2023_02_21_Auto3D_test.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/chupvl/gcolab/blob/main/2023_02_21_Auto3D_test.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
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      "source": [
        "# 2023-02-21: Testing Auto3D package"
      ],
      "metadata": {
        "id": "4FKF66PAmVIu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Notebook created by Vladimir Chupakhin, chupvl@gmail.com\n",
        "- https://www.linkedin.com/in/chupvl\n",
        "- https://twitter.com/chupvl\n",
        "\n",
        "Goal of this notebook is to test [Auto3D](https://github.com/isayevlab/Auto3D_pkg) for conformer generation for drug like compounds using Google Colaboratory. Auto3D was developed in the group of Professor [Olexandr Isayev](https://www.cmu.edu/chemistry/people/faculty/isayev.html) and published in [2022](https://pubs.acs.org/doi/10.1021/acs.jcim.2c00817). \n",
        "\n"
      ],
      "metadata": {
        "id": "blORoN3LzlAD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Libs"
      ],
      "metadata": {
        "id": "-TQoTO0smWU1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install py3Dmol"
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        "id": "K_TnbrKDor2o",
        "outputId": "881ac930-aa3b-4ef0-fc92-900606355e62"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting py3Dmol\n",
            "  Downloading py3Dmol-2.0.1.post1-py2.py3-none-any.whl (12 kB)\n",
            "Installing collected packages: py3Dmol\n",
            "Successfully installed py3Dmol-2.0.1.post1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install rdkit"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ar7VuUzimgen",
        "outputId": "f0b97332-d1e6-4d64-ecb2-ccf82dc89f5a"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting rdkit\n",
            "  Downloading rdkit-2022.9.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (29.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m29.3/29.3 MB\u001b[0m \u001b[31m46.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: Pillow in /usr/local/lib/python3.8/dist-packages (from rdkit) (7.1.2)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.8/dist-packages (from rdkit) (1.21.6)\n",
            "Installing collected packages: rdkit\n",
            "Successfully installed rdkit-2022.9.4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!sudo apt-get install python3-openbabel\n",
        "# !pip install openbabel will fail with \"legacy-install-failure\" error\n",
        "# so, going the other route"
      ],
      "metadata": {
        "id": "uQ3tRvnlxyY5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "57131d68-3e99-456f-9ffb-801eb61e6237"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "The following package was automatically installed and is no longer required:\n",
            "  libnvidia-common-510\n",
            "Use 'sudo apt autoremove' to remove it.\n",
            "The following additional packages will be installed:\n",
            "  libopenbabel6 libschroedinger-maeparser1\n",
            "The following NEW packages will be installed:\n",
            "  libopenbabel6 libschroedinger-maeparser1 python3-openbabel\n",
            "0 upgraded, 3 newly installed, 0 to remove and 21 not upgraded.\n",
            "Need to get 4,213 kB of archives.\n",
            "After this operation, 20.6 MB of additional disk space will be used.\n",
            "Get:1 http://archive.ubuntu.com/ubuntu focal/universe amd64 libschroedinger-maeparser1 amd64 1.2.2-1build1 [89.1 kB]\n",
            "Get:2 http://archive.ubuntu.com/ubuntu focal/universe amd64 libopenbabel6 amd64 3.0.0+dfsg-3ubuntu3 [3,568 kB]\n",
            "Get:3 http://archive.ubuntu.com/ubuntu focal/universe amd64 python3-openbabel amd64 3.0.0+dfsg-3ubuntu3 [556 kB]\n",
            "Fetched 4,213 kB in 1s (4,644 kB/s)\n",
            "debconf: unable to initialize frontend: Dialog\n",
            "debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 3.)\n",
            "debconf: falling back to frontend: Readline\n",
            "debconf: unable to initialize frontend: Readline\n",
            "debconf: (This frontend requires a controlling tty.)\n",
            "debconf: falling back to frontend: Teletype\n",
            "dpkg-preconfigure: unable to re-open stdin: \n",
            "Selecting previously unselected package libschroedinger-maeparser1:amd64.\n",
            "(Reading database ... 128126 files and directories currently installed.)\n",
