_c=8)\tvalue is linearly interpolated between g and b\n",
        "1.0  vdw(i=4,_j=8,_s=0,_^=100,_c=8)\ti and j are LJ exponents\n",
        "1.0  vdw(i=6,_j=12,_s=1,_^=100,_c=8) s is the smoothing, ^ is the cap\n",
        "1.0  non_dir_h_bond(g=-0.7,_b=0,_c=8)\tgood and bad\n",
        "1.0  non_dir_anti_h_bond_quadratic(o=0.4,_c=8) like repulsion, but for hbond, don't use\n",
        "1.0  non_dir_h_bond_lj(o=-0.7,_^=100,_c=8)\tLJ 10-12 potential, capped at ^\n",
        "1.0 acceptor_acceptor_quadratic(o=0,_c=8)\tquadratic potential between hydrogen bond acceptors\n",
        "1.0 donor_donor_quadratic(o=0,_c=8)\tquadratic potential between hydroben bond donors\n",
        "1.0  num_tors_div\tdiv constant terms are not linearly independent\n",
        "1.0  num_heavy_atoms_div\n",
        "1.0  num_heavy_atoms\tthese terms are just added\n",
        "1.0  num_tors_add\n",
        "1.0  num_tors_sqr\n",
        "1.0  num_tors_sqrt\n",
        "1.0  num_hydrophobic_atoms\n",
        "1.0  ligand_length\n",
        "''');"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6SgwFBMzNFgo"
      },
      "source": [
        "!./gnina -r rec.pdb -l lig.pdb --score_only --custom_scoring everything.txt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PAPiiaPXNLbI"
      },
      "source": [
        "# CNN Scoring"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ObN0CEI6NHKQ"
      },
      "source": [
        "!./gnina --help | grep \"cnn arg\" -A 12"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yizf6AAnNQ5D"
      },
      "source": [
        "!./gnina --score_only -r rec.pdb -l lig.pdb  | grep CNN"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c7DWIP3aNSdB"
      },
      "source": [
        "%%time\n",
        "!./gnina -r rec.pdb -l lig.pdb --autobox_ligand lig.pdb --seed 0  > /dev/null 2>&1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vTuvFbX5NWfm"
      },
      "source": [
        "%%time\n",
        "!CUDA_VISIBLE_DEVICES= ./gnina -r rec.pdb -l lig.pdb --autobox_ligand lig.pdb --seed 0"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zK6aigYPNfGK"
      },
      "source": [
        "# Whole Protein Docking"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "duG2Ny1gNbpf"
      },
      "source": [
        "!./gnina -r rec.pdb -l lig.pdb --autobox_ligand rec.pdb -o wdocking.sdf.gz --seed 0"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EElgbxo6NkIs"
      },
      "source": [
        "v = py3Dmol.view(height=400)\n",
        "v.addModel(open('rec.pdb').read())\n",
        "v.setStyle({'cartoon':{},'stick':{'radius':.1}})\n",
        "v.addModel(open('lig.pdb').read())\n",
        "v.setStyle({'model':1},{'stick':{'colorscheme':'dimgrayCarbon','radius':.125}})\n",
        "v.addModelsAsFrames(gzip.open('wdocking.sdf.gz','rt').read())\n",
        "v.setStyle({'model':2},{'stick':{'colorscheme':'greenCarbon'}})\n",
        "v.animate({'interval':1000}); v.zoomTo(); v.rotate(90)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oik4qs3TOj00"
      },
      "source": [
        "# Flexible Docking"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UKn-Vu6nN4nz"
      },
      "source": [
        "!wget http://files.rcsb.org/download/4ERK.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oxlY70baO5Sp"
      },
      "source": [
        "!grep ATOM 4ERK.pdb > rec2.pdb\n",
        "!obabel rec2.pdb -Orec2.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BlWuX33qO6vX"
      },
      "source": [
        "!grep OLO 4ERK.pdb > lig2.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QB8oM_p8O836"
      },
      "source": [
        "!./gnina -r rec2.pdb -l lig.pdb --autobox_ligand lig2.pdb --seed 0 -o 3erk_to_4erk.sdf"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "atbgzXQHO-Se"
      },
      "source": [
        "!obrms -firstonly lig.pdb 3erk_to_4erk.sdf"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Cbn6hQpPRmg"
      },
      "source": [
        "!./gnina -r rec2.pdb -l lig.pdb --autobox_ligand lig2.pdb --seed 0 -o flexdocked.sdf --flexdist 4 --flexdist_ligand lig2.pdb --out_flex flexout.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ZWLPSucSExv"
      },
      "source": [
        "!obrms -firstonly lig.pdb flexdocked.sdf"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CYe8hTawSNxa"
      },
      "source": [
        "!./gnina -r rec2.pdb -l lig.pdb --autobox_ligand lig2.pdb --seed 0 -o flexdocked2.sdf --exhaustiveness 16 --flexres A:52,A:103 --out_flex flexout2.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K49K1WyRbBKp"
