2023_03_13_Testing_Jazzy_for_solubility_prediction.ipynb

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        "Vdp9bADQCmM0"
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      "authorship_tag": "ABX9TyOZxQVrT0KgsS3oJb7mhSep",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/chupvl/gcolab/blob/main/2023_03_13_Testing_Jazzy_for_solubility_prediction.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2023-03-13: Solubility prediction using Jazzy features (hydration free energies)"
      ],
      "metadata": {
        "id": "smV7ZnFSCk4v"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Goal**: testing if free energy of hydration (without free parameters) from Jazzy have an impact on prediction of compound solubility.\n",
        "\n",
        "Data is taken from [SolCuration](https://github.com/Mengjintao/SolCuration/), that's a derivate from Meng et al [paper](https://www.nature.com/articles/s41597-022-01154-3) + additional datasets. Median is taken for measurments and compounds with SD > 0.5 are removed.\n",
        "\n",
        "**TLDR**: Jazzy descriptors does not have positive impact on solubility prediction.\n",
        "\n",
        "**Links**:\n",
        "* [Paper](https://www.nature.com/articles/s41598-023-30089-x)\n",
        "* [Jazzy RTD](https://jazzy.readthedocs.io/en/latest/cookbook.html)\n",
        "* [Jazzy Github](https://github.com/AstraZeneca/jazzy)"
      ],
      "metadata": {
        "id": "2lvCzawNDdOE"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Libs: installation"
      ],
      "metadata": {
        "id": "Vdp9bADQCmM0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install jazzy -q"
      ],
      "metadata": {
        "id": "e1ZgicQFDOnu",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "01ca6800-85d7-490a-df6e-1f04ec6264cb"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[?25h  Building wheel for optuna (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for pyperclip (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install rdkit -q"
      ],
      "metadata": {
        "id": "SL53qY7WEWoX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cfe43999-967c-4dce-d455-697da54a4318"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m29.4/29.4 MB\u001b[0m \u001b[31m32.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install kallisto"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_VYXASwgW4Oz",
        "outputId": "ff0d5b9d-85bb-4223-9b82-bb14067ba07f"
      },
      "execution_count": 3,
      "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: kallisto in /usr/local/lib/python3.9/dist-packages (1.0.9)\n",
            "Requirement already satisfied: numpy<2.0.0,>=1.19.0 in /usr/local/lib/python3.9/dist-packages (from kallisto) (1.22.4)\n",
            "Requirement already satisfied: click<9.0.0,>=8.0.0 in /usr/local/lib/python3.9/dist-packages (from kallisto) (8.0.4)\n",
            "Requirement already satisfied: scipy==1.9.2 in /usr/local/lib/python3.9/dist-packages (from kallisto) (1.9.2)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install catboost\n",
        "# it's faster compared to xgboost"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fZQEEkit89yu",
        "outputId": "0bcbd85b-e5d1-4821-d964-07aa33444708"
      },
      "execution_count": 4,
      "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 catboost\n",
            "  Downloading catboost-1.1.1-cp39-none-manylinux1_x86_64.whl (76.6 MB)\n",
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            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.9/dist-packages (from catboost) (1.4.4)\n",
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            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib->catboost) (4.39.0)\n",
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            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib->catboost) (1.4.4)\n",
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            "Requirement already satisfied: tenacity>=6.2.0 in /usr/local/lib/python3.9/dist-packages (from plotly->catboost) (8.2.2)\n",
            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib->catboost) (3.15.0)\n",
            "Installing collected packages: catboost\n",
            "Successfully installed catboost-1.1.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Libs"
      ],
      "metadata": {
        "id": "mNdLkwEgA1z3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from rdkit import Chem\n",
        "from rdkit.Chem import AllChem\n",
        "from rdkit.Chem import Draw\n",
        "from rdkit.Chem import Descriptors\n",
        "from rdkit.Chem.MolStandardize import rdMolStandardize\n",
        "from rdkit.Chem.Draw import IPythonConsole\n",
        "IPythonConsole.ipython_3d = True\n",
        "from rdkit.Chem.Draw import MolsToGridImage\n",
        "\n",
        "import numpy as np\n",
        "import xgboost as xgb\n",
        "import pandas as pd\n",
        "\n",
        "from sklearn.model_selection import KFold\n",
        "from sklearn.metrics import r2_score\n",
        "from sklearn.metrics import mean_absolute_percentage_error\n",
        "from sklearn.metrics import mean_squared_error"
      ],
      "metadata": {
        "id": "zhh6jkilGYBf"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# testing Jazzy\n",
        "from jazzy.api import molecular_vector_from_smiles\n",
        "from jazzy.api import deltag_from_smiles\n",
        "\n",
        "molecular_vector_from_smiles(\"CC(=O)NC1=CC=C(C=C1)O\")\n",
        "# working just fine\n",
        "# dgtot - Gibbs free energy of hydration (kJ/mol)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J2mqeBdWENft",
        "outputId": "4331d07b-a684-40e5-cdf0-1c9e3ef06e56"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'sdc': 4.2936,\n",
              " 'sdx': 1.4202,\n",
              " 'sa': 2.461,\n",
              " 'dga': -3.0141,\n",
              " 'dgp': -51.5689,\n",
              " 'dgtot': -54.583}"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "*   dgtot - Gibbs free energy of hydration (kJ/mol)\n",
        "*   sdc - sum of C–H donor strengths\n",
        "*   sdx - sum of X–H donor strengths where X is any non-carbon atom\n",
        "*   sa - sum of all atomic acceptor strengths\n",
        "*   dga\n",
        "*   dgp\n",
        "*   dgtot"
      ],
      "metadata": {
        "id": "cnbTFHcgA-Vb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def smiles_std(smiles):\n",
        "  try:\n",
        "    smiles = rdMolStandardize.StandardizeSmiles(smiles)\n",
        "    lfc = rdMolStandardize.LargestFragmentChooser()\n",
        "    mol_std = lfc.choose(Chem.MolFromSmiles(smiles))\n",
        "    smiles_std = Chem.MolToSmiles(mol_std)\n",
        "    return smiles_std\n",
        "  except:\n",
        "    return None"
      ],
      "metadata": {
        "id": "oUKid-ecGz9j"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def rdkit_calc_2d_descriptors(smiles):\n",
        "    \"\"\"\n",
        "    Calculates all possible chemical descriptors for a given molecule and returns them as a dictionary.\n",
        "    \n",
        "    Args:\n",
        "        molecule (str): A string representation of a molecule in SMILES format.\n",
        "        \n",
        "    Returns:\n",
        "        dict: A dictionary of all possible chemical descriptors for the molecule, with None values for descriptors that could not be calculated.\n",
        "    \"\"\"\n",
        "    descriptors = { descriptor:None for descriptor, function in Descriptors.descList }\n",
        "    try:\n",
        "      mol = Chem.MolFromSmiles(smiles)\n",
        "      descriptors = { descriptor:function(mol) for descriptor, function in Descriptors.descList }\n",
        "      return descriptors\n",
        "    except:\n",
        "      return descriptors"
      ],
      "metadata": {
        "id": "qFw1P5nWY6YJ"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_fp(smiles):\n",
        "  fp = AllChem.GetMorganFingerprintAsBitVect(Chem.MolFromSmiles(smiles), useChirality=False, radius=3, nBits = 1024)\n",
        "  return np.array(fp)"
      ],
      "metadata": {
        "id": "4mwNga2js3lL"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data: prep"
      ],
      "metadata": {
        "id": "2HlPRvY6CnbJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "datasets = {}\n",
        "datasets['aqsol'] = pd.read_csv('https://raw.githubusercontent.com/Mengjintao/SolCuration/master/cure/aqsol_cure.csv')\n",
        "datasets['chembl'] = pd.read_csv('https://raw.githubusercontent.com/Mengjintao/SolCuration/master/cure/chembl_cure.csv')\n",
        "datasets['esol'] = pd.read_csv('https://raw.githubusercontent.com/Mengjintao/SolCuration/master/cure/esol_cure.csv')\n",
        "datasets['oechem'] = pd.read_csv('https://raw.githubusercontent.com/Mengjintao/SolCuration/master/cure/ochem_cure.csv')\n",
        "datasets['phys'] = pd.read_csv('https://raw.githubusercontent.com/Mengjintao/SolCuration/master/cure/phys_cure.csv')"
      ],
      "metadata": {
        "id": "2fABuqKGBpqV"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "for k,v in datasets.items():\n",
        "  v['smiles_std'] = [smiles_std(s) for s in v['smiles']]\n",
        "  v['dataset'] = k\n",
        "  datasets[k] = v"
      ],
      "metadata": {
        "id": "AbpVyc_9Bpw9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.concat(datasets.values())\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "42w4t3SaEiRa",
        "outputId": "0633aea2-bce7-4540-f747-950de3297a6a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          smiles     logS  weight     smiles_std dataset\n",
              "0  B12B3B4B1C234 -4.74240   0.250  B12B3B4B1C234   aqsol\n",
              "1      Br/C=C/Br -1.47611   0.675      Br/C=C/Br   aqsol\n",
              "2      Br/C=C\\Br -1.36389   0.675      Br/C=C\\Br   aqsol\n",
              "3  BrC(Br)(Br)Br -3.14005   1.000  BrC(Br)(Br)Br   aqsol\n",
              "4      BrC(Br)Br -1.88302   1.000      BrC(Br)Br   aqsol"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-11bad7b7-d274-47b2-9c4d-eeebacab2887\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>smiles</th>\n",
              "      <th>logS</th>\n",
              "      <th>weight</th>\n",
              "      <th>smiles_std</th>\n",
              "      <th>dataset</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>B12B3B4B1C234</td>\n",
              "      <td>-4.74240</td>\n",
              "      <td>0.250</td>\n",
              "      <td>B12B3B4B1C234</td>\n",
              "      <td>aqsol</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Br/C=C/Br</td>\n",
              "      <td>-1.47611</td>\n",
              "      <td>0.675</td>\n",
              "      <td>Br/C=C/Br</td>\n",