            "Preparing to unpack .../libschroedinger-maeparser1_1.2.2-1build1_amd64.deb ...\n",
            "Unpacking libschroedinger-maeparser1:amd64 (1.2.2-1build1) ...\n",
            "Selecting previously unselected package libopenbabel6.\n",
            "Preparing to unpack .../libopenbabel6_3.0.0+dfsg-3ubuntu3_amd64.deb ...\n",
            "Unpacking libopenbabel6 (3.0.0+dfsg-3ubuntu3) ...\n",
            "Selecting previously unselected package python3-openbabel.\n",
            "Preparing to unpack .../python3-openbabel_3.0.0+dfsg-3ubuntu3_amd64.deb ...\n",
            "Unpacking python3-openbabel (3.0.0+dfsg-3ubuntu3) ...\n",
            "Setting up libschroedinger-maeparser1:amd64 (1.2.2-1build1) ...\n",
            "Setting up libopenbabel6 (3.0.0+dfsg-3ubuntu3) ...\n",
            "Setting up python3-openbabel (3.0.0+dfsg-3ubuntu3) ...\n",
            "Processing triggers for libc-bin (2.31-0ubuntu9.9) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install Auto3D --default-timeout=100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lDUyoonTmi1c",
        "outputId": "c7589b9d-4f29-4ee8-d2ce-c1d159908cf6"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: Auto3D in /usr/local/lib/python3.8/dist-packages (2.0)\n",
            "Requirement already satisfied: Send2Trash in /usr/local/lib/python3.8/dist-packages (from Auto3D) (1.8.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.8/dist-packages (from Auto3D) (4.64.1)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.8/dist-packages (from Auto3D) (6.0)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.8/dist-packages (from Auto3D) (5.4.8)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# ok, doing with  pip installation via local clone\n",
        "# if above is timed out use function below\n",
        "# !git clone https://github.com/isayevlab/Auto3D_pkg.git\n",
        "# !pip install ./Auto3D_pkg/. "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6hDBHLtkrMoY",
        "outputId": "dc3f588b-7bc6-48e4-cc8c-7e1b9f976e1d"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Auto3D_pkg'...\n",
            "remote: Enumerating objects: 592, done.\u001b[K\n",
            "remote: Counting objects: 100% (125/125), done.\u001b[K\n",
            "remote: Compressing objects: 100% (108/108), done.\u001b[K\n",
            "remote: Total 592 (delta 29), reused 45 (delta 17), pack-reused 467\u001b[K\n",
            "Receiving objects: 100% (592/592), 113.06 MiB | 40.40 MiB/s, done.\n",
            "Resolving deltas: 100% (311/311), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from rdkit import Chem\n",
        "from rdkit.Chem import AllChem\n",
        "from rdkit.Chem.Draw import IPythonConsole\n",
        "from rdkit.Chem import PandasTools\n",
        "from rdkit.Chem.MolStandardize import rdMolStandardize\n",
        "\n",
        "import py3Dmol\n",
        "import Auto3D\n",
        "\n",
        "from ipywidgets import interact, interactive, fixed, Dropdown\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd"
      ],
      "metadata": {
        "id": "K3ZagoJEmivk"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Functions"
      ],
      "metadata": {
        "id": "pjNlVq6iyNqN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def mol_clashes(mol, dist_cutoff=1, verbose=False):\n",
        "    '''for a rdkit molecule return number of clashes with a specified cutoff''' \n",
        "    distances = AllChem.Get3DDistanceMatrix(mol)\n",
        "    nClashes = sum(distances[np.triu_indices(len(distances), k = 1)] < dist_cutoff)\n",
        "    if verbose:\n",
        "        if nClashes > 0:\n",
        "            print(f'Number of clashes between atoms: {nClashes}')\n",
        "        else:\n",
        "            print(f'There are no clashes between atoms')\n",
        "    return nClashes"
      ],
      "metadata": {
        "id": "bXIcEiBcsGB_"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# from: http://rdkit.blogspot.com/2016/07/using-ipywidgets-and-py3dmol-to-browse.html\n",
        "def drawit(m, p):\n",
        "        mb = Chem.MolToMolBlock(m)\n",
        "        p.removeAllModels()\n",
        "        p.addModel(mb,'sdf')\n",
        "        p.setStyle({'stick':{}})\n",
        "        p.setBackgroundColor('0xeeeeee')\n",
        "        p.zoomTo()\n",
        "        return p.show()"
      ],
      "metadata": {
        "id": "eRTsclpMt2DK"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Tesing Auto3D"
      ],
      "metadata": {
