AlphaFold_run.ipynb

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  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "AlphaFold_run.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
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    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
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      "file_extension": ".py",
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      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.10"
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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/PotoyanGroup/Seq2Ensemble/blob/main/AlphaFold_run.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G4yBrceuFbf3"
      },
      "source": [
        "<img src=\"https://raw.githubusercontent.com/sokrypton/ColabFold/main/.github/ColabFold_Marv_Logo_Small.png\" height=\"200\" align=\"right\" style=\"height:240px\">\n",
        "\n",
        "##ColabFold: AlphaFold2 using MMseqs2\n",
        "\n",
        "Easy to use protein structure and complex prediction using [AlphaFold2](https://www.nature.com/articles/s41586-021-03819-2) and [Alphafold2-multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1). Sequence alignments/templates are generated through [MMseqs2](mmseqs.com) and [HHsearch](https://github.com/soedinglab/hh-suite). \n",
        "\n",
        "### Reference\n",
        "[Mirdita M, Schütze K, Moriwaki Y, Heo L, Ovchinnikov S, Steinegger M. ColabFold: Making protein folding accessible to all.\n",
        "*Nature Methods*, 2022](https://www.nature.com/articles/s41592-022-01488-1) "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kOblAo-xetgx",
        "cellView": "form"
      },
      "source": [
        "#@title Input protein sequence(s), then hit `Runtime` -> `Run all`\n",
        "from google.colab import files\n",
        "import os.path\n",
        "import re\n",
        "import hashlib\n",
        "import random\n",
        "\n",
        "def add_hash(x,y):\n",
        "  return x+\"_\"+hashlib.sha1(y.encode()).hexdigest()[:5]\n",
        "\n",
        "query_sequence = 'PIAQIHILEGRSDEQKETLIREVSEAISRSLDAPLTSVRVIITEMAKGHFGIGGELASK' #@param {type:\"string\"}\n",
        "#@markdown  - Use `:` to specify inter-protein chainbreaks for **modeling complexes** (supports homo- and hetro-oligomers). For example **PI...SK:PI...SK** for a homodimer\n",
        "\n",
        "# remove whitespaces\n",
        "query_sequence = \"\".join(query_sequence.split())\n",
        "\n",
        "jobname = 'test' #@param {type:\"string\"}\n",
        "# remove whitespaces\n",
        "basejobname = \"\".join(jobname.split())\n",
        "basejobname = re.sub(r'\\W+', '', basejobname)\n",
        "jobname = add_hash(basejobname, query_sequence)\n",
        "while os.path.isfile(f\"{jobname}.csv\"):\n",
        "  jobname = add_hash(basejobname, ''.join(random.sample(query_sequence,len(query_sequence))))\n",
        "\n",
        "with open(f\"{jobname}.csv\", \"w\") as text_file:\n",
        "    text_file.write(f\"id,sequence\\n{jobname},{query_sequence}\")\n",
        "\n",