              "      <td>aqsol</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Br/C=C\\Br</td>\n",
              "      <td>-1.36389</td>\n",
              "      <td>0.675</td>\n",
              "      <td>Br/C=C\\Br</td>\n",
              "      <td>aqsol</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>BrC(Br)(Br)Br</td>\n",
              "      <td>-3.14005</td>\n",
              "      <td>1.000</td>\n",
              "      <td>BrC(Br)(Br)Br</td>\n",
              "      <td>aqsol</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>BrC(Br)Br</td>\n",
              "      <td>-1.88302</td>\n",
              "      <td>1.000</td>\n",
              "      <td>BrC(Br)Br</td>\n",
              "      <td>aqsol</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-11bad7b7-d274-47b2-9c4d-eeebacab2887')\"\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",
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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",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-11bad7b7-d274-47b2-9c4d-eeebacab2887 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-11bad7b7-d274-47b2-9c4d-eeebacab2887');\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",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['dataset'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DSylpyDgFOWy",
        "outputId": "4b9f374c-f61f-4b00-8abe-1725496df696"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "chembl    28675\n",
              "aqsol      9061\n",
              "oechem     3766\n",
              "phys       2001\n",
              "esol       1157\n",
              "Name: dataset, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_mod = df.groupby('smiles_std')['logS'].agg(['median', 'std']).reset_index()\n",
        "print(df_mod.shape)\n",
        "df_mod.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224
        },
        "id": "I-XhfBYiFNhq",
        "outputId": "5c3b82fe-e6ed-4cba-feb7-6e51c308e695"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(35138, 3)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      smiles_std    median       std\n",
              "0  B12B3B4B1C234 -4.742400       NaN\n",
              "1      Br/C=C/Br -1.398055  0.110386\n",
              "2      Br/C=C\\Br -1.376945  0.018463\n",
              "3  BrC(Br)(Br)Br -3.140000  0.000025\n",
              "4      BrC(Br)Br -1.876355  0.035501"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4d4f04ad-1a12-4f2d-8e95-9e18e7f1a2fa\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>smiles_std</th>\n",
              "      <th>median</th>\n",
              "      <th>std</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>B12B3B4B1C234</td>\n",
              "      <td>-4.742400</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Br/C=C/Br</td>\n",
              "      <td>-1.398055</td>\n",
              "      <td>0.110386</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Br/C=C\\Br</td>\n",
              "      <td>-1.376945</td>\n",
              "      <td>0.018463</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>BrC(Br)(Br)Br</td>\n",
              "      <td>-3.140000</td>\n",
              "      <td>0.000025</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>BrC(Br)Br</td>\n",
              "      <td>-1.876355</td>\n",
              "      <td>0.035501</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4d4f04ad-1a12-4f2d-8e95-9e18e7f1a2fa')\"\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",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
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              "\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-4d4f04ad-1a12-4f2d-8e95-9e18e7f1a2fa 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-4d4f04ad-1a12-4f2d-8e95-9e18e7f1a2fa');\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",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# filling NaN\n",
        "df_mod['std'] = df_mod['std'].fillna(0)\n",
        "#\n",
        "nSTDg1 = df_mod[df_mod['std'] > 1].shape[0]\n",
        "nSTDg05 = df_mod[df_mod['std'] > 0.5].shape[0]\n",
        "print(f'Number of compounds with logS SD > 1: {nSTDg1}')\n",
        "print(f'Number of compounds with logS SD > 0.5: {nSTDg05}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T7HIYGltFNkx",
        "outputId": "bc230a02-bea9-454e-c3c1-e6d0f04c58c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of compounds with logS SD > 1: 888\n",
            "Number of compounds with logS SD > 0.5: 1823\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# dropping compounds with SD > 0.5\n",
        "df_mod = df_mod[df_mod['std'] < 0.5].reset_index(drop=True)\n",
        "df_mod.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9WjOAeKtFNn2",
        "outputId": "bcb85571-418f-4552-cd90-f5f35bd76e4d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(33315, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Eyntc_dj2CPq",
        "outputId": "b9c9783e-4843-4d20-c04d-443f0bf9307b"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_mod.to_csv('/content/gdrive/MyDrive/gcollab/data/jazzy-test/solubility-SolCuration-combined.csv', index=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CcEEdEAcFNq_",
        "outputId": "366d82e5-7650-4571-9b80-ba6d2735cf5f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Descriptors: Jazzy"
      ],
      "metadata": {
        "id": "0tYMGKD4Gzxv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "props = ['sdc', 'sdx', 'sa', 'dga', 'dgp', 'dgtot']\n",
        "def_empty = dict.fromkeys(props, None)"
      ],
      "metadata": {
        "id": "o3v5YqTjWuss"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def molecular_vector_from_smiles_debug(smiles):\n",
        "  try:\n",
        "    return molecular_vector_from_smiles(smiles)\n",
        "  except:\n",
        "    return def_empty"
      ],
      "metadata": {
        "id": "C1Kt6-8kLm_t"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%time\n",
        "# getting Jazzy features\n",
        "X = [ molecular_vector_from_smiles_debug(s) for s in df_mod['smiles_std'].values ]\n",
        "df_X = pd.DataFrame(X)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9bZMOTlrKKlN",
        "outputId": "690a3c4e-2444-4dfc-da93-3207f961b77b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "ERROR:root:The RDKit embedding has failed for the molecule: C/N=C(\\S)NCCCCC(NC(=O)C(Cc1cccc2ccccc12)Cc1cccc2ccccc12)C(=O)NC(CC(C)C)[C@@H](O)CC(=O)NC(CC(C)C)C(=O)NCc1ccccc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C/N=C(\\S)NCCCCC(NC(=O)C(Cc1ccccc1)NS(=O)(=O)N1CCOCC1)C(=O)NC(CC1CCCCC1)[C@@H](O)CC(=O)N1CCOC(CCN)C1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C(C)[C@@H]1CC[C@]2(C(=O)OCc3cn(CC(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@H](CCCNC(=N)N)C(=O)O)nn3)CC[C@]3(C)[C@H](CC[C@@H]4[C@@]5(C)CC[C@H](O)C(C)(C)[C@@H]5CC[C@]43C)[C@@H]12\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C(C)[C@@H]1CC[C@]2(C(=O)OCc3cn(CC(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)O)nn3)CC[C@]3(C)[C@H](CC[C@@H]4[C@@]5(C)CC[C@H](O)C(C)(C)[C@@H]5CC[C@]43C)[C@@H]12\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=CCCCCC[C@H](NC(=O)OC(C)(C)C)C(=O)N[C@H](C(=O)Nc1ccccc1C(=O)NS(=O)(=O)CCCC=C)c1ccc(Oc2cc(OC)nc(-c3ccccc3)n2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=CCCCS(=O)(=O)NC(=O)c1ccccc1NC(=O)[C@@H](NC(=O)[C@@H](NC(=O)OC(C)(C)C)C(C)(C)C)c1ccc(Oc2cc(OC)nc(-c3ccccc3)n2)c(C=C)c1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=CCCCS(=O)(=O)NC(=O)c1ccccc1NC(=O)[C@@H](NC(=O)[C@@H](NC(=O)OC(C)(C)C)C(C)(C)C)c1ccc(Oc2cc(OC)nc(-c3ccccc3)n2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=CCCC[C@](C)(NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@@H](NC(=O)[C@](C)(CCCC=C)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)[C@@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)[C@@H](C)CC)[C@@H](C)CC)C(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=CCOC(=O)[C@]12CCC(C)(C)C[C@H]1C1=CC[C@@H]3[C@@]4(C)CC[C@H](OC(=O)CCc5cn(CC(=O)NCCCC[C@H](NC(=O)CCNC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CO)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CO)NC(=O)[C@H](Cc6cnc[nH]6)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CO)NC(=O)[C@@H](NC(=O)[C@H](Cc6ccc(O)cc6)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CC(N)=O)NC(C)=O)[C@@H](C)O)[C@@H](C)CC)[C@@H](C)CC)C(N)=O)nn5)C(C)(C)[C@@H]4CC[C@@]3(C)[C@]1(C)CC2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=CCOC(=O)[C@]12CC[C@@H](C(=C)C)[C@@H]1[C@H]1CC[C@@H]3[C@@]4(C)CC[C@H](OC(=O)CCc5cn(CC(=O)NCCCC[C@H](NC(=O)CCNC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CO)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CO)NC(=O)[C@H](Cc6cnc[nH]6)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CO)NC(=O)[C@@H](NC(=O)[C@H](Cc6ccc(O)cc6)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CC(N)=O)NC(C)=O)[C@@H](C)O)[C@@H](C)CC)[C@@H](C)CC)C(N)=O)nn5)C(C)(C)[C@@H]4CC[C@@]3(C)[C@]1(C)CC2\n",
            "[03:09:52] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(OCC)nc3c(Br)c(OC)ccc23)CN1C(=O)[C@@H](CC(=O)NC(C)(C)C)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(OCC)nc3c(Br)c(OC)ccc23)CN1C(=O)[C@@H](CC(=O)Nc1ccccc1)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(OCC)nc3c(Cl)cccc23)CN1C(=O)[C@@H](CC(=O)Nc1ccccc1)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2nccc3cc(OC)ccc23)CN1C(=O)[C@@H](NC(=O)NC(C)(C)C)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2nccc3cc(OC)ccc23)CN1C(=O)[C@@H](NC(=O)N[C@H](C(=O)N1CCN(c2ncccn2)CC1)C(C)(C)C)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2nccc3cc(OC)ccc23)CN1C(=O)[C@@H](NC(=O)N[C@H](C(=O)O)C(C)(C)C)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2nccc3cc(OC)ccc23)CN1C(=O)[C@@H](NC(=O)N[C@H](COC)C(C)(C)C)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@](OC)(c2ccc(-c3ccc(OC)cc3)cc2)CN1C(=O)[C@@H](NC(=O)OC1CCCC1)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@](OC)(c2ccc(-c3cccc(OC)c3)cc2)CN1C(=O)[C@@H](NC(=O)OC1CCCC1)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=C[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@](OC)(c2ccc(-c3ccccc3)nc2)CN1C(=O)[C@@H](NC(=O)OC1CCCC1)C(C)(C)C)C(=O)NS(=O)(=O)C1CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C=Cc1cc([C@H](NC(=O)[C@@H](NC(=O)OC(C)(C)C)C(C)(C)C)C(=O)Nc2cccc(C(=O)NS(=O)(=O)c3ccc(C(F)(F)F)cc3)c2)ccc1Oc1cc(OC)nc(-c2ccccc2)n1\n",