        "id": "NokdpvVVr1xY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from Auto3D.auto3D import options, main\n",
        "print(Auto3D.__version__)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yKkDTJQxr04y",
        "outputId": "60bd2fec-e4e6-4060-95dd-361d1b44ab74"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%time\n",
        "smiles_file = './Auto3D_pkg/example/files/smiles.smi'\n",
        "if __name__ == \"__main__\":\n",
        "    path = smiles_file\n",
        "    args = options(path, k=1, use_gpu=True)   #specify the parameters for Auto3D \n",
        "    out = main(args)            #main acceps the parameters and run Auto3D\n",
        "    print(out)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4yovOb3GyWR5",
        "outputId": "6a600a36-8dc2-4de3-b83f-78a5d45eff51"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:\n",
            "             _              _             _____   ____  \n",
            "            / \\     _   _  | |_    ___   |___ /  |  _ \\ \n",
            "           / _ \\   | | | | | __|  / _ \\    |_ \\  | | | |\n",
            "          / ___ \\  | |_| | | |_  | (_) |  ___) | | |_| |\n",
            "         /_/   \\_\\  \\__,_|  \\__|  \\___/  |____/  |____/  2.0\n",
            "                // Automatic generation of the low-energy 3D structures                                      \n",
            "        \n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:                               INPUT PARAMETERS\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:path: ./Auto3D_pkg/example/files/smiles.smi\n",
            "INFO:auto3d:k: 1\n",
            "INFO:auto3d:window: False\n",
            "INFO:auto3d:verbose: False\n",
            "INFO:auto3d:job_name: 20230222-155817-731514\n",
            "INFO:auto3d:enumerate_tautomer: False\n",
            "INFO:auto3d:tauto_engine: rdkit\n",
            "INFO:auto3d:pKaNorm: True\n",
            "INFO:auto3d:isomer_engine: rdkit\n",
            "INFO:auto3d:enumerate_isomer: True\n",
            "INFO:auto3d:mode_oe: classic\n",
            "INFO:auto3d:mpi_np: 4\n",
            "INFO:auto3d:max_confs: None\n",
            "INFO:auto3d:use_gpu: True\n",
            "INFO:auto3d:capacity: 42\n",
            "INFO:auto3d:gpu_idx: 0\n",
            "INFO:auto3d:optimizing_engine: AIMNET\n",
            "INFO:auto3d:patience: 1000\n",
            "INFO:auto3d:opt_steps: 5000\n",
            "INFO:auto3d:convergence_threshold: 0.003\n",
            "INFO:auto3d:threshold: 0.3\n",
            "INFO:auto3d:memory: None\n",
            "INFO:auto3d:batchsize_atoms: 1024\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:                               RUNNING PROCESS\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:Checking input file...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Checking input file...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:\tThere are 4 SMILES in the input file ./Auto3D_pkg/example/files/smiles.smi. \n",
            "\tAll SMILES and IDs are valid.\n",
            "INFO:auto3d:Suggestions for choosing isomer_engine and optimizing_engine: \n",
            "INFO:auto3d:\tIsomer engine options: RDKit and Omega.\n",
            "INFO:auto3d:\tOptimizing engine options: ANI2x, ANI2xt and AIMNET.\n",
            "INFO:auto3d:The available memory is 15 GB.\n",
            "INFO:auto3d:The task will be divided into 1 jobs.\n",
            "INFO:auto3d:Job1, number of inputs: 4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\tThere are 4 SMILES in the input file ./Auto3D_pkg/example/files/smiles.smi. \n",
            "\tAll SMILES and IDs are valid.\n",
            "Suggestions for choosing isomer_engine and optimizing_engine: \n",
            "\tIsomer engine options: RDKit and Omega.\n",
            "\tOptimizing engine options: ANI2x, ANI2xt and AIMNET.\n",
            "The available memory is 15 GB.\n",
            "The task will be divided into 1 jobs.\n",
            "Job1, number of inputs: 4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:Energy unit: Hartree if implicit.\n",
            "INFO:auto3d:Program running time: 0 minutes\n",
            "INFO:auto3d:Output path: /content/Auto3D_pkg/example/files/20230222-155817-731514_smiles/smiles_out.sdf\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Energy unit: Hartree if implicit.\n",
            "Program running time: 0 minutes\n",
            "Output path: /content/Auto3D_pkg/example/files/20230222-155817-731514_smiles/smiles_out.sdf\n",
            "/content/Auto3D_pkg/example/files/20230222-155817-731514_smiles/smiles_out.sdf\n",