        "queries_path=f\"{jobname}.csv\"\n",
        "\n",
        "\n",
        "msa_mode = \"MMseqs2 (UniRef+Environmental)\" #@param [\"MMseqs2 (UniRef+Environmental)\", \"MMseqs2 (UniRef only)\",\"single_sequence\",\"custom\"]\n",
        "pair_mode = \"unpaired+paired\" \n",
        "#\"unpaired+paired\" = pair sequences from same species + unpaired MSA, \"unpaired\" = seperate MSA for each chain, \"paired\" - only use paired sequences.\n",
        "\n",
        "# decide which a3m to use\n",
        "if msa_mode.startswith(\"MMseqs2\"):\n",
        "  a3m_file = f\"{jobname}.a3m\"\n",
        "elif msa_mode == \"custom\":\n",
        "  a3m_file = f\"{jobname}.custom.a3m\"\n",
        "  if not os.path.isfile(a3m_file):\n",
        "    custom_msa_dict = files.upload()\n",
        "    custom_msa = list(custom_msa_dict.keys())[0]\n",
        "    header = 0\n",
        "    import fileinput\n",
        "    for line in fileinput.FileInput(custom_msa,inplace=1):\n",
        "      if line.startswith(\">\"):\n",
        "         header = header + 1\n",
        "      if not line.rstrip():\n",
        "        continue\n",
        "      if line.startswith(\">\") == False and header == 1:\n",
        "         query_sequence = line.rstrip()\n",
        "      print(line, end='')\n",
        "\n",
        "    os.rename(custom_msa, a3m_file)\n",
        "    queries_path=a3m_file\n",
        "    print(f\"moving {custom_msa} to {a3m_file}\")\n",
        "else:\n",
        "  a3m_file = f\"{jobname}.single_sequence.a3m\"\n",
        "  with open(a3m_file, \"w\") as text_file:\n",
        "    text_file.write(\">1\\n%s\" % query_sequence)\n",
        "\n",
        "model_type = \"auto\" \n",
        "# \"auto\" = protein structure prediction using \"AlphaFold2-ptm\" and complex prediction \"AlphaFold-multimer-v2\". For complexes \"AlphaFold-multimer-v[1,2]\" and \"AlphaFold-ptm\" can be used.\n",
        "num_recycles = 3 \n",
        "save_to_google_drive = False \n",
        "\n",
        "dpi = 200 \n",
        "#set dpi for image resolution\n",
        "\n",
        "if save_to_google_drive:\n",
        "  from pydrive.drive import GoogleDrive\n",
        "  from pydrive.auth import GoogleAuth\n",
        "  from google.colab import auth\n",
        "  from oauth2client.client import GoogleCredentials\n",
        "  auth.authenticate_user()\n",
        "  gauth = GoogleAuth()\n",
        "  gauth.credentials = GoogleCredentials.get_application_default()\n",
        "  drive = GoogleDrive(gauth)\n",
        "  print(\"You are logged into Google Drive and are good to go!\")"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iccGdbe_Pmt9",
        "pycharm": {
          "name": "#%%\n"
        },
        "cellView": "form"
      },
      "source": [
        "#@title Install dependencies\n",
        "%%bash\n",
        "\n",
        "set -e\n",
        "\n",
        "if [ ! -f COLABFOLD_READY ]; then\n",
        "  # install dependencies\n",
        "  # We have to use \"--no-warn-conflicts\" because colab already has a lot preinstalled with requirements different to ours\n",