            "[03:11:37] UFFTYPER: Unrecognized charge state for atom: 11\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)NC1C(O)CC(OCCOCCOCCNC(=O)O[C@H]2C[C@H]3OC[C@@]3(OC(C)=O)C3[C@H](OC(=O)c4ccccc4)[C@]4(O)C[C@H](OC(=O)[C@H](O)[C@@H](NC(=O)c5ccccc5)c5ccccc5)C(C)=C([C@@H](OC(C)=O)C(=O)[C@@]32C)C4(C)C)(C(=O)O)OC1[C@H](O)[C@@H](O)CO\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1csc2ccccc12)C(=O)N[C@@H](CO)C(=O)N(C)[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCN=C(N)N)C(=O)N1CCC[C@@H]1C(=O)N[C@@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1csc2ccccc12)C(=O)N[C@@H](CO)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCN=C(N)N)C(=O)N1CCC[C@@H]1C(=O)N[C@@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)N[C@@H](Cc1ccc(OCc2ccccc2)cc1)C(=O)N[C@H](C(=O)N[C@@H](CCCCNC(=N)NS(=O)(=O)c1c(C)c(C)c2c(c1C)CCC(C)(C)O2)C(=O)Cc1ccccc1)[C@@H](C)OCc1ccccc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)N[C@@H](Cc1ccc2ccccc2c1)C(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1cccnc1)C(=O)N[C@@H](CO)C(=O)N(C)[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCC(N)C(=O)c1ccncc1)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCC(N)C(C)C)C(=O)N1CCC[C@@H]1C(=O)N[C@@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)N[C@@H](Cc1ccc2ccccc2c1)C(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1cccnc1)C(=O)N[C@@H](CO)C(=O)N(C)[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(N)=O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCN=C(N)N)C(=O)N1CCC[C@@H]1C(=O)N[C@@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)N[C@@H](Cc1ccc2ccccc2c1)C(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1cccnc1)C(=O)N[C@@H](CO)C(=O)N[C@@H](CCCC(N)C(=O)c1cccnc1)C(=O)N[C@@H](CCCC(N)C(=O)c1cccnc1)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCC(N)C(C)C)C(=O)N1CCC[C@@H]1C(=O)N[C@@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)N[C@@H](Cc1ccc2ccccc2c1)C(=O)N[C@@H](Cc1ccc(Cl)cc1)C(=O)N[C@@H](Cc1cccnc1)C(=O)N[C@@H](CO)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(N)=O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCN=C(N)N)C(=O)N1CCC[C@@H]1C(=O)N[C@@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1cc(C(=O)Nc2cn(C)c(C(=O)NCCC(=O)Nc3cn(C)c(C(=O)Nc4cc(C(=O)Nc5cc(C(=O)NCCCC(=O)Nc6cc(C(=O)Nc7cc(C(=O)Nc8cc(C(=O)Nc9cc(C(=O)Nc%10ccc%11[nH]c(C(=O)N%12CC(CCl)c%13c%12cc(OC(=O)NCCCN(C)C)c%12ccccc%13%12)cc%11c%10)n(C)c9)n(C)c8)n(C)c7)n(C)c6)n(C)c5)n(C)c4)n3)n2)n(C)c1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1cc(C(=O)Nc2cn(C)c(C(=O)NCCC(=O)Nc3cn(C)c(C(=O)Nc4cc(C(=O)Nc5cc(C(=O)NCCCC(=O)Nc6cc(C(=O)Nc7cc(C(=O)Nc8cc(C(=O)Nc9cc(C(=O)Nc%10ccc%11[nH]c(C(=O)N%12CC(CCl)c%13c%12cc(OC(=O)[C@@H](N)CCCCN)c%12ccccc%13%12)cc%11c%10)n(C)c9)n(C)c8)n(C)c7)n(C)c6)n(C)c5)n(C)c4)n3)n2)n(C)c1\n",
            "[03:14:06] UFFTYPER: Unrecognized charge state for atom: 56\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@@H](NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)[S+](C)[O-])C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](CCC(N)=O)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)S(=O)(=O)C(C)C)cc1\n",
            "[03:14:09] UFFTYPER: Unrecognized charge state for atom: 102\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](CCC(N)=O)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)[S+]([O-])C(C)C)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](CCC(N)=O)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](SC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](CCC(N)=O)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@H](C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)S(=O)(=O)C(C)C)cc1\n",
            "[03:14:12] UFFTYPER: Unrecognized charge state for atom: 102\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](CCC(N)=O)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@H](C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)[S+]([O-])C(C)C)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](CCC(N)=O)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@H](SC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "[03:14:15] UFFTYPER: Unrecognized charge state for atom: 104\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)[S+]([O-])C(C)C)cc1\n",
            "[03:14:16] UFFTYPER: Unrecognized charge state for atom: 107\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@@H](C(N)=O)[S+](C)[O-])cc1\n",
            "[03:14:18] UFFTYPER: Unrecognized charge state for atom: 107\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C(N)=O)[S+](C)[O-])cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](SC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "[03:14:22] UFFTYPER: Unrecognized charge state for atom: 104\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@H](C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)[S+]([O-])C(C)C)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@H](SC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@H](Cc2ccc3ccccc3c2)NC(C)=O)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](CO)NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@H](NC(C)=O)Sc2ccc3ccccc3c2)C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "[03:14:27] UFFTYPER: Unrecognized charge state for atom: 56\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1ccc(C[C@H](NC(=O)[C@H](NC(=O)[C@@H](Cc2cccnc2)NC(=O)[C@@H](Cc2ccc(Cl)cc2)NC(=O)[C@@H](Cc2ccc3ccccc3c2)NC(C)=O)[S+](C)[O-])C(=O)N[C@H](Cc2ccc(NC(C)=O)cc2)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N2CCC[C@H]2C(=O)N[C@H](C)C(N)=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1cn(C)c(C(=O)Nc2cn(C)c(C(=O)NCCOCCOCC(=O)Nc3cn(C)c(C(=O)Nc4cc(C(=O)Nc5cc(C(=O)NCCCC(=O)Nc6cn(C)c(C(=O)Nc7cc(C(=O)NCCOCCOCC(=O)Nc8cn(C)c(C(=O)Nc9cc(C(=O)Nc%10cc(C(=O)NCCC(=O)NCCCN(C)CCCN)n(C)c%10)n(C)c9)n8)n(C)c7)n6)n(C)c5)n(C)c4)n3)n2)n1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1cn(C)c(C(=O)Nc2cn(C)c(C(=O)NCCOCCOCC(=O)Nc3cn(C)c(C(=O)Nc4cc(C(=O)Nc5cc(C(=O)NCCCC(=O)Nc6cn(C)c(C(=O)Nc7cc(C(=O)Nc8cc(C(=O)NCCC(=O)Nc9cn(C)c(C(=O)Nc%10cc(C(=O)Nc%11cc(C(=O)NCCC(=O)NCCCN(C)CCCN)n(C)c%11)n(C)c%10)n9)n(C)c8)n(C)c7)n6)n(C)c5)n(C)c4)n3)n2)n1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)Nc1cn(C)c(C(=O)Nc2cn(C)c(C(=O)Nc3cc(C(=O)NCCC(=O)Nc4cn(C)c(C(=O)Nc5cc(C(=O)Nc6cc(C(=O)NCCCC(=O)Nc7cn(C)c(C(=O)Nc8cc(C(=O)Nc9cc(C(=O)NCCC(=O)Nc%10cn(C)c(C(=O)Nc%11cc(C(=O)Nc%12cc(C(=O)NCCC(=O)NCCCN(C)CCCN)n(C)c%12)n(C)c%11)n%10)n(C)c9)n(C)c8)n7)n(C)c6)n(C)c5)n4)n(C)c3)n2)n1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@@]2(C)[C@H]([C@H](OC(=O)c3ccccc3)[C@]3(O)C[C@H](OC(=O)[C@H](OC(=O)CCC(=O)NCCCC[C@H](NC(=O)[C@@H]4CCCN4C(=O)CNC(=O)[C@@H]4C[C@@H](O)CN4C(=O)[C@@H]4CCCN4C(=O)CNC(=O)[C@@H]4C[C@@H](O)CN4C(=O)[C@@H]4CCCN4C(=O)CNC(=O)[C@@H]4C[C@@H](O)CN4C(=O)[C@@H]4CCCN4C(=O)CNC(=O)[C@@H]4C[C@@H](O)CN4C(=O)[C@@H]4CCCN4)C(=O)NCC(=O)N4CCC[C@H]4C(=O)N4C[C@H](O)C[C@H]4C(=O)NCC(=O)N4CCC[C@H]4C(=O)N4C[C@@H](O)C[C@H]4C(=O)NCC(=O)N4CCC[C@H]4C(=O)N4C[C@H](O)C[C@H]4C(=O)NCC(=O)N4CCC[C@H]4C(=O)N4C[C@@H](O)C[C@H]4C(=O)NCC(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)NCC(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)NCC(=O)O)[C@@H](NC(=O)c4ccccc4)c4ccccc4)C(C)=C1C3(C)C)[C@]1(OC(C)=O)CO[C@@H]1C[C@@H]2O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@@]2(C)[C@H]([C@H](OC(=O)c3ccccc3)[C@]3(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCOC(=O)C[C@H](O)C(=O)O)[C@@H](NC(=O)c4ccccc4)c4ccccc4)C(C)=C1C3(C)C)[C@]1(OC(C)=O)CO[C@@H]1C[C@@H]2O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@@]2(C)[C@H]([C@H](OC(=O)c3ccccc3)[C@]3(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCOC(=O)[C@@H](N)CC(C)C)[C@@H](NC(=O)c4ccccc4)c4ccccc4)C(C)=C1C3(C)C)[C@]1(OC(C)=O)CO[C@@H]1C[C@@H]2O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@@]2(C)[C@H]([C@H](OC(=O)c3ccccc3)[C@]3(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCOC(=O)[C@@H]4CCCN4)[C@@H](NC(=O)c4ccccc4)c4ccccc4)C(C)=C1C3(C)C)[C@]1(OC(C)=O)CO[C@@H]1C[C@@H]2O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@@]2(C)[C@H]([C@H](OC(=O)c3ccccc3)[C@]3(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCOC(=O)[C@H](C)N)[C@@H](NC(=O)c4ccccc4)c4ccccc4)C(C)=C1C3(C)C)[C@]1(OC(C)=O)CO[C@@H]1C[C@@H]2O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@]2(C)[C@@H](OC(=O)OCCSSCCN)C[C@H]3OC[C@@]3(OC(C)=O)[C@H]2[C@H](OC(=O)c2ccccc2)[C@]2(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCN)[C@@H](NC(=O)c3ccccc3)c3ccccc3)C(C)=C1C2(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@]2(C)[C@@H](OC(=O)OCCSSCCNC(=O)CCC(=O)O)C[C@H]3OC[C@@]3(OC(C)=O)[C@H]2[C@H](OC(=O)c2ccccc2)[C@]2(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCNC(=O)CCC(=O)O)[C@@H](NC(=O)c3ccccc3)c3ccccc3)C(C)=C1C2(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@]2(C)[C@@H](OC(=O)OCCSSCCO)C[C@H]3OC[C@@]3(OC(C)=O)[C@H]2[C@H](OC(=O)c2ccccc2)[C@]2(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCO)[C@@H](NC(=O)c3ccccc3)c3ccccc3)C(C)=C1C2(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C(=O)[C@]2(C)[C@@H](OC(=O)OCCSSCCOC(=O)CCC(=O)O)C[C@H]3OC[C@@]3(OC(C)=O)[C@H]2[C@H](OC(=O)c2ccccc2)[C@]2(O)C[C@H](OC(=O)[C@H](OC(=O)OCCSSCCOC(=O)CCC(=O)O)[C@@H](NC(=O)c3ccccc3)c3ccccc3)C(C)=C1C2(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(=O)O[C@H]1C[C@H]2CC[C@@]1(C)C2(C)C\n",
            "[03:18:34] UFFTYPER: Unrecognized charge state for atom: 14\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(C)(C)[C@H](NC(=O)OCc1ccccc1)C(=O)N[C@@H](Cc1ccccc1)[C@@H](O)[C@@H](NCc1ccc(CNC(=O)Nc2ccccc2)cc1)C(=O)N[C@H]1c2ccccc2C[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(C)(C)[C@H](NC(=O)OCc1ccccc1)C(=O)N[C@@H](Cc1ccccc1)[C@@H](O)[C@@H](NCc1ccc(CNC(=O)OCc2ccccc2)cc1)C(=O)N[C@H]1c2ccccc2C[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(C)(C)[C@H](NC(=O)OCc1ccccc1)C(=O)N[C@@H](Cc1ccccc1)[C@@H](O)[C@@H](NCc1ccc(OCCN2CCOCC2)cc1)C(=O)N[C@H]1c2ccccc2C[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(C)(C)c1cc(CCC(=O)OCC(COC(=O)CCc2cc(C(C)(C)C)c(O)c(C(C)(C)C)c2)(COC(=O)CCc2cc(C(C)(C)C)c(O)c(C(C)(C)C)c2)COC(=O)CCc2cc(C(C)(C)C)c(O)c(C(C)(C)C)c2)cc(C(C)(C)C)c1O\n",
            "[03:21:36] UFFTYPER: Unrecognized charge state for atom: 21\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(C)CCCCCCCCCCCCCCC(=O)OCC(COC(=O)CCCCCCCCCCCCCCC(C)C)(COC(=O)CCCCCCCCCCCCCCC(C)C)COC(=O)CCCCCCCCCCCCCCC(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(C)CCCCCCCCCCCCCCC(=O)OCC(COC(=O)CCCCCCCCCCCCCCC(C)C)OC(=O)CCCCCCCCCCCCCCC(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC(C)CCCCCCCCCCOC(=O)c1ccc(C(=O)OCCCCCCCCCCC(C)C)c(C(=O)OCCCCCCCCCCC(C)C)c1\n",
            "[03:26:25] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[03:26:41] UFFTYPER: Unrecognized charge state for atom: 28\n",
            "[03:27:44] UFFTYPER: Unrecognized charge state for atom: 11\n",
            "[03:29:05] UFFTYPER: Unrecognized charge state for atom: 7\n",
            "[03:29:10] UFFTYPER: Unrecognized atom type: S_6+6 (21)\n",
            "[03:30:49] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:34:25] UFFTYPER: Unrecognized charge state for atom: 24\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC1(C)[C@@H]2CC[C@]1(C)[C@H](O)C2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC1(C)[C@H]2CC[C@@]1(C)C(=O)C2\n",
            "[03:35:24] UFFTYPER: Unrecognized charge state for atom: 28\n",
            "[03:35:28] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "[03:35:28] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "[03:36:05] UFFTYPER: Unrecognized charge state for atom: 20\n",