            "CPU times: user 261 ms, sys: 649 ms, total: 910 ms\n",
            "Wall time: 33.6 s\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wall_time = 34\n",
        "print(f'Seconds per compound: {wall_time/4}')\n",
        "# # patience is important parameter according to Zhen (M2D2 talk)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NKj6-is6zlQ0",
        "outputId": "efe77191-70bf-41b3-b1f8-1c31c180da7c"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Seconds per compound: 8.5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = PandasTools.LoadSDF('/content/Auto3D_pkg/example/files/20230222-155817-731514_smiles/smiles_out.sdf')\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 905
        },
        "id": "pt23mfpD0fx7",
        "outputId": "35f196e8-35ea-434d-d55e-f8b1dd40ad09"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     ID                E_tot                   fmax Converged E_rel(kcal/mol)  \\\n",
              "0  smi1   -479.9679257386429  0.0028632120229303837      True             0.0   \n",
              "1  smi2  -232.66908617406136   0.002958697732537985      True             0.0   \n",
              "2  smi3  -346.07272607393577  0.0028641908429563046      True             0.0   \n",
              "3  smi4  -349.49279513970663   0.002949257381260395      True             0.0   \n",
              "\n",
              "                                              ROMol  \n",
              "0  <rdkit.Chem.rdchem.Mol object at 0x7fd428bd86d0>  \n",
              "1  <rdkit.Chem.rdchem.Mol object at 0x7fd428bd87b0>  \n",
              "2  <rdkit.Chem.rdchem.Mol object at 0x7fd428bd8820>  \n",
              "3  <rdkit.Chem.rdchem.Mol object at 0x7fd428bd8890>  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0f659d66-f707-4a45-9489-c27b9f992272\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>E_tot</th>\n",
              "      <th>fmax</th>\n",
              "      <th>Converged</th>\n",
              "      <th>E_rel(kcal/mol)</th>\n",
              "      <th>ROMol</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>smi1</td>\n",
              "      <td>-479.9679257386429</td>\n",
              "      <td>0.0028632120229303837</td>\n",
              "      <td>True</td>\n",
              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>smi2</td>\n",
              "      <td>-232.66908617406136</td>\n",
              "      <td>0.002958697732537985</td>\n",
              "      <td>True</td>\n",
              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>smi3</td>\n",
              "      <td>-346.07272607393577</td>\n",
              "      <td>0.0028641908429563046</td>\n",
              "      <td>True</td>\n",
              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>smi4</td>\n",
              "      <td>-349.49279513970663</td>\n",
              "      <td>0.002949257381260395</td>\n",
              "      <td>True</td>\n",
              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0f659d66-f707-4a45-9489-c27b9f992272')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%time\n",
        "smiles_file = './Auto3D_pkg/example/files/smiles.smi'\n",
        "if __name__ == \"__main__\":\n",
        "    path = smiles_file\n",
        "    args = options(path, k=1, use_gpu=True, patience=100)   #specify the parameters for Auto3D \n",
        "    out = main(args)            #main acceps the parameters and run Auto3D\n",
        "    print(out)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "clPSJFWl1wGa",
        "outputId": "2a6a591e-8bbc-4cba-af02-cf5d4c129670"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:\n",
            "             _              _             _____   ____  \n",
            "            / \\     _   _  | |_    ___   |___ /  |  _ \\ \n",
            "           / _ \\   | | | | | __|  / _ \\    |_ \\  | | | |\n",
            "          / ___ \\  | |_| | | |_  | (_) |  ___) | | |_| |\n",
            "         /_/   \\_\\  \\__,_|  \\__|  \\___/  |____/  |____/  2.0\n",
            "                // Automatic generation of the low-energy 3D structures                                      \n",
            "        \n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:                               INPUT PARAMETERS\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:path: ./Auto3D_pkg/example/files/smiles.smi\n",
            "INFO:auto3d:k: 1\n",
            "INFO:auto3d:window: False\n",
            "INFO:auto3d:verbose: False\n",