        "  pip install -q --no-warn-conflicts \"colabfold[alphafold-minus-jax] @ git+https://github.com/sokrypton/ColabFold\"\n",
        "  # high risk high gain\n",
        "  pip install -q \"jax[cuda11_cudnn805]>=0.3.8,<0.4\" -f https://storage.googleapis.com/jax-releases/jax_releases.html\n",
        "  touch COLABFOLD_READY\n",
        "fi"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_sztQyz29DIC",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "813cfea7-4192-46e1-caa9-d645b2fd38cb"
      },
      "source": [
        "#@title Run Prediction\n",
        "nmodels = 4 #@param {type:\"number\"}\n",
        "import sys\n",
        "\n",
        "from colabfold.download import download_alphafold_params, default_data_dir\n",
        "from colabfold.utils import setup_logging\n",
        "from colabfold.batch import get_queries, run, set_model_type\n",
        "K80_chk = !nvidia-smi | grep \"Tesla K80\" | wc -l\n",
        "\n",
        "if \"1\" in K80_chk:\n",
        "\n",
        "  print(\"WARNING: found GPU Tesla K80: limited to total length < 1000\")\n",
        "  if \"TF_FORCE_UNIFIED_MEMORY\" in os.environ:\n",
        "    del os.environ[\"TF_FORCE_UNIFIED_MEMORY\"]\n",
        "  if \"XLA_PYTHON_CLIENT_MEM_FRACTION\" in os.environ:\n",
        "    del os.environ[\"XLA_PYTHON_CLIENT_MEM_FRACTION\"]\n",
        "\n",
        "from colabfold.colabfold import plot_protein\n",
        "from pathlib import Path\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "def prediction_callback(unrelaxed_protein, length, prediction_result, input_features, type):\n",
        "  fig = plot_protein(unrelaxed_protein, Ls=length, dpi=150)\n",
        "  plt.show()\n",
        "  plt.close()\n",
        "\n",
        "result_dir=\".\"\n",
        "setup_logging(Path(\".\").joinpath(\"log.txt\"))\n",
        "queries, is_complex = get_queries(queries_path)\n",
        "model_type = set_model_type(is_complex, model_type)\n",
        "download_alphafold_params(model_type, Path(\".\"))\n",
        "run(\n",
        "    queries=queries,\n",
        "    result_dir=result_dir,\n",
        "    use_templates=False,\n",
        "    custom_template_path=None,\n",
        "    use_amber=False,\n",
        "    msa_mode=msa_mode,    \n",
        "    model_type=model_type,\n",
        "    num_models=nmodels,\n",
        "    num_recycles=num_recycles,\n",
        "    model_order=list(range(1,nmodels+1)),\n",
        "    is_complex=is_complex,\n",
        "    data_dir=Path(\".\"),\n",
        "    keep_existing_results=False,\n",
        "    recompile_padding=1.0,\n",
        "    rank_by=\"auto\",\n",
        "    pair_mode=pair_mode,\n",
        "    stop_at_score=float(100),\n",
        "    prediction_callback=prediction_callback,\n",
        "    dpi=dpi\n",
        ")"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/Bio/Data/SCOPData.py:18: BiopythonDeprecationWarning: The 'Bio.Data.SCOPData' module will be deprecated in a future release of Biopython in favor of 'Bio.Data.PDBData.\n",
            "  warnings.warn(\n",