            "[03:36:06] UFFTYPER: Unrecognized charge state for atom: 20\n",
            "[03:36:06] UFFTYPER: Unrecognized charge state for atom: 20\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC1=C2CC(C=O)C(C1)C(C(C)C)C2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCC(C)CNC(=O)C[C@H](O)C(CC(C)C)NC(=O)C(CCCC/N=C(/S)NC)NC(=O)C(Cc1cccc2ccccc12)Cc1cccc2ccccc12\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCC(COC(=O)CCCCCCCCCCCCCCC(C)C)(COC(=O)CCCCCCCCCCCCCCC(C)C)COC(=O)CCCCCCCCCCCCCCC(C)C\n",
            "[03:38:51] UFFTYPER: Unrecognized atom type: S_6+6 (18)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCC(CC)C(=O)OCC(COC(=O)C(CC)CCCC)(COC(=O)C(CC)CCCC)COC(=O)C(CC)CCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCC(CC)C(=O)OCC(COCC(COC(=O)CCCCCC(C)C)(COC(=O)C(CC)CCCC)COC(=O)C(CC)CCCC)(COC(=O)CCCCCC(C)C)COC(=O)CCCCCC(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCC(CC)COC(=O)c1ccc(Nc2nc(Nc3ccc(C(=O)NC(C)(C)C)cc3)nc(Nc3ccc(C(=O)OCC(CC)CCCC)cc3)n2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCC(CC)COC(=O)c1ccc(Nc2nc(Nc3ccc(C(=O)OCC(CC)CCCC)cc3)nc(Nc3ccc(C(=O)OCC(CC)CCCC)cc3)n2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCC(Cc1cc(C(C)(C)C)c(O)c(C(C)(C)C)c1)(C(=O)OC1CC(C)(C)N(C)C(C)(C)C1)C(=O)OC1CC(C)(C)N(C)C(C)(C)C1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCC(=O)OCCN(CCN(CCOC(=O)CCCCC)CC(=O)N(CC(=O)O)CC(=O)O)CC(=O)N(CC(=O)O)CC(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCC(=O)OCC(COC(=O)CCCCCC)(COC(=O)CCCCCC)COC(=O)CCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCC(O)CCCCCCCCCCC(=O)OCC(COC(=O)CCCCCCCCCCC(O)CCCCCC)OC(=O)CCCCCCCCCCC(O)CCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCC(=O)n1cc(C[C@@H](NC(=O)C[C@@H]2NC(=O)[C@@H]3C4CCC(CC4)N3C2=O)C(=O)N[C@@H](Cc2ccccc2)C(=O)N(C)Cc2ccccc2)c2ccccc21\n",
            "[03:41:31] UFFTYPER: Warning: hybridization set to SP3 for atom 19\n",
            "[03:41:31] UFFTYPER: Unrecognized charge state for atom: 19\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCC/C=C\\CCCCCCCC(=O)OCC(COC(=O)CCCCCCC/C=C\\CCCCCCCC)(COC(=O)CCCCCCC/C=C\\CCCCCCCC)COC(=O)CCCCCCC/C=C\\CCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCC/C=C\\CCCCCCCC(=O)OCC(COC(=O)CCCCCCC/C=C\\CCCCCCCC)OC(=O)CCCCCCC/C=C\\CCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCC(=O)OCC(CC)(COC(=O)CCCCCCCC)COC(=O)CCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCCC/C=C/C/C=C/CCCCCCCCCCCCCCCCCCCCNCCCCCCCCCCC/C=C/C/C=C/CCCCCCCCCCCCCCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCCCCCC(=O)OCC(COC(=O)CCCCCCCCCCCCC)OC(=O)CCCCCCCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCCCCCC(=O)OCCN(CCN(CCOC(=O)CCCCCCCCCCCCC)CC(=O)N(CC(=O)O)CC(=O)O)CC(=O)N(CC(=O)O)CC(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCCCCCCCC(=O)NCCCC[C@H](NC(=O)CCNC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@@H](NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@@H](NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@@H](NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@@H](NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@@H](NC(C)=O)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)[C@@H](C)CC)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCCCCCCCCC(=O)[C@H](CCN[C@@H](CCC(=O)NCCCC[C@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CO)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CO)NC(=O)[C@@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)CNC(=O)[C@H](CCC(N)=O)NC(=O)C(C)(C)NC(=O)[C@@H](N)Cc1cnc[nH]1)[C@@H](C)O)[C@@H](C)O)C(=O)N[C@@H](CC(=O)O)C(=O)N[C@@H](CCC(=O)O)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](C)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](Cc1ccccc1)C(=O)N[C@H](C(=O)N[C@@H](CCC(=O)O)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(=O)N[C@@H](CC(C)C)C(=O)NC(C)(C)C(=O)N[C@@H](C)C(=O)NCC(=O)NCC(=O)N1CCC[C@H]1C(=O)N1CCC[C@H]1C(=O)N[C@@H](CO)C(=O)N[C@@H](C)C(=O)N[C@@H](CCCCN)C(=O)N1CCC[C@H]1C(=O)N1CCC[C@H]1C(=O)N1CCC[C@H]1C(=O)N[C@@H](CCCCN)C(N)=O)[C@@H](C)CC)C(=O)O)C(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCCCCCCCCCC(=O)OCC(COC(=O)CCCCCCCCCCCCCCCCC)OC(=O)CCCCCCCCCCCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCCCCCCCCCC(=O)OCC(OC(=O)CCCCCCCCCCCCCCCCC)[C@H]1OC[C@@H](O)[C@@H]1OC(=O)CCCCCCCCCCCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCCCOC(=O)c1ccc(C(=O)OCCCCCCCCC)c(C(=O)OCCCCCCCCC)c1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCCCOCC(COCCCCCCC)(COCCCCCCC)COCCCCCCC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCC[C@@H]1[C@H](O)[C@@H](O)[C@@H](Cc2ccccc2)N(Cc2cccc(C(=O)Nc3nc4ccccc4[nH]3)c2)C(=O)N1Cc1cccc(C(=O)Nc2nc3ccccc3[nH]2)c1\n",
            "[03:48:01] UFFTYPER: Unrecognized charge state for atom: 6\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCCc1ccc(-c2cc3cn([C@H]4C[C@H](OC(=O)[C@@H](NC(=O)[C@@H]5CCCN5C(=O)[C@@H](N)C(C)C)C(C)C)[C@@H](COC(=O)[C@@H](NC(=O)[C@@H]5CCCN5C(=O)[C@@H](N)C(C)C)C(C)C)O4)c(=O)nc3o2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCCN(c1nc(NCCCN(CCN(CCCNc2nc(N(CCCC)C3CC(C)(C)N(C)C(C)(C)C3)nc(N(CCCC)C3CC(C)(C)N(C)C(C)(C)C3)n2)c2nc(N(CCCC)C3CC(C)(C)N(C)C(C)(C)C3)nc(N(CCCC)C3CC(C)(C)N(C)C(C)(C)C3)n2)c2nc(N(CCCC)C3CC(C)(C)N(C)C(C)(C)C3)nc(N(CCCC)C3CC(C)(C)N(C)C(C)(C)C3)n2)nc(N(CCCC)C2CC(C)(C)N(C)C(C)(C)C2)n1)C1CC(C)(C)N(C)C(C)(C)C1\n",
            "[03:49:28] UFFTYPER: Warning: hybridization set to SP3 for atom 5\n",
            "[03:49:28] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "[03:49:41] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCC[C@H](N[C@@H](Cc1ccccc1)C(=O)N1CCC(OCOC)CC1)C(=O)N[C@@H](CC1CCCCC1)[C@@H](O)C[C@H](C(=O)NCCCNCCO)C(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCCC[C@H](N[C@@H](Cc1ccccc1)C(=O)N1CCC(OCOC)CC1)C(=O)N[C@@H](CC1CCCCC1)[C@@H](O)C[C@H](C(=O)NCCN1CCCCC1)C(C)C\n",
            "[03:50:53] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:53] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:54] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:54] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:54] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:54] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:55] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:55] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:55] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:55] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:56] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:56] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:56] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:57] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:57] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:58] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:58] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:58] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:50:58] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:53:13] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[03:53:29] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCN(CC)CCN(CC12CC(c3ccc(C(F)(F)F)cc3)(C1)C2)C(=O)Cn1c(SCc2ccc(F)cc2)nc(=O)c2c1CCC2\n",
            "[03:55:51] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCN(CC)c1ccc(/C=C2\\CC/C(=C\\c3ccc(N(CCOCCOCCOCCOCCOC)CCOCCOCCOCCOCCOC)cc3)C2=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCN(CC)c1ccc(C=C2CC(=Cc3ccc(N(CCOCCOCCOCCOC)CCOCCOCCOCCOC)cc3)C2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCN(CC)c1ccc(C=C2CC(=Cc3ccc(N(CCOCCOCCOCCOCCOC)CCOCCOCCOCCOCCOC)cc3)C2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CCN(CC)c1ccc2cc(C(=O)/C=C/c3ccc(N(CCOCCOCCOCCOC)CCOCCOCCOCCOC)cc3)c(=O)oc2c1\n",
            "[03:56:54] UFFTYPER: Unrecognized charge state for atom: 11\n",
            "[04:01:34] UFFTYPER: Unrecognized charge state for atom: 10\n",
            "[04:01:38] UFFTYPER: Unrecognized charge state for atom: 13\n",
            "[04:01:40] UFFTYPER: Unrecognized charge state for atom: 11\n",
            "[04:01:41] UFFTYPER: Unrecognized charge state for atom: 10\n",
            "[04:01:41] UFFTYPER: Unrecognized charge state for atom: 10\n",
            "[04:01:44] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "[04:01:44] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "[04:01:44] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[04:01:44] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "[04:01:44] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[04:01:45] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "[04:01:45] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[04:02:51] UFFTYPER: Unrecognized charge state for atom: 21\n",
            "[04:03:07] UFFTYPER: Unrecognized atom type: S_6+6 (16)\n",
            "[04:03:43] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(-c3csc(NC(C)C)n3)nc3c(Cl)c(OC)ccc23)CN1C(=O)[C@@H](NC(=O)O[C@@H]1C[C@@H]2C[C@@H]2C1)C(C)(C)C)C(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(-c3csc(NC(C)C)n3)nc3c(Cl)c(OC)ccc23)CN1C(=O)[C@@H](NC(=O)O[C@@H]1C[C@@H]2[C@H](C1)C2(F)F)C(C)(C)C)C(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(-c3csc(NC(C)C)n3)nc3c(Cl)c(OC)ccc23)CN1C(=O)[C@@H](NC(=O)O[C@H]1C[C@@H]2[C@H](C1)C2(F)F)C(C)(C)C)C(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(-c3csc(NC(C)C)n3)nc3c(Cl)c(OCCN4CCCCC4)ccc23)CN1C(=O)[C@@H](NC(=O)O[C@@H]1C[C@@H]2C[C@@H]2C1)C(C)(C)C)C(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@H]1C[C@]1(NC(=O)[C@@H]1C[C@@H](Oc2cc(-c3csc(NC(C)C)n3)nc3c(Cl)c(OCCN4CC[C@@H](OC)C4)ccc23)CN1C(=O)[C@@H](NC(=O)O[C@@H]1C[C@@H]2C[C@@H]2C1)C(C)(C)C)C(=O)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@]1(OC(=O)OCCSSC[C@H](N)C(=O)NCCCCCC(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](Cc2ccccc2)C(=O)N[C@@H](Cc2ccccc2)C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(N)=O)C(=O)OCc2c1cc1n(c2=O)Cc2cc3ccccc3nc2-1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@]1(OC(=O)OCCSSC[C@H](N)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N2CCC[C@H]2C(=O)N[C@@H](CCCCN)C(=O)N2CCC[C@H]2C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](Cc2ccccc2)C(=O)N[C@@H](Cc2ccccc2)C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(N)=O)C(=O)OCc2c1cc1n(c2=O)Cc2cc3ccccc3nc2-1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@@]1(OC(=O)OCCSSC[C@H](NC(=O)CCCCCNC(=O)[C@@H](N)CSSCCOC(=O)O[C@]2(CC)C(=O)OCc3c2cc2n(c3=O)Cc3cc4ccccc4nc3-2)C(=O)N[C@](N)(CCCNC(=N)N)C(=O)N2CCC[C@H]2C(=O)N[C@@H](CCCCN)C(=O)N2CCC[C@H]2C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](Cc2ccccc2)C(=O)N[C@@H](Cc2ccccc2)C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(N)=O)C(=O)OCc2c1cc1n(c2=O)Cc2cc3ccccc3nc2-1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)CNC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)CNC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCCCN)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@H](N)COC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)CNC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)CNC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CCCCN)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](C)NC(=O)CNC(=O)[C@H](CCCCN)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CO)NC(=O)CNC(=O)[C@@H](NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](C)NC(=O)[C@@H](N)CC(=O)O)C(C)C)C(C)C)C(C)C)C(=O)N[C@H](C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)NCC(=O)NCC(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](C)C(=O)O)[C@@H](C)CC)C(C)C)C(C)C)C(C)C)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)N[C@H]1CCCCNC(=O)C[C@@H](C(N)=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](CC(C)C)NC1=O)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)N[C@H]1CCCCNC(=O)C[C@@H](C(=O)O)NC(=O)[C@H](CC(C)C)NC(=O)CNC(=O)[C@H](CC(C)C)NC1=O)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@H](CCSC)C(=O)N[C@H](C(=O)N[C@H]1CCCCNC(=O)C[C@@H](C(N)=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](CC(C)C)NC1=O)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@@]1(C)CCC/C=C/CCC[C@@](C)(C(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H]([C@@H](C)CC)NC1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@H](C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)[C@@H](C)CC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc1cnc[nH]1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]1CCCN1C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](CCCNC(=N)N)C(=O)N[C@H]1CCCCNC(=O)C[C@@H](C(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCCCN)NC(=O)[C@H]([C@@H](C)CC)NC1=O\n",