            "INFO:auto3d:job_name: 20230222-155940-304635\n",
            "INFO:auto3d:enumerate_tautomer: False\n",
            "INFO:auto3d:tauto_engine: rdkit\n",
            "INFO:auto3d:pKaNorm: True\n",
            "INFO:auto3d:isomer_engine: rdkit\n",
            "INFO:auto3d:enumerate_isomer: True\n",
            "INFO:auto3d:mode_oe: classic\n",
            "INFO:auto3d:mpi_np: 4\n",
            "INFO:auto3d:max_confs: None\n",
            "INFO:auto3d:use_gpu: True\n",
            "INFO:auto3d:capacity: 42\n",
            "INFO:auto3d:gpu_idx: 0\n",
            "INFO:auto3d:optimizing_engine: AIMNET\n",
            "INFO:auto3d:patience: 100\n",
            "INFO:auto3d:opt_steps: 5000\n",
            "INFO:auto3d:convergence_threshold: 0.003\n",
            "INFO:auto3d:threshold: 0.3\n",
            "INFO:auto3d:memory: None\n",
            "INFO:auto3d:batchsize_atoms: 1024\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:                               RUNNING PROCESS\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:Checking input file...\n",
            "INFO:auto3d:\tThere are 4 SMILES in the input file ./Auto3D_pkg/example/files/smiles.smi. \n",
            "\tAll SMILES and IDs are valid.\n",
            "INFO:auto3d:Suggestions for choosing isomer_engine and optimizing_engine: \n",
            "INFO:auto3d:\tIsomer engine options: RDKit and Omega.\n",
            "INFO:auto3d:\tOptimizing engine options: ANI2x, ANI2xt and AIMNET.\n",
            "INFO:auto3d:The available memory is 15 GB.\n",
            "INFO:auto3d:The task will be divided into 1 jobs.\n",
            "INFO:auto3d:Job1, number of inputs: 4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Checking input file...\n",
            "\tThere are 4 SMILES in the input file ./Auto3D_pkg/example/files/smiles.smi. \n",
            "\tAll SMILES and IDs are valid.\n",
            "Suggestions for choosing isomer_engine and optimizing_engine: \n",
            "\tIsomer engine options: RDKit and Omega.\n",
            "\tOptimizing engine options: ANI2x, ANI2xt and AIMNET.\n",
            "The available memory is 15 GB.\n",
            "The task will be divided into 1 jobs.\n",
            "Job1, number of inputs: 4\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:Energy unit: Hartree if implicit.\n",
            "INFO:auto3d:Program running time: 0 minutes\n",
            "INFO:auto3d:Output path: /content/Auto3D_pkg/example/files/20230222-155940-304635_smiles/smiles_out.sdf\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Energy unit: Hartree if implicit.\n",
            "Program running time: 0 minutes\n",
            "Output path: /content/Auto3D_pkg/example/files/20230222-155940-304635_smiles/smiles_out.sdf\n",
            "/content/Auto3D_pkg/example/files/20230222-155940-304635_smiles/smiles_out.sdf\n",
            "CPU times: user 175 ms, sys: 70 ms, total: 245 ms\n",
            "Wall time: 16.7 s\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wall_time = 17\n",
        "print(f'Seconds per compound: {wall_time/4}')\n",
        "# # patience is important parameter according to Zhen (M2D2 talk)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Z7vRsVGC4tr",
        "outputId": "15d7d09c-2e4b-4123-e2c6-120f252eebac"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Seconds per compound: 4.25\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = PandasTools.LoadSDF('/content/Auto3D_pkg/example/files/20230222-155940-304635_smiles/smiles_out.sdf')\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 905
        },
        "id": "en0Cy6OKC83a",
        "outputId": "5f4970ae-0564-4551-e768-46a5805988a8"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     ID                E_tot                   fmax Converged E_rel(kcal/mol)  \\\n",
              "0  smi1    -479.967925682787  0.0028751068748533726      True             0.0   \n",
              "1  smi2   -232.6690861473655   0.002975183306261897      True             0.0   \n",
              "2  smi3  -346.07272605476953  0.0028248142916709185      True             0.0   \n",
              "3  smi4   -349.4903122393265  0.0029992631170898676      True             0.0   \n",
              "\n",
              "                                              ROMol  \n",
              "0  <rdkit.Chem.rdchem.Mol object at 0x7fd428be93c0>  \n",
              "1  <rdkit.Chem.rdchem.Mol object at 0x7fd428be96d0>  \n",
              "2  <rdkit.Chem.rdchem.Mol object at 0x7fd428be94a0>  \n",
              "3  <rdkit.Chem.rdchem.Mol object at 0x7fd428be92e0>  "