            "Downloading alphafold2 weights to .: 100%|██████████| 3.47G/3.47G [00:18<00:00, 198MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-01-02 19:20:20,791 Found 5 citations for tools or databases\n",
            "2023-01-02 19:20:20,810 Unable to initialize backend 'tpu_driver': NOT_FOUND: Unable to find driver in registry given worker: \n",
            "2023-01-02 19:20:21,686 Unable to initialize backend 'rocm': NOT_FOUND: Could not find registered platform with name: \"rocm\". Available platform names are: Host CUDA Interpreter\n",
            "2023-01-02 19:20:21,688 Unable to initialize backend 'tpu': module 'jaxlib.xla_extension' has no attribute 'get_tpu_client'\n",
            "2023-01-02 19:20:21,688 Unable to initialize backend 'plugin': xla_extension has no attributes named get_plugin_device_client. Compile TensorFlow with //tensorflow/compiler/xla/python:enable_plugin_device set to true (defaults to false) to enable this.\n",
            "2023-01-02 19:20:27,106 Query 1/1: test_a5e17 (length 59)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "COMPLETE: 100%|██████████| 150/150 [elapsed: 00:01 remaining: 00:00]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-01-02 19:20:29,327 Running model_1\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.8/dist-packages/alphafold/model/mapping.py:50: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.\n",
            "  values_tree_def = jax.tree_flatten(values)[1]\n",
            "/usr/local/lib/python3.8/dist-packages/alphafold/model/mapping.py:54: FutureWarning: jax.tree_unflatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_unflatten instead.\n",
            "  return jax.tree_unflatten(values_tree_def, flat_axes)\n",
            "/usr/local/lib/python3.8/dist-packages/alphafold/model/mapping.py:129: FutureWarning: jax.tree_flatten is deprecated, and will be removed in a future release. Use jax.tree_util.tree_flatten instead.\n",
            "  flat_sizes = jax.tree_flatten(in_sizes)[0]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-01-02 19:21:22,924 model_1 took 50.1s (3 recycles) with pLDDT 95.5 and ptmscore 0.752\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x450 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-01-02 19:21:25,744 Running model_2\n",
            "2023-01-02 19:21:42,568 model_2 took 14.9s (3 recycles) with pLDDT 96.4 and ptmscore 0.764\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x450 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-01-02 19:21:44,578 Running model_3\n",
            "2023-01-02 19:22:01,425 model_3 took 14.9s (3 recycles) with pLDDT 97.4 and ptmscore 0.782\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x450 with 2 Axes>"
            ],
            "image/png": 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EHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHhZIREREREREHnOgO0BEVMzaP7qgBMDwXB7a0VXa0e/QWk+ERql29FvQ+nXt6LvGPLxt90B9DkRERIVacHV77jmodZXWXg4CpVrrtzTwunb0XdseHTNoclC01gPdByKiARH55MK/E8ENELkYgipt65ROaVunHAWNCrhv+CG/x9Faw07YL2rbWTHm4W17/feciIjIv4UfjvwdIDeI4GIAVVrrlNbadhytgIBz0LZfdBy9YtujY4o+B1kgEdEZJ/qphVMg8oiE5UIR6fa6djTsiA2dcAI9rmM7KTtu1Y55eNsrgTZMRESUh4Ufjk4RwSMiWXLQLWjgOMHWCY7jpCzLrt326JiizkEWSER0Rol84soFqszYLEp6vQfTSTqwT1iBHt+xnJgdt84f84tthwJtmIiIKAdXfiiywDDUZpEcctBxYFl2oMd3HCdmWfb52x4dU7Q5yEkaiOiMEf3UwrepUmNDLsURAKiwghpmBNoHZaoyMeUngTZKRESUg4Ufjr7NMNSGXIojAFBKwTCCLReUUmWiijsHWSAR0ZnDkO1iSDivXcoMSKj78ANf3QgZ85o/PKcs0EaJiIh6IYLtInnmoGEg0zA8PwxlzJvz3uaizUEWSER0RojdsfiDKqQmF7KvKg32KpIYSkFwR6CNEhER9WDxtbEPKlVYDgZ/FUmKOgdZIBHRkBe/c0k5BD8odH8JB3vmDACgMTP4RomIiLpbsiJeDvjIwYCvIAEo6hxkgUREZ4IviUhloTuLCGAEGw5a66mBNkhERJSd7xwMukbSKN4c5Cx2RDSkxe9cMg3AHvhcGDvVkgQCnMgn0Ra37bg1vOqxnbHgWiUiIjrdkhXxQHIwmUwF0yFPPJ6wLdsevnNTVdHlIK8gEdGQFb9zicAdUuArFAAAAZ5LcheOtQwA04NrlYiI6HRLVsSDy8EAaa1h2XbR5iALJCIayq4HMMdvI9rWQIBrxjpJu7Pgek9wrRIREXUTTA4GPOLMdk6GalHmIAskIhqS4ncuGQPg20G05cSDG1untUayI9n5z7rAGiYiIkqzZEU8sBy07eDOEmqtkUwUdw6yQCKioerfAIz124h2NJx4cMGQPJGAtk62V9d01Sy+DxMRUV8IJge1huMEl4OJZBLOqStSdbMWNxVdDhZdh4iI/IrfueRSACuDaMuJ2oHcf6QdB4nWOOy4lf70GADn+2+diIjolCUr4oHlYFBXjxytEY8nYFmnjcooyhxkgUREQ0r8ziUmgHuDaEtbjq+rR1pr2CkbqUgSsWNR2Akr02ZFOf6aiIgGpyUr4oHloOP4u3qktYZt20gmU4hGY7DsjEPWiy4Hi2pGCyKiAPwDgBq/jWitYXfY7QBaAbRne6SiyWXa0tO01oDW0BruR8e9apTD1af3APix3/4SERF5gstBu/ccTKZSy7Sjp2l4GYhTWejkNrlD0eXgkC2QVrZe9rcALgUwCoADre9bPXrrmwPcLSLqQ/E7l0wE8C8BNbe64t4tq3rbqOmqWccBfMvHcYryBlUa/C77QOtpOai1vm/rb0czB4mGsCUr4oHm4JZ1Fb3m4KzFTUMuB4dUgbSyZZ5A5OswjI8hXHLWaS9q/aWV7QuOwra/snrUUz8coC4SUd/6LwAVAbRzVEQ+n+O2O3we67ymq2aNrXps51Gf7RBh3vtbRES+bhjGx0pKwqfloNb6Swuubj9q2/ZXnvrNKOYg0dA0KHNw1uKmsTs3VRVNDg6Ze5BWNtVNg1KHEC75IgzzrG4biACGORah8A9Wts1/dGXLPBmAbhJRH4nfuWQhgL8PqLl/LL1rY3OO2z4PIOHzeEV39owGn7rFTdOUUodKSsJfNE2jWw6KCEzTGBsOh34w/4Ntj857fwtzkGgIWbIiHmgObnyo9IzNwUFfIK1qqitb2VT3DZSWvYRQeGKvO4gAofAyGObzK6OLGA5EQ0D8ziVlAL4fUHPbADyY68ZVj+1MANjt85hFd4MqDR51i5vK6hY3faOsrPSlcDjUaw6KCMLh0DLTNJ5fdE2UOUg0BCxZER+wHNy5qWrI5eCgLpBWNdVdAeAlGOYXEArn97mYZi0c534WSURDwucBvCOAdiwAHy+9a2O+E3s/4/O4RRUMNHjULW66AsBLpml8IRwO5ZWDpmnWOo5zP4skoiEh0Bzc+FDpGZ2Dg7JAWtVUN35VU90vAPxOA1NQUlJYQ0rdAOCfA+waEfWz+J1LzgfwTwE1963SuzbuLWA/v8FwSdNVs0p9tkFnkLrFTePrFjf9AsDvAEwpKTAHFXOQaNBbsiIeaA5ufKh0QHJw1uKmosnBQVUgrWqqM1Y11X0cwJ8AfAgAoBRg+Jpr4hsro4tuC6B7RNTP4ncuEQA/ABAOoLkGAN8ocN+dPo8dBnCRzzboDFC3uMmoW9x0Wg4qpWCahp9mv7HomihzkGgQWrIizhzsA4OmQFrVVFcLd5aM7wMYcfIFFcin8L2V0UUrgmiIiPrVNQAuC6itT5TetTFayI7eDHSv+jx+UQ0voOJTt7gpYw6qgHJw0TVR5iDR4BNoDm58qLSgHPRmoBsyOVj0BdKqprrhq5rq7oZ789eMbhtIYJ/CAyuji64KqjEi6lvxO5eM0lrfHVBzj5TetXGDzzaG1PhrKh51i5uG1y1uypqDSgV2C9EDi66JMgeJBoklK+KB5uDGh0qZg56iLZBWNdXJqqa69wPYC+DTyNbX3FbozYUB4Fcro4vmBtUgEfUdRzvfEZGqAJqKAPhkAO34DYa6pqtm8WZ5OqlucZPULW7qNQd1wDm46Jro3KAaJKK+4zhDLwdnLW4qihwsygJpVVPdJACPAvgNgHN63Ni2gjx0CYDHVkYXTQ+yUSIKVsfnrpgnkJsCau6rpXdtPBhAO36DYSyAdwbQDxoC6hY35ZyDlmUHeegSAI8tuibKHCQqYlcs75gnElwObnyolDmYpqgKpFVNdaFVTXWfg3u2LLfL/FoDjhNkNyoAbF4ZXTQtyEaJKBjNn50rEHlUJJCTTC8DuCeIhuCOvc51Ub1simqhPOp/dYubQnWLm/LKQa01nD7IwUXXRJmDREVo7vuaRQTMwT5UNAXSqqa6WXBX4v0PAOW57icAkIgVfmBlQMIlkNJySEkZpKQMMMNjAHlyZXTR2wtvmIj6gkBWmcocHlBzt5betTEVRENVj+104N5A70fRjL+m/le3uKmgHASAWKzwRewNQ6GkJIzy8lKUlZWgrKwE4bA5RgRPLromyhwkKjIisso0g8vBjQ+VBpKDOzdVDZkc9DU/dhBWNdWNBnAXgJWFtiGWBZ1KAqE8ZjhUChIug2SY/UcMEzoUHgc7Vb8ytvjC1WWb3ii0b12FK9eHAUwAcAxAJHlkWWCDx4nOBIYy7gioqTWld230Oxygq2cALPWxf1EEA/WvusVNvnPQsiwkkymEw6Gc91FKoawsnHEWPNM0EA6HxqVSdv3ia2MXbvp5GXOQqEgYRnA5uPGhUuZgBgNWIK1qqhMA1wK4G0Cl7wbjMUAZgJHDWhBGyL1q1MOlSREBzPBIiHplZWLZlNUl648V2rVw5XoBcD2AqwHMhTt8AQBi4cr1ewD83ns8mzyyrPDTgERnAFOFJvltw9EOWmPHfzMhiA6dzm/QTG26ataYqsd2+h2iQINAnXszcmA5GIvFYRgKRg45GAoZKCkJ95qD4bA5Uil5ZdlHElPW/7SEOUhUBEIh038OOg6OH2/9jXuuIlC+c3DW4qYxOzdVDWgODsgQu1VNde8EsAXAzxBEcQRvqF0sAti93Kwqqtfi6LTNDXOEmGbB3+xw5fpxADYCeABuRV2R9nIZgEsBfBHA0wCaw5XrHw9Xrv9suHJ9TbhyfdEMgSQqFhLA+1Y02QFb24+9euu0vw+iT2l2A/A7VKEoxl9T36pb3BR4DgJAJBKD3UsOKiW9FkfpTNMYYTIHiYqI/zVuOjqisG37sWl1rzIHM5AApwft1aqmuhLtON+EyO0i0idXr7QIUF6RdQFZKSmH5HKVqQsnmbhhdfjRB/LZJ1y5/iwAL6K3mfiyOwLgSXhn1pJHlgUxwwjRoPXm7dNlTNlYx8+NqSk7iROJVgCA5ViphJV423n37m0Kqo9NV816FsDMQvfXWv/buA3P/nNQ/aHiUre4qcRxnG9KH+agiKCiojzrArLl5SU5XWXqKpFI3vDoA2HmINEAmr7gTRk7doyvHEwmU2htPQEAsCwrlUgk3rZ3x3mB5eCsxU2+c/DZx8cNaA7225mZWw5dfJN2nOOi1Gf6KhQAQLQGopHMM9sZZkHFEQCIYfxLPtt7wwnuReGhALhnFa8BsAbAgXDl+lfDlet/EK5c/4Fw5frRPtolGpQmfvc57Wi74FlZtNaIJNtP/ttUZihkhLYG0rlT/A0v0DnO4EmDzsXzD93kOM5x1cc5qLVGJBLNOLOdaRoFFUcAYDAHiQbcc09M1Lbt+MrB9vbIyX+bphkKhYosB3OdyboP9UuBdMuhi/9dQuE1otSw/jieaAeIReLQOn7a82buN692o1S+gzQXAQj6suU7AXwMwK8BHAtXrt8Vrlz/zXDl+svCletLAz4WUVGyHKvgN964FYWtTx9+FFKhqX++dWoQC+118hcMggsaF84sCagvVCQunn/o38Ph0BrVTznoOBqRSCyuu+RgKFR4XaaYg0RFwbIKz8FoNN5tGG4oFJo6ddafiycHgQtmXtk4oDnY5wXSLYcu/raEwncENFd7rjaI40yFyHwAUQDuvUdG4cEgooyV8aXVeezS19WvAjAdwOfhDj9oCVeu3xKuXP+5cOX6Wo7bpqHK0fa/FTI02HZsRFPRbs+LCAwxbguibx5fwSAioh19RVCdoYF38fxD3w6HQ/2eg47jTJW0HFRKYJqFXT3y9jeWXhdnDhINMNt2CstB20Y0miUHjSLLQT2wOdinbx63HLx4lJihT/VjKLwJ4IMAlt1XtaNhdfnjOwB8AEBKQj6uHnkklMf8qcB83wfMTymABXDXz3gBwJFw5fpfhivX3xKuXM91LGjIGP2dp59K2PG87oPQWqMj2QYgc6B4f0QGouqxnU3a1j4WZwOg9YUBdYcG2MXzD44KhcwBycEdm6oaHn+4/GQOhgLIwXA4r0aYg0R94OlHRj8VjyfyzsG2tg5kq6uCzMGdm6qatPaXgxoY0Bzs22m+lfxUlCr8dFXuHADfBfDl+6p2tKe/sLr88d+tjC1ZCSP0Ez8H0NpxxDD/msu23rjrfM6yBU7C6iwJyXIxZTkAlE7ZFAXwZxF8V0Lql9F9C/39AUc0gCLJ9hsV1PSwWTKtt2211mhPtMFyrJ42635KrUAH62rPNStCZYXe5wEAWg/s+wcFR0T9VPVzDu7YVHTQWPEAACAASURBVHVaDj7+cPnvlqyIrQyFDF856DjaMU1j8OSgqLNEZLmIl4Pj0nJQ1C+jh5mDNHi1t0duVEpNLykJ55SDbW3tsKz+ycHaeQfPDYXMMsPHFWtAD+j7R59eQRJl/F1ftu/ZDWD6fVU7Pt21OOqkyoZV+j575zhH78W6nK5neoveBTYbSF5MgTHShDHchCo1IKaCmAoqrMpVWNVKSP1Ea32i7F2PP1Y+dfNN5VM3BznmlKhfTPzuc/r11v2Lj0WOpGwn+5TGKTuJtkQLUk6ytyaPBNi9lU4qwyQxeRAlhwLqCw0ww1D9loM7NlV9umtx1GnYsDLfOeg4ztF1q7Nchu1iQHMQAsMwYRgmlDIgoiCioJQqV0rVing5OP7xx8onbL6pfAJzkAaf556YqPfvf33xkSPHUj1N7Z9MptDS0oZksteZt4PNwUyTpeVBMLA52LdXkERG9GHrJwD8M4B776vakfUn41YsNwB8PIDj3Z/n9o3o57NnElZQFUava1t4syct9R66fOrmPwJ4DMB6AK9E9y3kquZU1OpvnmQAeOBo9EgolopiZNkomCoEU0w4cGA7NiwnBcvJbSkG27G3BNGvg3W1JQBudFI2tDZzXmcmndYa2tH5vt9QkZJ+ysEdm6qy5uDylThzclCUVxTlmYMTuuTgYeYgFbdJNfUGgAeOHDkaikZjGDVqJEIhE6ZpwnEc2LaNVMpCKtXjVaOTbDuYHKydd7AEwI2248DUuvAc1AObg31WIH30QG2pUVrWV1eo1gH49H1VOw7nsO1SAL5WHNZap8Qw85reFG4fC54DPm8GciqOMhC4i/RdCuBfAbxePnVzZ0hsj+5b6HexL6K+8E8A5gBAR6oDDhxUhCt62SWzlJ06EUlFfhpQv94P4Gw4gJN0YJTkP7xAW7pt4u+feyug/tAAqp13oLSsrLRPc3DHpqp+y0HTzG+ab/R3DgI5FUcZdM/BCWk5eJg5SEXpVA52dMBxHFRUFJiDqdSJSCTgHNSA4zgFLSugHd323BMTBzQH+2yI3Y8n1ce10/Og/wK8DmDRfVU7PpRjcQQAnwjguD+4F+vyHav8IwAtARw7J0ZFYWerM3g7gNvhLsp3rHzq5l+UT918bfnUzVxvgopC/c2TZgL4evpz0VQU7Yl2FDKrj+VYd9euORDU2eJbO//Hjuf/9qe1hp2w/zugvtAAq986Ke70UQ7u2FT1oRyLIyCgHFy3GsWdg0Yf5eCEzb8on7D52vIJzEEqDpNq6rvnYDSK9vYCc9Cy7j6wpzbwHLSs7EP/stFaw7YHPgf79B4k7TiBVH9aaziJOKyOE3fdV7Vjc6773YrlU+FzFh2ttSMi/5nvfskjy9oB3OHn2DlTgJh98q0cAeBDAB4CcLR86uat5VM3f6Z86uZz++JgRL2pv3nSCAA/B9DtlFTMiuFE4kRe4RBJRl5oT7Z/vfcte3ewrvZd8M7mAYC2NFKR/E4821Er7iTsfw+iP1QcnABzMB5P4MSJjrt2bKrKOQeXr8SZkYNwh9f1gdNzcMLmreUTNn+mfAJzkAbGpJr67DkYi+HEiTxzMBJ5ob09mBysnXfw9Bx0NFK93/t0Gitlx23bGfAc7Nt7kBznMbgLuhVMWxbsRAxwHGitf3jTq1Pfuv+8fetz3P0f/BwbAERk/b1Yd6CQfZNHlv04XLk+DOD7fvvREwn3y1IPBoC53uM75Rdsfk0M2SmGbJWw+l9RchzAiRM75+d/uoAod98D8I5sLybsBFriLRhRMgKmyv72prVGJBVpiaai8wO8erSq6xNO3IYFwCjv+cy21hp21IIdt++v3lHfEVB/qAg4AeSgZVmIxRJwvBycOuvVt/btPK9fc3DdahR3DvZNcdTV6Tk4YfNrIrJTRLaKqP8V8XLwIHOQ+lTPOZhIoKWlBSNGjIBp9pKDkUhLNBqdH+DVo245aNsOkLJgmj0Pf9Vaw0rZsG37/vqt1QOeg1LIpbhc3XLwIkPMULMYRt43qWrHgZOIQ1unV55aa8dJJK5ee+H+3/S0/61YPhLuehB+Vy2ffy/WPeWngXDl+qsAfAXAxT77kpEaZkCV9sMssoZAlSqIKRl/yLXWWkROAGiFO6wi34/xEzvn88ZYyqj+5kkrAPws1+3LQ+UIG2GEVAgi4l6J1g4SdgLRVNRxtDO7ds0Bv6t9AwAO1tWWwX2/yTwERwnMMhOqRJ32u6MdDSflwIpagKMBoKZ6R/3/BdEnKg4XXXbQCIXMZqOAHHQcB/F4ottN1lprJ5FMXL1/94U95uDylQgsB9etRnHnoDLQP7OpC5Ryf4/7LAcPMgcps0k19fnlYHk5wuEwQqG0HHQcJBIJRKNRx3Gc2Qf21AaSg7XzDvaYgyKAaZpQRpcc1BqO7cCyrM41mmrqt1YPeA72aYEEALccuvi9Ego/ks+4YCeVhJOII9tqVtq2k04yWbX2b/7amq2NW7H8dgD35N3h0+0FcGGu03v3xFsTYh7cS/WXo4fqP1+q3IAq69tgUOUGVN9fqUoiS3CIKUrCMhwajRD8XsJqa8vjcxJ93SEqDvU3T3oHgBcBDC9kfyUKjj5tytGv1q458LUg+gYAB+tqrweQ2w2uSiAKgAa0fdpby87qHfV1QfWJisfF8w+9NxwO5ZWDyWQK8Xgi61AZ27GTyWSy6q/P/03WHFy+EoHlYK7Te/ekT3OwHwok9xgDmIMiSkSGw50d8Pei1NaWvzIHzxSTaur95aBS6DL19lcP7KkNLAdr5x3MOQdFvP9odH2P21m/tboocrDPCyQA+GjDu29T4ZLvSS8zWWjbdofT9TCfeyc7kdix9oLX3pPptVuxXAH4E4B3FtLfNB+/F+t+6LONjMKV698Bd1z45d7HswptS8oUjPK+Gy3ZT8VRlmMrSImCqNP/sNCOdnRSPwno5a2/n5f1DwQa/OpvnhQCsB3uDFNBeAbA3No1BwK7ef5gXe0zAPy+qd9QvaM+r5XRafB499yG20pKwt/rbUYn27YRiyXQ07omnRLJxI7XnrsgYw4uX4nAcnDdahR/DoqCYfRhDvZPcZTl2AqiVLcrVlprR2v9JLRe3trAHBzKJtXU90kOHthTG1gO1s47GEgO1m+tLooc7Jff9h9PfvH7dizyWTsRh87wpq8tC3YsCjvakVNxBAAqHK67ce87x2d5+Qr4D4U2AA/6bCOr5JFlf00eWfaj5JFlHwJQCeAiuDezbgEQz6ctney7IldK1MAUR6bAGGVClRndiiMAECVKlaoFElZHRy14+qP930HqR19GcKHQBmBFwMXRhfAfCq1wp0SmIerFpyd/PxKJfTYez1z8WJaFaDSGjo5oTsURAIRD4bp3Tt/LHES3s9CB8haZ7bP2ezgwDNOEMjLfuyEiSim1QJQ6OurtzMEhLvAcDLg4GnI52LeTNKRZM+Xlu29+7YIqO5m4A6K862vaHUZXwBubiMBxnBUAvp3hZd83pQL4yb1Y5/smsdnHF49QYl4PoFZDNwjkJctObPrD2N+dvLkqeWSZA6Dee3wrXLm+FO4P2uXe4xK46zRkZmvolAMJBf8GrkoGIBQUYAzPXBh1JUpMhPGj0Yu3TRElX2zeMJs3xw4h9TdPmgPgCwE2uap2zYGCbjbvqc0A2nigekd9vlMo0yDz8h+m3H3Be16rSiSSdygl3j0BJxdFzLu9/sjBdavhPweXHR+hlLg5qNEggpcsy970hw1jg8tBaGjt9MlkDQN15cjIUhh15S16+6PR79g2RUS+2LyfOTiUTKqpDzwHD+ypLcocrN9aXTQ52C9D7Drd/NoFCu7NZdcE0Z6dSDy59oLXLk9/7lYsnwLgL+jxjTQn592LdX8pZMeZjbNDplFyc0l4+NcNIzS26xu27Vgp206sFajbt45+pNezZOHK9WPgzprTGRTdzgqKKVAjAlsDwm0zJDCG9VsNfZIxwiio2NNaPyEi1zVvmH2kD7pF/az+5kmjAfwfgHMCavIntWsO3BRQWwCAg3W1wwAchjsVsB/TqnfU7wugS1TkLnjPa4HmYCKRePK13RecloPLVyKwHFy3GoXl4JWNIdM0bi4pCX/dMIyxXbPJtp2UbdtrRXD71t+ODiYHRaBUwDko0qdD97IxDANSQGF2Mgf3MweHgkk19YHn4IE9tYHmYO28g4HlYP3W6qLJwX49LbLm3FccADcC2BpEeyKSaTD3bfAfCo8XUhzNbJx9zszG2V8LmeVHysvG/NA0S7oVRwBgKDMUDg27RSnj6Ozjiyf21m7yyLLm5JFlv0keWfbx5JFl5wGYDOBmAA8DOAq4a644HXagwwzECC5kcj5mSAq+EiYiCwDUj1m6fXawvaL+Vn/zJNFaP4DgQuEvcBd+DNqH4D8UtrM4OnO88sy5gyYHCymOZl7ZeM7MKxu/FgqZR8rLy35omma34ggADEOFwuHQLUqpo7