            "[04:20:14] UFFTYPER: Unrecognized charge state for atom: 10\n",
            "[04:20:15] UFFTYPER: Unrecognized charge state for atom: 9\n",
            "[04:20:15] UFFTYPER: Unrecognized charge state for atom: 9\n",
            "[04:20:16] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:17] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:17] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:17] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:18] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:18] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:18] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:19] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:19] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:19] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:20] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:20] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:20] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:21] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:21] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:21] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:22] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:22] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:22] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:23] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:23] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:23] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:24] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:20:24] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H]1OC(=O)[C@H](C)[C@@H](O[C@H]2C[C@@](C)(OC)[C@@H](O)[C@H](C)O2)[C@H](C)[C@@H](O[C@@H]2O[C@H](C)C[C@H](N(C)C)[C@H]2OCCC(=O)NCCNc2ccnc3cc(Cl)ccc23)[C@](C)(O)C[C@@H](C)CN(C)[C@H](C)[C@@H](O)[C@]1(C)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H]1OC(=O)[C@H](C)[C@@H](O[C@H]2C[C@@](C)(OC)[C@@H](O)[C@H](C)O2)[C@H](C)[C@@H](O[C@@H]2O[C@H](C)C[C@H](N(C)C)[C@H]2OCCCNC(=O)CNc2ccnc3cc(Cl)ccc23)[C@](C)(O)C[C@@H](C)CN(C)[C@H](C)[C@@H](O)[C@]1(C)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H]1OC(=O)[C@H](C)[C@@H](O[C@H]2C[C@@](C)(OC)[C@@H](O)[C@H](C)O2)[C@H](C)[C@@H](O[C@@H]2O[C@H](C)C[C@H](N(C)C)[C@H]2OCCCNCc2ccc3ccccc3n2)[C@](C)(O)C[C@@H](C)CN(C)[C@H](C)[C@@H](O)[C@]1(C)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H]1OC(=O)[C@H](C)[C@@H](O[C@H]2C[C@@](C)(OC)[C@@H](O)[C@H](C)O2)[C@H](C)[C@@H](O[C@@H]2O[C@H](C)C[C@H](N(C)C)[C@H]2OCCCNCc2ccnc3ccccc23)[C@](C)(O)C[C@@H](C)CN(C)[C@H](C)[C@@H](O)[C@]1(C)O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CC[C@H]1OC(=O)[C@H](C)[C@@H](O[C@H]2C[C@@](C)(OC)[C@@H](O)[C@H](C)O2)[C@H](C)[C@@H](O[C@@H]2O[C@H](C)C[C@H](N(C)C)[C@H]2OCCCNCc2cnc3ccccc3c2)[C@](C)(O)C[C@@H](C)CN(C)[C@H](C)[C@@H](O)[C@]1(C)O\n",
            "[04:21:15] UFFTYPER: Unrecognized charge state for atom: 2\n",
            "[04:21:16] UFFTYPER: Unrecognized charge state for atom: 2\n",
            "[04:21:16] UFFTYPER: Unrecognized charge state for atom: 2\n",
            "[04:21:16] UFFTYPER: Unrecognized charge state for atom: 2\n",
            "[04:22:41] UFFTYPER: Unrecognized atom type: S_6+6 (15)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN(C)c1ccc(C[C@@H]2[C@H](O)[C@@H](O)[C@@H](Cc3ccc(N(C)C)cc3)N(Cc3cccc(C(=O)Nc4nc5ccccc5[nH]4)c3)C(=O)N2Cc2cccc(C(=O)Nc3nc4ccccc4[nH]3)c2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN(Cc1ccccc1)C(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](Cc1cn(C(=O)CCCCCCN)c2ccccc12)NC(=O)C[C@@H]1NC(=O)[C@@H]2C3CCC(CC3)N2C1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN(Cc1ccccc1)C(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](Cc1cn(C(=O)OC(C)(C)C)c2ccccc12)NC(=O)C[C@@H]1NC(=O)[C@@H]2C3CCC(CC3)N2C1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN(Cc1ccccc1)C(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](Cc1cn(C(=O)OCCCCCCN)c2ccccc12)NC(=O)C[C@@H]1NC(=O)[C@@H]2C3CCC(CC3)N2C1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN(Cc1ccccc1)C(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](Cc1cn(C(=O)OCc2ccccc2)c2ccccc12)NC(=O)C[C@@H]1NC(=O)[C@@H]2C3CCC(CC3)N2C1=O\n",
            "[04:28:16] UFFTYPER: Unrecognized charge state for atom: 24\n",
            "[04:28:47] UFFTYPER: Unrecognized charge state for atom: 10\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN1C(C)(C)CC(OC(=O)CC(C(=O)OC2CC(C)(C)N(C)C(C)(C)C2)C(CC(=O)OC2CC(C)(C)N(C)C(C)(C)C2)C(=O)OC2CC(C)(C)N(C)C(C)(C)C2)CC1(C)C\n",
            "[04:32:04] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[04:33:58] UFFTYPER: Unrecognized charge state for atom: 10\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN[C@H](CC(C)C)C(=O)N[C@H]1C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]2C(=O)N[C@H]3C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c4cc(O)cc(O)c4-c4cc3ccc4O)[C@H](O)c3ccc(c(Cl)c3)Oc3cc2cc(c3OC2OC(CO)C(O)C(O)C2OC2CC(C)(NC(=O)OCc3cc(C)c(OC(=O)C(C)NC(=O)COCCO)c(C)c3)C(O)C(C)O2)Oc2ccc(cc2Cl)[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN[C@H](CC(C)C)C(=O)N[C@H]1C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]2C(=O)N[C@H]3C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c4cc(O)cc(O)c4-c4cc3ccc4O)[C@H](O)c3ccc(c(Cl)c3)Oc3cc2cc(c3OC2OC(CO)C(O)C(O)C2OC2CC(C)(NC(=O)OCc3cc(C)c(OC(=O)CNC(=O)CC(NC(=O)COCCO)C(=O)NCC(=O)Oc4c(C)cc(COC(=O)NC5(C)CC(OC6C(Oc7c8cc9cc7Oc7ccc(cc7Cl)[C@@H](O)[C@@H](NC(=O)[C@@H](CC(C)C)NC)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]9C(=O)N[C@H]7C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c9cc(O)cc(O)c9-c9cc7ccc9O)[C@H](O)c7ccc(c(Cl)c7)O8)OC(CO)C(O)C6O)OC(C)C5O)cc4C)c(C)c3)C(O)C(C)O2)Oc2ccc(cc2Cl)[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN[C@H](CC(C)C)C(=O)N[C@H]1C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]2C(=O)N[C@H]3C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c4cc(O)cc(O)c4-c4cc3ccc4O)[C@H](O)c3ccc(c(Cl)c3)Oc3cc2cc(c3OC2OC(CO)C(O)C(O)C2OC2CC(C)(NC(=O)OCc3cc(C)c(OC(=O)CNC(=O)COCCO)c(C)c3)C(O)C(C)O2)Oc2ccc(cc2Cl)[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN[C@H](CC(C)C)C(=O)N[C@H]1C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]2C(=O)N[C@H]3C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c4cc(O)cc(O)c4-c4cc3ccc4O)[C@H](O)c3ccc(c(Cl)c3)Oc3cc2cc(c3OC2OC(CO)C(O)C(O)C2OC2CC(C)(NC(=O)OCc3cc(C)c(OC(=O)COCCO)c(C)c3)C(O)C(C)O2)Oc2ccc(cc2Cl)[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN[C@H](CC(C)C)C(=O)N[C@H]1C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]2C(=O)N[C@H]3C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c4cc(O)cc(O)c4-c4cc3ccc4O)[C@H](O)c3ccc(c(Cl)c3)Oc3cc2cc(c3OC2OC(CO)C(O)C(O)C2OC2CC(C)(NC(=O)OCc3cc(C)c(OC(=O)NCCOCCO)c(C)c3)C(O)C(C)O2)Oc2ccc(cc2Cl)[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CN[C@H](CC(C)C)C(=O)N[C@H]1C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]2C(=O)N[C@H]3C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c4cc(O)cc(O)c4-c4cc3ccc4O)[C@H](O)c3ccc(c(Cl)c3)Oc3cc2cc(c3OC2OC(CO)C(O)C(O)C2OC2CC(C)(NC(=O)OCc3cc(C)c(OC(=O)NCCOCCOCCNC(=O)CNC(=O)CC(NC(=O)COCCO)C(=O)NCC(=O)NCCOCCOCCNC(=O)Oc4c(C)cc(COC(=O)NC5(C)CC(OC6C(Oc7c8cc9cc7Oc7ccc(cc7Cl)[C@@H](O)[C@@H](NC(=O)[C@@H](CC(C)C)NC)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@H]9C(=O)N[C@H]7C(=O)N[C@H](C(=O)N[C@H](C(=O)O)c9cc(O)cc(O)c9-c9cc7ccc9O)[C@H](O)c7ccc(c(Cl)c7)O8)OC(CO)C(O)C6O)OC(C)C5O)cc4C)c(C)c3)C(O)C(C)O2)Oc2ccc(cc2Cl)[C@H]1O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CO/C(C)=C1/NC(=O)[C@H]([C@@H](C)O)NC(=O)c2csc(n2)-c2cc(O)c(-c3nc(C(=O)N[C@@H](C)C(=O)NCCOCCOCCOCCOCCOCCOC4O[C@H](CO)[C@@H](O)[C@H](O)[C@H]4O)cs3)nc2-c2csc(n2)[C@@H]2COC(=O)c3c4c5c(cccc5n3O)COC(=O)[C@@H](O[C@H]3C[C@](C)(O)[C@H](N(C)C)[C@H](C)O3)[C@@H](OC4)[C@H](NC(=O)c3csc1n3)c1nc(cs1)C(=O)N2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COC(=O)N[C@H](C(=O)N1CCC[C@H]1c1nc2ccc([C@H]3CC[C@H](c4ccc5nc([C@@H]6CCCN6C(=O)[C@@H](NC(=O)OC)C(C)C)[nH]c5c4)N3c3cc(F)c(N4CCC(c5ccc(F)cc5)CC4)c(F)c3)cc2[nH]1)C(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COC(=O)N[C@H](C(=O)N1CCC[C@H]1c1nc2ccc([C@H]3CC[C@H](c4ccc5nc([C@@H]6CCCN6C(=O)[C@@H](NC(=O)OC)C(C)C)[nH]c5c4)N3c3cc(F)c(N4CCC(c5ccccc5)CC4)c(F)c3)cc2[nH]1)C(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COC(=O)N[C@H](C(=O)N1CCC[C@H]1c1nc2ccc([C@H]3CC[C@H](c4ccc5nc([C@@H]6CCCN6C(=O)[C@@H](NC(=O)OC)C(C)C)[nH]c5c4)N3c3ccc(N4CCC(c5ccccc5)CC4)cc3)cc2[nH]1)C(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COC(=O)N[C@H](C(=O)N[C@@H](Cc1ccc(-c2ccc(N(C)C)nc2)cc1)[C@@H](O)C[C@@H](Cc1ccccc1F)C(=O)N[C@H]1c2cc(F)cc(Cl)c2OC[C@H]1O)C(C)(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COC(=O)[C@H]1[C@@H]2C[C@@H](O[C@@H]3O[C@H](C)[C@@H](O)[C@H](NC(=O)CCOCCOCCOCCOCCOCCOCCOCCOCCN)[C@@H]3O)/C=C/C=C/C=C/C=C/C=C/C=C/C=C/[C@H](C)[C@@H](O)[C@@H](C)[C@H](C)OC(=O)C[C@H](O)C[C@H](O)CC[C@@H](O)[C@H](O)C[C@H](O)C[C@](O)(C[C@@H]1O)O2\n",
            "[04:45:48] UFFTYPER: Warning: hybridization set to SP3 for atom 8\n",
            "[04:46:53] UFFTYPER: Unrecognized charge state for atom: 12\n",