            ],
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              "<style scoped>\n",
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>E_tot</th>\n",
              "      <th>fmax</th>\n",
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              "      <td>-479.967925682787</td>\n",
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              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>smi2</td>\n",
              "      <td>-232.6690861473655</td>\n",
              "      <td>0.002975183306261897</td>\n",
              "      <td>True</td>\n",
              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>smi3</td>\n",
              "      <td>-346.07272605476953</td>\n",
              "      <td>0.0028248142916709185</td>\n",
              "      <td>True</td>\n",
              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>smi4</td>\n",
              "      <td>-349.4903122393265</td>\n",
              "      <td>0.0029992631170898676</td>\n",
              "      <td>True</td>\n",
              "      <td>0.0</td>\n",
              "      <td style=\"text-align: center;\"><div style=\"width: 200px; height: 200px\" data-content=\"rdkit/molecule\"><img src=\"data:image/png;base64,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\" alt=\"Mol\"/></div></td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-407e15ff-9dc3-4cbf-ba48-b4d570f0ac2a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-407e15ff-9dc3-4cbf-ba48-b4d570f0ac2a button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-407e15ff-9dc3-4cbf-ba48-b4d570f0ac2a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Testing Auto3D: drug-like compounds"
      ],
      "metadata": {
        "id": "u5yi9TJ41PLR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c0eKAROwDEaI",
        "outputId": "99325939-cd79-41f4-9c98-469435937a2c"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%time\n",
        "smiles_file = '/content/gdrive/MyDrive/gcollab/data/chembl_drugs_lite_20230221_test.smi'\n",
        "if __name__ == \"__main__\":\n",
        "    path = smiles_file\n",
        "    args = options(path, k=1, use_gpu=True, patience=100)   #specify the parameters for Auto3D \n",
        "    out = main(args)            #main acceps the parameters and run Auto3D\n",
        "    print(out)"
      ],
      "metadata": {
        "id": "enuoANNEWnOJ",
        "outputId": "f826653b-94cd-4fbe-fdd9-1536803551e3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:\n",
            "             _              _             _____   ____  \n",
            "            / \\     _   _  | |_    ___   |___ /  |  _ \\ \n",
            "           / _ \\   | | | | | __|  / _ \\    |_ \\  | | | |\n",
            "          / ___ \\  | |_| | | |_  | (_) |  ___) | | |_| |\n",
            "         /_/   \\_\\  \\__,_|  \\__|  \\___/  |____/  |____/  2.0\n",
            "                // Automatic generation of the low-energy 3D structures                                      \n",
            "        \n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:                               INPUT PARAMETERS\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:path: /content/gdrive/MyDrive/gcollab/data/chembl_drugs_lite_20230221_test.smi\n",
            "INFO:auto3d:k: 1\n",
            "INFO:auto3d:window: False\n",
            "INFO:auto3d:verbose: False\n",
            "INFO:auto3d:job_name: 20230222-160208-411749\n",
            "INFO:auto3d:enumerate_tautomer: False\n",
            "INFO:auto3d:tauto_engine: rdkit\n",
            "INFO:auto3d:pKaNorm: True\n",
            "INFO:auto3d:isomer_engine: rdkit\n",
            "INFO:auto3d:enumerate_isomer: True\n",
            "INFO:auto3d:mode_oe: classic\n",
            "INFO:auto3d:mpi_np: 4\n",
            "INFO:auto3d:max_confs: None\n",
            "INFO:auto3d:use_gpu: True\n",
            "INFO:auto3d:capacity: 42\n",
            "INFO:auto3d:gpu_idx: 0\n",
            "INFO:auto3d:optimizing_engine: AIMNET\n",
            "INFO:auto3d:patience: 100\n",
            "INFO:auto3d:opt_steps: 5000\n",
            "INFO:auto3d:convergence_threshold: 0.003\n",
            "INFO:auto3d:threshold: 0.3\n",
            "INFO:auto3d:memory: None\n",
            "INFO:auto3d:batchsize_atoms: 1024\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:                               RUNNING PROCESS\n",
            "INFO:auto3d:================================================================================\n",