      },
      "source": [
        "# Virtual Screening"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_hEeNFO9SpJl"
      },
      "source": [
        "!wget http://files.rcsb.org/download/4PPS.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5xmCNROKbGiu"
      },
      "source": [
        "!grep ^ATOM 4PPS.pdb > errec.pdb"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TcaTLJ5obg_H"
      },
      "source": [
        "!wget http://bits.csb.pitt.edu/files/workshop_minimized_results.sdf.gz"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kecn2uqFbH2N"
      },
      "source": [
        "!./gnina -r errec.pdb -l workshop_minimized_results.sdf.gz --minimize -o gnina_scored.sdf.gz --scoring vinardo"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_LcxM-dDbKsh"
      },
      "source": [
        "from openbabel import pybel\n",
        "import pandas as pd\n",
        "\n",
        "scores = []\n",
        "for mol in pybel.readfile('sdf','gnina_scored.sdf.gz'):\n",
        "    scores.append({'title': mol.title,\n",
        "                   'CNNscore': float(mol.data['CNNscore']),\n",
        "                   'CNNaffinity': float(mol.data['CNNaffinity']),\n",
        "                   'Vinardo': float(mol.data['minimizedAffinity'])})\n",
        "scores = pd.DataFrame(scores)\n",
        "scores['label'] = scores.title.str.contains('active')\n",
        "\n",
        "scores"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2h0DHkeeb5OL"
      },
      "source": [
        "from sklearn.metrics import roc_auc_score, roc_curve, auc\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nJ0w97M2g6ul"
      },
      "source": [
        "plt.figure(dpi=150)\n",
        "plt.plot([0,1],[0,1],'k--',alpha=0.5,linewidth=1)\n",
        "fpr,tpr,_ = roc_curve(scores.label,-scores.Vinardo)\n",
        "plt.plot(fpr,tpr,label=\"Vinardo (AUC = %.2f)\"%auc(fpr,tpr))\n",
        "fpr,tpr,_ = roc_curve(scores.label,scores.CNNaffinity)\n",
        "plt.plot(fpr,tpr,label=\"CNNaffinity (AUC = %.2f)\"%auc(fpr,tpr))\n",
        "fpr,tpr,_ = roc_curve(scores.label, scores.CNNaffinity.rank() + (-scores.Vinardo).rank())\n",
        "plt.plot(fpr,tpr,label=\"Consensus (AUC = %.2f)\"%auc(fpr,tpr))\n",
        "plt.legend(loc='lower right')\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.gca().set_aspect('equal')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q53Z8bxIiXlI"
      },
      "source": [
        "# Custom Scoring"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ux-swSoLiVwD"
      },
      "source": [
        "!./gnina -r errec.pdb -l workshop_minimized_results.sdf.gz --score_only --custom_scoring everything.txt > scores.txt 2>&1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fOQKdbEyiayO"
      },
      "source": [
        "!head -30 scores.txt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZneO_qlmicW0"
      },
      "source": [
        "import subprocess, io, re\n",
        "terms = pd.read_csv(io.BytesIO(subprocess.check_output(\"grep \\#\\# scores.txt | sed 's/## //'\",shell=True)),delim_whitespace=True)\n",
        "terms[['CNNscore','CNNaffinity','CNNvariance']] = re.findall(r'CNNscore: (\\S+)\\s*CNNaffinity: (\\S+)\\s*CNNvariance: (\\S+)',open('scores.txt').read())\n",
        "terms['label'] = terms.Name.str.contains('active')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vXSD-Rg2ihL1"
      },
      "source": [
        "import sklearn\n",
        "from sklearn.linear_model import *\n",
        "\n",
        "X = terms.drop(['Name','label'],axis=1).astype(float) # features\n",
        "Y = terms.label"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-m9rJN2KikPf"
      },
      "source": [
        "X"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TWgWg0u8ilif"
      },
      "source": [
        "model = LogisticRegression(solver='liblinear')\n",
        "cvpredict = sklearn.model_selection.cross_val_predict(model, X, Y, method='predict_proba')\n",
        "fpr,tpr,_ = roc_curve(Y,cvpredict[:,1])\n",
        "fig,ax = plt.subplots(1,1,dpi=100)\n",
        "ax.plot(fpr,tpr,label=\"Combined CV ROC (AUC=%.2f)\"%auc(fpr,tpr))\n",
        "plt.xlabel('False Positive Rate')\n",
        "plt.ylabel('True Positive Rate')\n",
        "plt.legend()\n",
        "ax.set_aspect('equal');"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "roP156aoinz9"
      },
      "source": [],
      "execution_count": null,
      "outputs": []
    }
  ]
}