            "[04:46:53] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "[04:46:53] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCN1CCC(N(CC23CC(c4ccc(C(F)(F)F)cc4)(C2)C3)C(=O)Cn2c(SCc3cccc(F)c3F)cc(=O)c3ccccc32)CC1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCNC(=O)C(NC(=O)C(Cc1cc(OC)c(OC)c(OC)c1)CC(O)C(Cc1ccccc1)NC(=O)OC(C)(C)C)C(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCNC(=O)Oc1cc2c(c3ccccc13)C(CCl)CN2C(=O)c1cc2cc(NC(=O)c3cc(NC(=O)c4cc(NC(=O)c5cc(NC(=O)c6cc(NC(=O)CCCNC(=O)c7cc(NC(=O)c8cc(NC(=O)c9nc(NC(=O)CCNC(=O)c%10nc(NC(=O)c%11cc(NC(C)=O)cn%11C)cn%10C)cn9C)cn8C)cn7C)cn6C)cn5C)cn4C)cn3C)ccc2[nH]1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCOCCOCC1N(C)CC23C4=C5C6=C7c8c9c%10c%11c%12c%13c%14c(c2c2c%15c%16c%17c%18c%19c(c5c5c%20c%21c%22c%23c(c8C%22C65)c%10c5c%11c6c%13c8c(c%15%14)c%16c%10c%18c%11c(c%20%19)c%21c%13c%23c5c5c%13c%11c%10c8c65)C%17C42)C%12C9C713\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCOCCOCCN1CC23C4=C5C6=C7c8c9c%10c%11c%12c%13c%14c(c2c2c%15c%16c%17c%18c%19c(c5c5c%20c%21c%22c%23c(c8C%22C65)c%10c5c%11c6c%13c8c(c%15%14)c%16c%10c%18c%11c(c%20%19)c%21c%13c%23c5c5c%13c%11c%10c8c65)C%17C42)C%12C9C73C1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCOCCOCCN1CC23C4=C5C6=C7c8c9c%10c%11c%12c%13c%14c(c2c2c%15c%16c%17c%18c%19c(c5c5c%20c%21c%22c%23c(c8C%22C65)c%10c5c%11c6c%13c8c(c%15%14)c%16c%10c%18c%11c(c%20%19)c%21c%13c%23c5c5c%13c%11c%10c8c65)C%17C42)C%12C9C73C1COCCOCCOC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCOCCOCCOCCN(CCOCCOCCOCCOC)c1ccc(/C=C/C(=O)c2cc3ccc(OCCOCCOCCOC)cc3oc2=O)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCOCCOCCOCCOCCOc1cc2cc(C(=O)N3C[C@@H](CCl)c4c3cc(O)c3[nH]c(C(=O)OC)cc43)[nH]c2c(OCCOCCOCCOCCOCCOC)c1OCCOCCOCCOCCOCCOC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCOCCOCCOCCOc1cc2cc(C(=O)N3C[C@@H](CCl)c4c3cc(O)c3[nH]c(C(=O)OC)cc43)[nH]c2c(OCCOCCOCCOCCOC)c1OCCOCCOCCOCCOC\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COCCOCCOCCOc1cc2cc(C(=O)N3C[C@@H](CCl)c4c3cc(O)c3[nH]c(C(=O)OC)cc43)[nH]c2c(OCCOCCOCCOC)c1OCCOCCOCCOC\n",
            "[04:50:48] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[04:50:49] UFFTYPER: Unrecognized atom type: S_6+6 (17)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COC[C@H]1OC(=O)/C(=C\\N(C)CCCN(C)C)C2=C(O)C(=O)C3=C([C@H](OC(C)=O)C[C@]4(C)[C@@H](OC(=O)CCCCCCC(=O)O[C@@H]5CC[C@@H](C[C@@H](C)[C@@H]6CC(=O)[C@H](C)/C=C(\\C)[C@@H](O)[C@@H](OC)C(=O)[C@H](C)C[C@H](C)/C=C/C=C/C=C(\\C)[C@@H](OC)C[C@@H]7CC[C@@H](C)[C@@](O)(O7)C(=O)C(=O)N7CCCC[C@H]7C(=O)O6)C[C@H]5OC)CC[C@@H]34)[C@]21C\n",
            "[04:51:51] UFFTYPER: Unrecognized atom type: S_6+6 (16)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CO[C@H]1/C=C/O[C@@]2(C)Oc3c(C)c(O)c4c(O)c(c(CNCCCN5CCN(CCCNCc6c7c(O)c8c(O)c(C)c9c(c8c6O)C(=O)[C@@](C)(O/C=C/[C@H](OC)[C@@H](C)[C@@H](OC(C)=O)[C@H](C)[C@H](O)[C@H](C)[C@@H](O)[C@@H](C)/C=C/C=C(/C)C(=O)N7)O9)CC5)c(O)c4c3C2=O)NC(=O)/C(C)=C\\C=C\\[C@H](C)[C@H](O)[C@@H](C)[C@@H](O)[C@@H](C)[C@H](OC(C)=O)[C@@H]1C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CO[C@H]1C[C@@H]2CC[C@@H](C)[C@@](O)(O2)C(=O)C(=O)N2CCCC[C@H]2C(=O)O[C@H]([C@H](C)C[C@@H]2CC[C@@H](OCCOC(=O)CSC[C@H](NC(=O)CC[C@H](N)C(=O)O)C(=O)NCC(=O)O)[C@H](OC)C2)CC(=O)[C@H](C)/C=C(\\C)[C@@H](O)[C@@H](OC)C(=O)[C@H](C)C[C@H](C)/C=C\\C=C\\C=C\\1C\n",
            "[04:53:56] UFFTYPER: Warning: hybridization set to SP3 for atom 2\n",
            "[04:53:56] UFFTYPER: Unrecognized charge state for atom: 2\n",
            "[04:53:56] UFFTYPER: Unrecognized charge state for atom: 2\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:55:07] UFFTYPER: Unrecognized atom type: Se2+2 (12)\n",
            "[04:57:54] UFFTYPER: Unrecognized charge state for atom: 15\n",
            "[05:01:08] UFFTYPER: Unrecognized charge state for atom: 12\n",
            "[05:01:24] UFFTYPER: Unrecognized atom type: Se2+2 (13)\n",
            "[05:01:24] UFFTYPER: Unrecognized atom type: Se2+2 (13)\n",
            "[05:01:24] UFFTYPER: Unrecognized atom type: Se2+2 (13)\n",
            "[05:01:24] UFFTYPER: Unrecognized atom type: Se2+2 (13)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1ccc(C(=O)OC[C@H]2O[C@@H](n3cnc4c(OC)ncnc43)[C@@H](OC(=O)c3ccc(OC)cc3)[C@@H]2OC(=O)c2ccc(OC)cc2)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1ccc(CN[C@@H](C(=O)NC(C(=O)NCc2nc3ccccc3[nH]2)C(C)C)[C@H](O)[C@H](Cc2ccccc2)NC(=O)OC(C)(C)C)cc1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1ccc(CN[C@@H](C(=O)N[C@H](C(=O)NCc2nc3ccccc3[nH]2)C(C)C)[C@H](O)[C@H](Cc2ccccc2)NC(=O)[C@@H](NC(=O)OCc2ccccc2)C(C)C)cc1\n",
            "[05:04:08] UFFTYPER: Unrecognized charge state for atom: 15\n",
            "[05:04:08] UFFTYPER: Unrecognized charge state for atom: 15\n",
            "[05:05:06] UFFTYPER: Unrecognized charge state for atom: 14\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1ccc(OC)c(C(=O)O[C@H]2C3[C@](C)(C(=O)[C@H](O)C4=C(C)[C@@H](OC(=O)[C@H](O)[C@H](C=C(C)C)NC(=O)OC(C)(C)C)C[C@]2(O)C4(C)C)C(OC(=O)CCOCCOCCOCCOCCSSC)C[C@H]2OC[C@@]32OC(C)=O)c1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1ccc(OC)c(C(=O)O[C@H]2C3[C@](C)(C(=O)[C@H](OC(=O)CCOCCOCCOCCOCCOCCOCCOCCOCCOCCOCCSSC)C4=C(C)[C@@H](OC(=O)[C@H](O)[C@H](C=C(C)C)NC(=O)OC(C)(C)C)C[C@]2(O)C4(C)C)C(O)C[C@H]2OC[C@@]32OC(C)=O)c1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1ccc(OC)c(C(=O)O[C@H]2C3[C@](C)(C(=O)[C@H](OC(=O)CCOCCOCCOCCOCCSSC)C4=C(C)[C@@H](OC(=O)[C@H](O)[C@H](C=C(C)C)NC(=O)OC(C)(C)C)C[C@]2(O)C4(C)C)C(O)C[C@H]2OC[C@@]32OC(C)=O)c1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1ccc(OC)c(C(=O)O[C@H]2C3[C@](C)(C(=O)[C@H](OC(=O)N4CCN(CCSSC)CC4)C4=C(C)[C@@H](OC(=O)[C@H](O)[C@H](C=C(C)C)NC(=O)OC(C)(C)C)C[C@]2(O)C4(C)C)C(O)C[C@H]2OC[C@@]32OC(C)=O)c1\n",
            "[05:06:30] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[05:06:31] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[05:07:36] UFFTYPER: Unrecognized charge state for atom: 15\n",
            "[05:07:36] UFFTYPER: Unrecognized charge state for atom: 15\n",
            "[05:08:35] UFFTYPER: Unrecognized charge state for atom: 15\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)C(CCCN2CCN(C)CC2)NC(=O)[C@H](CCc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCc2ccc(O)cc2)NC(=O)[C@H](CCc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)C(CCc2ccncc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@@H](NC(=O)CNC(=O)[C@H](CCCN)NC(=O)NC(=O)[C@@H]2CCCN2C(=O)c2ccccc2S(=O)(=O)O)[C@@H](C)OCc2ccccc2)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@@H](NC(=O)CNC(=O)[C@H](CO)NC(=O)[C@@H]2CCCN2C(=O)c2cc(S(=O)(=O)O)cc(S(=O)(=O)O)c2)[C@@H](C)OCc2ccccc2)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](CCc2ccc(O)cc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(=O)[C@H](CCC(=O)O)NC(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](COCc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)C2CCCN2C(=O)CCC(=O)O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](COCc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(=O)CS(=O)(=O)O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](COCc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(=O)[C@H](CC(=O)O)NC(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](COCc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(=O)[C@H](CCC(=O)O)NC(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](COCc2ccccc2)NC(=O)CNC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]2CCCN2C(=O)[C@H](CCC(=O)O)NC(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](COCc2ccccc2)NC(=O)CNC(=O)[C@H](CCCN)NC(=O)NC(=O)[C@@H]2CCCN2C(=O)[C@H](CCC(=O)O)NC(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](COCc2ccccc2)NC(=O)CNC(=O)[C@H](CCCNC(N)=O)NC(=O)[C@@H]2CCCN2C(=O)CS(=O)(=O)O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](CSCc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(=O)[C@H](CCC(=O)O)NC(C)=O)[C@H](O)[C@H](C)O1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@H](Cc2ccccc2)NC(=O)CNC(=O)[C@H](CC(C)C)NC(=O)[C@@H]2CCCN2C(C)=O)[C@H](O)[C@H](C)O1\n",
            "[05:12:15] UFFTYPER: Unrecognized charge state for atom: 21\n",
            "[05:12:58] UFFTYPER: Unrecognized atom type: S_6+6 (16)\n",
            "[05:13:03] UFFTYPER: Unrecognized atom type: S_6+6 (18)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CSCC[C@@H]1NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](Cc2ccc(O)cc2)NC(=O)[C@@H](NC(=O)[C@H](CCCNC(=N)N)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](C)NC(=O)[C@H](Cc2cnc[nH]2)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H]2CCCN2C(=O)[C@H](CC(=O)O)NC(C)=O)[C@@H](C)O)CCCCNC(=O)C[C@@H](C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CC(C)C)C(=O)NCC(=O)N[C@@H](CC(C)C)C(=O)NCC(N)=O)NC1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CSCC[C@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CC(C)C)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CO)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@H](C(=O)N[C@H](C(=O)N[C@@H](CCCCN)C(=O)N[C@@]1(C)CCC/C=C\\CCC[C@@](C)(C(=O)N[C@@H](Cc2ccc(O)cc2)C(N)=O)NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CC(C)C)NC1=O)C(C)C)C(C)C\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CSCC[C@H](NC(=O)[C@H](CCC(=O)O)NC(=O)[C@H](Cc1ccc(O)cc1)NC(=O)[C@@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(=O)O)NC(=O)[C@H](CC(C)C)NC(C)=O)[C@@H](C)O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CO)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@]1(C)CCC/C=C\\CCC[C@@](C)(C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CCC(=O)O)C(=O)N[C@@H](CO)C(=O)N[C@@H](Cc2ccc(O)cc2)C(N)=O)NC(=O)[C@H](CCCCN)NC(=O)[C@H](C(C)C)NC(=O)[C@H](C(C)C)NC1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CSCC[C@H](NC(=O)[C@H](CCCN=C(N)N)NC(=O)[C@H](CCCN=C(N)N)NC(=O)CC(N)CSC1CC(=O)N(CCC(=O)O[C@@H](C(=O)O[C@@H]2C(C)=CC3[C@@H](OC(C)=O)C(=O)[C@@]4(C)[C@H]([C@H](OC(=O)c5ccccc5)[C@@]2(O)C3(C)C)[C@]2(OC(C)=O)CO[C@@H]2C[C@@H]4O)[C@@H](NC(=O)c2ccccc2)c2ccccc2)C1=O)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(=O)N[C@@H](CCCCN)C(=O)N[C@@H](CCCCN)C(N)=O\n",
            "[05:13:46] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "[05:13:46] UFFTYPER: Unrecognized charge state for atom: 3\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CS[C@@H](NC(=O)[C@@H](Cc1cccnc1)NC(=O)[C@@H](Cc1ccc(Cl)cc1)NC(=O)[C@@H](Cc1ccc2ccccc2c1)NC(C)=O)C(=O)N[C@@H](Cc1ccc(NC(C)=O)cc1)C(=O)N[C@H](Cc1ccc(NC(C)=O)cc1)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N1CCC[C@H]1C(=O)N[C@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CS[C@@H](NC(=O)[C@@H]1CCCN1C(=O)[C@H](CCCCNC(C)C)NC(=O)[C@H](CC(C)C)NC(=O)[C@@H](Cc1ccc(NC(C)=O)cc1)NC(=O)[C@H](Cc1ccc(NC(C)=O)cc1)NC(=O)[C@H](CO)NC(=O)[C@@H](Cc1cccnc1)NC(=O)[C@@H](Cc1ccc(Cl)cc1)NC(=O)[C@@H](Cc1ccc2ccccc2c1)NC(C)=O)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CS[C@H](NC(=O)[C@@H](Cc1cccnc1)NC(=O)[C@@H](Cc1ccc(Cl)cc1)NC(=O)[C@@H](Cc1ccc2ccccc2c1)NC(C)=O)C(=O)N[C@@H](Cc1ccc(NC(C)=O)cc1)C(=O)N[C@H](Cc1ccc(NC(C)=O)cc1)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCCNC(C)C)C(=O)N1CCC[C@H]1C(=O)N[C@H](C)C(N)=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: CS[C@H](NC(=O)[C@@H]1CCCN1C(=O)[C@H](CCCCNC(C)C)NC(=O)[C@H](CC(C)C)NC(=O)[C@@H](Cc1ccc(NC(C)=O)cc1)NC(=O)[C@H](Cc1ccc(NC(C)=O)cc1)NC(=O)[C@H](CO)NC(=O)[C@@H](Cc1cccnc1)NC(=O)[C@@H](Cc1ccc(Cl)cc1)NC(=O)[C@@H](Cc1ccc2ccccc2c1)NC(C)=O)C(N)=O\n",