            "INFO:auto3d:Checking input file...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Checking input file...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:\tThere are 10 SMILES in the input file /content/gdrive/MyDrive/gcollab/data/chembl_drugs_lite_20230221_test.smi. \n",
            "\tAll SMILES and IDs are valid.\n",
            "INFO:auto3d:Suggestions for choosing isomer_engine and optimizing_engine: \n",
            "INFO:auto3d:\tIsomer engine options: RDKit and Omega.\n",
            "INFO:auto3d:\tOptimizing engine options: ANI2x, ANI2xt and AIMNET.\n",
            "INFO:auto3d:The available memory is 15 GB.\n",
            "INFO:auto3d:The task will be divided into 1 jobs.\n",
            "INFO:auto3d:Job1, number of inputs: 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\tThere are 10 SMILES in the input file /content/gdrive/MyDrive/gcollab/data/chembl_drugs_lite_20230221_test.smi. \n",
            "\tAll SMILES and IDs are valid.\n",
            "Suggestions for choosing isomer_engine and optimizing_engine: \n",
            "\tIsomer engine options: RDKit and Omega.\n",
            "\tOptimizing engine options: ANI2x, ANI2xt and AIMNET.\n",
            "The available memory is 15 GB.\n",
            "The task will be divided into 1 jobs.\n",
            "Job1, number of inputs: 10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:auto3d:Energy unit: Hartree if implicit.\n",
            "INFO:auto3d:Program running time: 1 minutes\n",
            "INFO:auto3d:Output path: /content/gdrive/MyDrive/gcollab/data/20230222-160208-411749_chembl_drugs_lite_20230221_test/chembl_drugs_lite_20230221_test_out.sdf\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Energy unit: Hartree if implicit.\n",
            "Program running time: 1 minutes\n",
            "Output path: /content/gdrive/MyDrive/gcollab/data/20230222-160208-411749_chembl_drugs_lite_20230221_test/chembl_drugs_lite_20230221_test_out.sdf\n",
            "/content/gdrive/MyDrive/gcollab/data/20230222-160208-411749_chembl_drugs_lite_20230221_test/chembl_drugs_lite_20230221_test_out.sdf\n",
            "CPU times: user 528 ms, sys: 117 ms, total: 645 ms\n",
            "Wall time: 1min 48s\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wall_time = 60 + 48\n",
        "print(f'Seconds per compound: {wall_time/10} ')\n",
        "# patience is important parameter according to Zhen (M2D2 talk)\n",
        "# 450 is an overkill"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mNHmAX_GyX4L",
        "outputId": "00dd1cb3-46e9-48dd-ecc9-1183746465d4"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Seconds per compound: 10.8 \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f = '/content/gdrive/MyDrive/gcollab/data/20230222-160208-411749_chembl_drugs_lite_20230221_test/chembl_drugs_lite_20230221_test_out.sdf'\n",
        "df_drugs_test_3D = PandasTools.LoadSDF(f)"
      ],
      "metadata": {
        "id": "PyAt_QY9oWFd"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for m in df_drugs_test_3D['ROMol'].values:\n",
        "  n = mol_clashes(m)\n",
        "  if n > 0:\n",
        "    print('Molecule has clashes')"
      ],
      "metadata": {
        "id": "4KgBQjuHpAkS"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "options = [(name, value) for name, value in zip(df_drugs_test_3D['ID'], df_drugs_test_3D['ROMol'].values)]\n",
        "dropdown = Dropdown(options=options)\n",
        "p = py3Dmol.view(width=600,height=600)\n",
        "interact(drawit, m=dropdown, p=fixed(p));\n",
        "# apologies, I removed common names for those compounds...\n",
        "# also, take into account that those conformations are for the gas phase\n",
        "# PS: all looks good to me"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 649,
          "referenced_widgets": [
            "1d4f58506f374417b9d39e10dd722a01",
            "0885787e65024c2ba3de90397ba1bc15",
            "17cb4e896c7a4a8985e68d91476b81a5",
            "1b9b00e4a8f049418ccdeb15d8854ab4",
            "2b1b56dd43754ec8b1e97d06191660b7",
            "a55942726bac40e18e1473abc5df60bf",
            "a049cd06b8fc4224b01f41accd98d982"
          ]
        },
        "id": "ERmSiS5-vYTP",
        "outputId": "173bc41c-9a26-48e3-81d9-2373b5eff7f4"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "interactive(children=(Dropdown(description='m', options=(('CHEMBL1537', <rdkit.Chem.rdchem.Mol object at 0x7fd…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1d4f58506f374417b9d39e10dd722a01"
            }
          },
          "metadata": {}
        }
      ]
    }
  ]
}