            "[05:14:11] UFFTYPER: Unrecognized atom type: S_6+6 (15)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C[C@@H]1CC[C@H]2C(CN3CCN(CCO)CC3)=C(C(F)(F)F)O[C@@H]3O[C@]4(C)CC[C@@H]1[C@]32OO4\n",
            "[05:17:15] UFFTYPER: Unrecognized charge state for atom: 27\n",
            "[05:17:22] UFFTYPER: Unrecognized charge state for atom: 27\n",
            "[05:17:32] UFFTYPER: Unrecognized charge state for atom: 11\n",
            "[05:17:33] UFFTYPER: Unrecognized charge state for atom: 11\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: C[C@@H]1[C@H](O)[C@@H](C)/C=C/C=C/C=C/C=C/C=C/C=C/C=C/[C@H](O[C@@H]2O[C@H](C)[C@@H](O)[C@H](NC(=O)CCOCCOCCOCCOCCOCCOCCOCCOCCN)[C@@H]2O)C[C@@H]2O[C@](O)(C[C@@H](O)C[C@@H](O)[C@H](O)CC[C@@H](O)C[C@@H](O)CC(=O)O[C@H]1C)C[C@H](O)[C@H]2C(=O)O\n",
            "[05:18:16] UFFTYPER: Unrecognized charge state for atom: 9\n",
            "[05:20:59] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:20:59] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:20:59] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:00] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:00] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:00] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:00] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:01] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:01] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:01] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:01] UFFTYPER: Unrecognized charge state for atom: 19\n",
            "[05:21:01] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:02] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:21:02] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1c(C)c(S(=O)(=O)NC(=N)NCCCC[C@H](NC(=O)[C@@H](NC(=O)[C@H](Cc2ccc(OCc3ccccc3)cc2)NC(=O)OC(C)(C)C)[C@@H](C)OCc2ccccc2)C(=O)Cc2ccccc2)c(C)c2c1OC(C)(C)CC2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1c(C)c(S(=O)(=O)NC(=N)NCCCC[C@H](NC(=O)[C@@H](NC(=O)[C@H](Cc2ccc(OCc3ccccc3)cc2)NS(=O)(=O)Cc2ccccc2)[C@@H](C)OCc2ccccc2)C(=O)Cc2ccccc2)c(C)c2c1OC(C)(C)CC2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1c(C)c(S(=O)(=O)NC(=N)NCCCC[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(OCc3ccccc3)cc2)NC(=O)OC(C)(C)C)C(=O)Cc2ccccc2)c(C)c2c1OC(C)(C)CC2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1c(C)c(S(=O)(=O)NC(=N)NCCCC[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](Cc2ccc(OCc3ccccc3)cc2)NS(=O)(=O)Cc2ccccc2)C(=O)Cc2ccccc2)c(C)c2c1OC(C)(C)CC2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1c(C)c(S(=O)(=O)NC(=N)NCCCC[C@H](NC(=O)[C@H](Cc2ccccc2)NC(=O)[C@@H](Cc2ccccc2)NC(=O)OCc2ccccc2)C(=O)Cc2ccccc2)c(C)c2c1OC(C)(C)CC2\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1c(N2CC[C@@H]([C@H](C)N)C2)c(F)c(N)c2c(=O)c(C(=O)O)cn([C@@H]3C[C@@H]3F)c12\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1c(Nc2ccc(C#N)cc2Cl)ncnc1OC1C[C@@H]2CC[C@@H](C1)N2S(=O)(=O)C1CC1\n",
            "[05:26:08] UFFTYPER: Unrecognized charge state for atom: 20\n",
            "[05:26:09] UFFTYPER: Unrecognized charge state for atom: 20\n",
            "[05:26:09] UFFTYPER: Unrecognized charge state for atom: 20\n",
            "[05:27:42] UFFTYPER: Unrecognized charge state for atom: 13\n",
            "[05:29:40] UFFTYPER: Unrecognized charge state for atom: 18\n",
            "[05:29:51] UFFTYPER: Unrecognized atom type: S_6+6 (9)\n",
            "[05:29:52] UFFTYPER: Unrecognized atom type: S_6+6 (9)\n",
            "[05:29:52] UFFTYPER: Unrecognized atom type: S_6+6 (9)\n",
            "[05:29:52] UFFTYPER: Unrecognized atom type: S_6+6 (9)\n",
            "[05:30:10] UFFTYPER: Unrecognized charge state for atom: 9\n",
            "[05:31:00] UFFTYPER: Unrecognized charge state for atom: 16\n",
            "[05:31:26] UFFTYPER: Unrecognized charge state for atom: 16\n",
            "[05:31:27] UFFTYPER: Unrecognized charge state for atom: 17\n",
            "[05:31:39] UFFTYPER: Unrecognized charge state for atom: 16\n",
            "[05:32:48] UFFTYPER: Unrecognized charge state for atom: 19\n",
            "[05:33:45] UFFTYPER: Unrecognized charge state for atom: 6\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1cn(CC(=O)N(CC(=O)NCCN(CC(=O)NCCN(CC(=O)NCCN(CC(=O)NC[C@@H](C)N(CC(=O)N[C@H](CCCCN)C(N)=O)C(=O)Cn2cc(C)c(=O)[nH]c2=O)C(=O)Cn2ccc(N)nc2=O)C(=O)Cn2cnc3c(N)ncnc32)C(=O)Cn2ccc(N)nc2=O)[C@H](C)CNC(=O)CN(CCNC(=O)CN(CCNC(=O)CN(CCNC(=O)CN(C(=O)Cn2cc(C)c(=O)[nH]c2=O)[C@H](C)CNC(=O)CN(CCN)C(=O)Cn2cnc3c(=O)[nH]c(N)nc32)C(=O)Cn2cnc3c(N)ncnc32)C(=O)Cn2cnc3c(=O)[nH]c(N)nc32)C(=O)Cn2cnc3c(N)ncnc32)c(=O)[nH]c1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1cn(CC(=O)N(CC(=O)NCCN(CC(=O)NCCN(CC(=O)NCCN(CC(=O)NC[C@H](C)N(CC(=O)N[C@@H](CCCCN)C(N)=O)C(=O)Cn2cc(C)c(=O)[nH]c2=O)C(=O)Cn2ccc(N)nc2=O)C(=O)Cn2cnc3c(N)ncnc32)C(=O)Cn2ccc(N)nc2=O)[C@@H](C)CNC(=O)CN(CCNC(=O)CN(CCNC(=O)CN(CCNC(=O)CN(C(=O)Cn2cc(C)c(=O)[nH]c2=O)[C@@H](C)CNC(=O)CN(CCN)C(=O)Cn2cnc3c(=O)[nH]c(N)nc32)C(=O)Cn2cnc3c(N)ncnc32)C(=O)Cn2cnc3c(=O)[nH]c(N)nc32)C(=O)Cn2cnc3c(N)ncnc32)c(=O)[nH]c1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1cn(CC(=O)N(CCNC(=O)CN(CCNC(=O)CN(CCNC(=O)CN(CCNC(=O)CN(CCNC(=O)CN(CCN)C(=O)Cn2cnc3c(=O)[nH]c(N)nc32)C(=O)Cn2cc(C)c(=O)[nH]c2=O)C(=O)Cn2cnc3c(N)ncnc32)C(=O)Cn2cnc3c(=O)[nH]c(N)nc32)C(=O)Cn2cnc3c(N)ncnc32)CC(=O)NCCN(CC(=O)NCCN(CC(=O)NCCN(CC(=O)NCCN(CC(=O)N[C@@H](CCCCN)C(N)=O)C(=O)Cn2cc(C)c(=O)[nH]c2=O)C(=O)Cn2ccc(N)nc2=O)C(=O)Cn2cnc3c(N)ncnc32)C(=O)Cn2ccc(N)nc2=O)c(=O)[nH]c1=O\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: Cc1ncn(-c2ccc(C(=O)N[C@H]3[C@H]4CC[C@H]3N(c3ncc(Cl)c5cnoc35)C4)c(Cl)c2)n1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: ClC1=C(Cl)[C@]2(Cl)C3C([C@@H]4C[C@H]3C3OC34)[C@]1(Cl)C2(Cl)Cl\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: ClC1=C(Cl)[C@]2(Cl)[C@H]3[C@H]([C@@H]4C=C[C@H]3C4)[C@]1(Cl)C2(Cl)Cl\n",
            "[05:43:23] UFFTYPER: Unrecognized atom type: Se2+2 (6)\n",
            "[05:43:58] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "[05:43:58] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "[05:43:58] UFFTYPER: Unrecognized charge state for atom: 5\n",
            "[05:44:33] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[05:46:10] UFFTYPER: Unrecognized atom type: S_6+6 (1)\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: FS(F)(F)(F)(F)F\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: N#CC12CC(CN([C@H](CCC(F)(F)F)C(N)=O)S(=O)(=O)c3ccc(Cl)cc3)(C1)C2\n",
            "[05:48:54] UFFTYPER: Unrecognized charge state for atom: 20\n",
            "[05:49:43] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[05:49:43] UFFTYPER: Unrecognized charge state for atom: 4\n",
            "[05:51:59] UFFTYPER: Unrecognized charge state for atom: 13\n",
            "[05:52:01] UFFTYPER: Unrecognized charge state for atom: 9\n",
            "[05:52:54] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[05:52:54] UFFTYPER: Unrecognized charge state for atom: 18\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: O=C(CCC(=O)O[C@@H]1[C@@H](O)[C@@H](O)O[C@H](CO)[C@H]1O)Oc1ccc(/C=C/c2cc(OC(=O)CCC(=O)O[C@@H]3[C@@H](O)[C@@H](O)O[C@H](CO)[C@H]3O)cc(OC(=O)CCC(=O)O[C@@H]3[C@@H](O)[C@@H](O)O[C@H](CO)[C@H]3O)c2)cc1\n",
            "[05:59:12] UFFTYPER: Unrecognized charge state for atom: 36\n",
            "[06:01:15] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[06:01:16] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[06:02:04] UFFTYPER: Unrecognized charge state for atom: 45\n",
            "[06:02:05] UFFTYPER: Unrecognized charge state for atom: 45\n",
            "[06:04:02] UFFTYPER: Unrecognized charge state for atom: 10\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: O=C(O)CNC(=O)C(CSC(=O)N(O)c1ccc(Br)cc1)NC(=O)CCC(NCCC(=O)OCCOCCOCCOCCNC(=O)CCCCCCC(=O)NCCCOCCOCCOCCCNC(=O)CCCCCCC(=O)NCCOCCOCCOCCOC(=O)CCNC(CCC(=O)NC(CSC(=O)N(O)c1ccc(Br)cc1)C(=O)NCC(=O)O)C(=O)O)C(=O)O\n",
            "[06:07:49] UFFTYPER: Unrecognized charge state for atom: 21\n",
            "[06:08:00] UFFTYPER: Unrecognized charge state for atom: 29\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: O=C(O[C@@H]1C[C@@H]2C[C@H]3C[C@H](C1)N2CC3=O)c1c[nH]c2ccccc12\n",
            "[06:10:34] UFFTYPER: Unrecognized charge state for atom: 7\n",
            "[06:11:49] UFFTYPER: Unrecognized charge state for atom: 28\n",
            "[06:14:27] UFFTYPER: Unrecognized charge state for atom: 18\n",
            "[06:14:32] UFFTYPER: Unrecognized charge state for atom: 7\n",
            "[06:15:12] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[06:15:12] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[06:15:12] UFFTYPER: Unrecognized charge state for atom: 8\n",
            "[06:15:14] UFFTYPER: Warning: hybridization set to SP3 for atom 1\n",
            "[06:15:14] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[06:15:14] UFFTYPER: Warning: hybridization set to SP3 for atom 1\n",
            "[06:15:14] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: O=c1cccc2n1C[C@@H]1CNC[C@@H]2C1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: OCCCOCC(OCCCO)C(OCCCO)C(OCCCO)C(COCCCO)OCCCO\n",
            "[06:18:41] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[06:18:41] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[06:18:41] UFFTYPER: Unrecognized charge state for atom: 7\n",
            "[06:18:41] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[06:18:42] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[06:18:42] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "[06:18:42] UFFTYPER: Unrecognized charge state for atom: 1\n",
            "ERROR:root:The RDKit embedding has failed for the molecule: c1cc2ccc1CCc1ccc(cc1)CC2\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CPU times: user 3h 34min 47s, sys: 2h 37min 27s, total: 6h 12min 15s\n",
            "Wall time: 3h 16min 11s\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# merging with original DF\n",
        "df_mod_wJ = pd.concat([df_mod, df_X], axis=1)\n",
        "df_mod_wJ.to_csv('/content/gdrive/MyDrive/gcollab/data/jazzy-test/solubility-SolCuration-combined-wJazzyDescr.csv', index=False)"
      ],
      "metadata": {
        "id": "i2UENjDwdOvg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_mod_wJ = pd.read_csv('/content/gdrive/MyDrive/gcollab/data/jazzy-test/solubility-SolCuration-combined-wJazzyDescr.csv')"
      ],
      "metadata": {
        "id": "-Z0SrDxU1qne"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Let's check some issues\n",
        "buggy_smiles = df_mod_wJ[df_mod_wJ['dgtot'].isnull()]['smiles_std'].values\n",
        "buggy_mols = [Chem.MolFromSmiles(smiles) for smiles in buggy_smiles]\n",
        "MolsToGridImage(buggy_mols, molsPerRow=5)\n",
        "# all buggy compounds are big, or greasy or both"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "kpA9LTb4dYac",
        "outputId": "564ccfbb-6448-4e00-846d-75a7bd177285"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.9/dist-packages/rdkit/Chem/Draw/IPythonConsole.py:258: UserWarning: Truncating the list of molecules to be displayed to 50. Change the maxMols value to display more.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# let's remove them\n",
        "df_mod_wJ = df_mod_wJ.dropna().reset_index(drop=True)"
      ],
      "metadata": {
        "id": "jDBiWakkToVU"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# adding 2D descriptors\n",
        "X_2d_descr = [ rdkit_calc_2d_descriptors(s) for s in df_mod_wJ['smiles_std'].values ]\n",
        "df_X_2d_descr = pd.DataFrame(X_2d_descr)\n",
        "df_X_2d_descr_names = df_X_2d_descr.columns"
      ],
      "metadata": {
        "id": "AOA6rblffb47"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_X_2d_descr.values.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8cme6Azd75D-",
        "outputId": "4c98c332-65ff-4955-ac3a-ed4497ba299d"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(33089, 208)"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Morgan fingerprint\n",
        "lst_X_mrg = [ get_fp(s) for s in df_mod_wJ['smiles_std'].values ]\n",
        "X_mrg = np.vstack(lst_X_mrg)"
      ],
      "metadata": {
        "id": "IY2vxwuABLle"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y = df_mod_wJ['median'].values"
      ],
      "metadata": {
        "id": "6xRFvkf5BKF4"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "jazzy_props = ['std', 'sdc', 'sdx', 'sa', 'dga', 'dgp', 'dgtot']"
      ],
      "metadata": {
        "id": "261V-A7h66sE"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "d_ts = {}\n",
        "d_ts['Jazzy'] = df_mod_wJ[jazzy_props].values\n",
        "d_ts['2D'] = df_X_2d_descr.values\n",
        "d_ts['Morgan'] = X_mrg\n",
        "# combos\n",
        "d_ts['combo_Morgan_Jazzy'] = np.concatenate((df_mod_wJ[jazzy_props].values, X_mrg), axis=1)\n",
        "d_ts['combo_Morgan_2D'] = np.concatenate((df_X_2d_descr.values, X_mrg), axis=1)\n",
        "d_ts['combo_2D_Jazzy'] = np.concatenate((df_X_2d_descr.values, df_mod_wJ[jazzy_props].values), axis=1)\n",
        "d_ts['combo_2D_Jazzy_Morgan'] = np.concatenate((df_X_2d_descr.values, df_mod_wJ[jazzy_props].values, X_mrg), axis=1)"
      ],
      "metadata": {
        "id": "PRxtWw3Hiia9"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_mod_wJ['median'].hist()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "cK0X1sb5bv_o",
        "outputId": "379ab5ae-1740-445b-dbd9-c6e603df403f"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 59
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Modeling"
      ],
      "metadata": {
        "id": "O7xcNvBBCohl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 5-fold CV, let's go easy...\n",
        "kf = KFold(n_splits=5, shuffle=True)"
      ],
      "metadata": {
        "id": "IhcX587AMyGf"
      },
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from catboost import CatBoostRegressor"
      ],
      "metadata": {
        "id": "Y_D2_G2D8x-j"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "benchmark = []\n",
        "for i, (train_index, test_index) in enumerate(kf.split(X_mrg)):\n",
        "  for k,v in d_ts.items():\n",
        "    X_train = v[train_index]\n",
        "    X_test = v[test_index]\n",
        "    y_train = y[train_index]\n",
        "    y_test = y[test_index]\n",
        "    model = CatBoostRegressor()\n",
        "    model.fit(X_train, y_train, verbose=False)\n",
        "    preds = model.predict(X_test)\n",
        "    d = {}\n",
        "    d['fold'] = i\n",
        "    d['descriptors'] = k\n",
        "    d['R2'] = r2_score(y_test, preds)\n",
        "    d['mean_absolute_percentage_error'] = mean_absolute_percentage_error(y_test, preds)\n",
        "    d['mse'] = mean_squared_error(y_test, preds)\n",
        "    d['rmse'] = mean_squared_error(y_test, preds, squared=False)\n",
        "    print(f\"Fold {i} for {k}: R2 - {round(d['R2'], 2)}, RMSE - {round(d['rmse'], 2)}\")\n",
        "    benchmark.append(d)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sz7GvfInMdR-",
        "outputId": "dd00f534-4309-4e0b-86da-1609d7a3155e"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Fold 0 for Jazzy: R2 - 0.48, RMSE - 1.21\n",
            "Fold 0 for 2D: R2 - 0.76, RMSE - 0.83\n",
            "Fold 0 for Morgan: R2 - 0.64, RMSE - 1.01\n",
            "Fold 0 for combo_Morgan_Jazzy: R2 - 0.7, RMSE - 0.92\n",
            "Fold 0 for combo_Morgan_2D: R2 - 0.77, RMSE - 0.8\n",
            "Fold 0 for combo_2D_Jazzy: R2 - 0.76, RMSE - 0.83\n",
            "Fold 0 for combo_2D_Jazzy_Morgan: R2 - 0.77, RMSE - 0.81\n",
            "Fold 1 for Jazzy: R2 - 0.49, RMSE - 1.21\n",
            "Fold 1 for 2D: R2 - 0.76, RMSE - 0.83\n",
            "Fold 1 for Morgan: R2 - 0.65, RMSE - 1.0\n",
            "Fold 1 for combo_Morgan_Jazzy: R2 - 0.71, RMSE - 0.91\n",
            "Fold 1 for combo_Morgan_2D: R2 - 0.76, RMSE - 0.82\n",
            "Fold 1 for combo_2D_Jazzy: R2 - 0.76, RMSE - 0.83\n",
            "Fold 1 for combo_2D_Jazzy_Morgan: R2 - 0.76, RMSE - 0.82\n",
            "Fold 2 for Jazzy: R2 - 0.47, RMSE - 1.21\n",
            "Fold 2 for 2D: R2 - 0.74, RMSE - 0.84\n",
            "Fold 2 for Morgan: R2 - 0.63, RMSE - 1.01\n",
            "Fold 2 for combo_Morgan_Jazzy: R2 - 0.68, RMSE - 0.93\n",
            "Fold 2 for combo_Morgan_2D: R2 - 0.75, RMSE - 0.83\n",
            "Fold 2 for combo_2D_Jazzy: R2 - 0.74, RMSE - 0.85\n",
            "Fold 2 for combo_2D_Jazzy_Morgan: R2 - 0.75, RMSE - 0.83\n",
            "Fold 3 for Jazzy: R2 - 0.48, RMSE - 1.21\n",
            "Fold 3 for 2D: R2 - 0.76, RMSE - 0.82\n",
            "Fold 3 for Morgan: R2 - 0.65, RMSE - 1.0\n",
            "Fold 3 for combo_Morgan_Jazzy: R2 - 0.71, RMSE - 0.91\n",
            "Fold 3 for combo_Morgan_2D: R2 - 0.78, RMSE - 0.8\n",
            "Fold 3 for combo_2D_Jazzy: R2 - 0.76, RMSE - 0.82\n",
            "Fold 3 for combo_2D_Jazzy_Morgan: R2 - 0.77, RMSE - 0.8\n",
            "Fold 4 for Jazzy: R2 - 0.49, RMSE - 1.23\n",
            "Fold 4 for 2D: R2 - 0.78, RMSE - 0.81\n",
            "Fold 4 for Morgan: R2 - 0.65, RMSE - 1.02\n",
            "Fold 4 for combo_Morgan_Jazzy: R2 - 0.72, RMSE - 0.91\n",
            "Fold 4 for combo_Morgan_2D: R2 - 0.78, RMSE - 0.8\n",
            "Fold 4 for combo_2D_Jazzy: R2 - 0.77, RMSE - 0.82\n",
            "Fold 4 for combo_2D_Jazzy_Morgan: R2 - 0.78, RMSE - 0.8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_benchmark = pd.DataFrame(benchmark)\n",
        "df_benchmark.to_csv('/content/gdrive/MyDrive/gcollab/data/jazzy-test/solubility-SolCuration-combined-catboost-bmk.csv', index=False)"
      ],
      "metadata": {
        "id": "BiwbFMKD-2ZR"
      },
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_benchmark_med = df_benchmark.groupby(['descriptors']).median()\n",
        "df_benchmark_med = df_benchmark_med.sort_values('R2').drop(columns=['fold'])\n",
        "df_benchmark_med"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "r8zkc4BuUbhu",
        "outputId": "1c86bff1-0130-4ee0-84ed-37bee501b74a"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             R2  mean_absolute_percentage_error       mse  \\\n",
              "descriptors                                                                 \n",
              "Jazzy                  0.483166                        0.697701  1.464090   \n",
              "Morgan                 0.647810                        0.636827  1.010520   \n",
              "combo_Morgan_Jazzy     0.709274                        0.522402  0.833167   \n",
              "combo_2D_Jazzy         0.755690                        0.422069  0.692619   \n",
              "2D                     0.756753                        0.416461  0.689372   \n",
              "combo_2D_Jazzy_Morgan  0.770472                        0.431028  0.650256   \n",
              "combo_Morgan_2D        0.772232                        0.412204  0.645269   \n",
              "\n",
              "                           rmse  \n",
              "descriptors                      \n",
              "Jazzy                  1.209996  \n",
              "Morgan                 1.005246  \n",
              "combo_Morgan_Jazzy     0.912780  \n",
              "combo_2D_Jazzy         0.832237  \n",
              "2D                     0.830284  \n",
              "combo_2D_Jazzy_Morgan  0.806384  \n",
              "combo_Morgan_2D        0.803286  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b2ab346d-e260-4e15-8a4d-ead51233de7d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>R2</th>\n",
              "      <th>mean_absolute_percentage_error</th>\n",
              "      <th>mse</th>\n",
              "      <th>rmse</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>descriptors</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Jazzy</th>\n",
              "      <td>0.483166</td>\n",
              "      <td>0.697701</td>\n",
              "      <td>1.464090</td>\n",
              "      <td>1.209996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Morgan</th>\n",
              "      <td>0.647810</td>\n",
              "      <td>0.636827</td>\n",
              "      <td>1.010520</td>\n",
              "      <td>1.005246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>combo_Morgan_Jazzy</th>\n",
              "      <td>0.709274</td>\n",
              "      <td>0.522402</td>\n",
              "      <td>0.833167</td>\n",
              "      <td>0.912780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>combo_2D_Jazzy</th>\n",
              "      <td>0.755690</td>\n",
              "      <td>0.422069</td>\n",
              "      <td>0.692619</td>\n",
              "      <td>0.832237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2D</th>\n",
              "      <td>0.756753</td>\n",
              "      <td>0.416461</td>\n",
              "      <td>0.689372</td>\n",
              "      <td>0.830284</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>combo_2D_Jazzy_Morgan</th>\n",
              "      <td>0.770472</td>\n",
              "      <td>0.431028</td>\n",
              "      <td>0.650256</td>\n",
              "      <td>0.806384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>combo_Morgan_2D</th>\n",
              "      <td>0.772232</td>\n",
              "      <td>0.412204</td>\n",
              "      <td>0.645269</td>\n",
              "      <td>0.803286</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b2ab346d-e260-4e15-8a4d-ead51233de7d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\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",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b2ab346d-e260-4e15-8a4d-ead51233de7d 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-b2ab346d-e260-4e15-8a4d-ead51233de7d');\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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    }
  ]
}