OXHQ8mB7WG4wScgwEWW/kcs5DiyNvXzcEpzMHBblJN/RmVg8VUHAH9XCABwJpzX0kA+IDW+mW/bWnH2Z/+71uxfBiAICrjnFfwndk4W81snH35zMbZvwHQYBolXy4vGz0ql8v8hhGuCJlle+e2vPfsfDqXPLLsQPLIsvuTR5ZdC2AcgHcD+EeddDY7HXaiy8xYhRuIYAj7PuYEAFvHLN3++TFLtw/MuAjyLaWtL4rIVQE1ZwG4tnbNgb5YV+HW3jfp1X0BtEGDyCvPnBtYDjr69BxcvhL9n4NXNqqZVzZePvPKRjcHTePL5eVlo3IpLgzDqAiFzL1z39cSTA5qZ7Pj2IngiqSBKZB8cnNwyvbPj5nCHBysLCsVeA4e2FPLHMzRgPzirDn3lVY7ErlTnz7dYP60fqHLM9cBGOmvUbwG4He9bTSzcfbomY2zPw13lqAnALxfRBllpZmXQcnGMMIjAGwspKOAO247eWTZnuSRZd9JHlm2SCedkXZb6nInZm/Ulj5RaLsABiIXgrqPSgH4JoANY5Zuzyt0aeDtvHHcpSaMQFb19nyhds2B3QG2BwA4WFdbC2C6z2aOAfh1AN2hQeaVZ85tjUQjdzo+c1A7A5iDVzaOnnllY5ccFKOsrDSvg3lrRAWXg9oZadupyx3H3qi1zxwcAIVePeriVA5OYQ4ONuPetfNSwzADzcEDe2oDz8HaeQeHbA4O2JkFJ5l8t9XejkKLJMeytJ1I3N/571uxXAB8IoCuff9erMvaqZmNs6fPbJx9P9zxlncjbRx0OFRR0DoMIbN0xpzmq8YV0tmukkeWJZJNy56MNyxZGvvLopEAJsK9eW4j8p0VyBr0a9Utgjvkrijm1KfcKFE/DXBYy1PIfAO7b1oHclPq2uod9VzH5AyVTCbf3d7e3nWNrpxZlqUTaTm4fCUCy8F1q5E9B69snD7zysbMORgOFTSpQShkzpjz3ubgcvDIsifjby1ZGmv0mYP9eJ92H3FzcApzcDBRarDkoA4kB+u3VhddDvb/nYenXKFtG1ZHB8zhw/O+pGzHYrsfvOTN9De6OQAu8NmnCICfdH1yZuPscgAfBvBx9LAKeMgsKeigIgoi6jsAVhTUQA+i+xYeBrAawOryqZuHwb25dRmApXCnVc1KpxwA/bEyefpBA2/xHADbxizd/nkA32neMHvQp91Q9ocbx84rlzK/UxN3Og7gI7VrDvi8VN1dwyUXT5AQgphWd3UAbdDgdYXt2Ojo6MDwivxzMBaP7X7zlUv6JwevbMwtB0OF/VkhIhCRvsnBw2k5OCHPHNQDkIPBc3NwipeD+5mDxWzsO/8wr6ysPNAcPLCnNvAcrJnTMEFEhmwODkiBdP2u8cPhzZeuLcstkioqcg4HOxaDTqV+0eXpIM6a/fRerGvr/MfMxtnnwx1beQOAUT3tKBAoFSr4wIYKzSp45xxF9y2MAHgUwKPlUzcrADMAXAU3KC7stoMGnKTTr+sgaVtDzMDH9pkAvgXg78Ys3X5D84bZLUEfgIJhwlgZ4Fmzm2vXHHgzqMY6NdRMPw8mnhbx/VfTk9U76guaIYwGv/HTdp3MQcuy0BHpQMWw3HMwFosh1Uc5uG41TuXglY2556D4mxLbMFTf5+DhtByckEMOAnAcp1+n+tZa98XkEKdycMr2G5r3MweLlWGYgebggT21gedgzZyG8wA8nWWSmHw8Wb+1uihzsF+n+e50/a7xVwFYf1pHDMO9ktTDm5DWGnY0CieRAIC/eXBG48sAcCuWVwN4Hf6HDF5Y3/jWq3DfKD8Gd2XvnIgojKjItl5f77TWlohUbKl4eEAuM5ZP3fx2nAqJOegsngUwhps5rUkUBAkJjBF9WrcfALC8ecPsXX15ECrMszeN31UiYb/jmeFo5+cX338o8DPRDTXTFwF4WEqtkb5jAbi6ekf9//jvFQ1G46ft6paDhmFgeMXwHv8Y11ojGosi4eVg494ZLwPA8pUILAcPHGgsMAcFI0ZUFHzgkzm4rmJgcnBClhwEYBjBTh/eE/EWiO1Dbg7uZw4Wo/FTn90VDpf4z0HH+fmhly4OPAdr5jS4OSgyMoDfiavrt1YXZQ4O1D1IV3R9Qts2Um1tsKJRONbpi/tqx4EdjyPV1tZZHDUCeCVtk1vh83NxtH6mvvGtqwE0APgf5BEKgHsZ3k+x6S301udnz7KJ7lv4enTfwu9G9y28HMDZcIdS/BwarXbEhnb6p5DWKd3X9z5NAvCHMUu33z5m6fYBmIaCeiIQ3zcTW9pCs9M684kbhp8VRJ8AoKFmujTUTP8nABsBHURx1AT3LDadubrloG3baDvRhmg0CqtLDjqOg3g8jrYTbZ3FUfA56OhnDhxo9JGDhS1422nAc/Dwwtejhxd+N3q4Sw4CrbYd7PThPfH7dcyBm4NTtt8+ZgpzsNiIBJCDloXW1uaZw9/2RGA5WDOnQWrmNHg5iCCKo6LOwaIpkAAAWsOJx2GdOIFkS8vJR6q1FXY0Cpya0GHLgzMaNQDciuWljta+53VvaGmdBeArcKfHLIgu8EbbNAv8NhCE6L6FbdF9C38Z3bdwBYBK2Hqe3W59z0k6/TIbkN1h9XVBFgJwD4BfjVm63e9sTxQgDe1rdW+tNdqdCABMAfDIEzcML+zGwDQNNdPL4f6RdBcAgQrkZ/P+6h31qSAaokErYw5qrRFPxHGi/QRaWltOPlrbWhGNRZE2692Wxr0zNAAsX4lSHUAOHjvWEkAO+v79KI4cPLywLXp44S+jh70chJ5n29b3HKefctCy+rpIOpWDU5iDxURr/zkYibQDXg4Of9sTvnOwZk7D6TkYjPvrt1YXbQ72+z1I1+8aPxnAeb1u2PMbw5bO/4lbqc+VmqFhfvqUtG20JRK+i0XLTiCsyv00cTmAL/jtR5Ci+xamADwN4OnyqZtv1ylnlphyNZRMF0EVRCwo2ABKRGQ03DHq/s6v24DdbsMYYQS7IropUKaCGAJRAq31BwEsHHfds9tESSPc2Y1i3seeHr1u0/jTmYHfEHkmsLW9BYK5he4f0VHYsDv/+bcA7n/ihuHXLVjbXtBfGg010ycD+C3cNVZcPt8ptIYWwY/8tUKD2fhpuyYjhxzs5Q/kkzmYSlmfC4VMXzloWTZisQBy0LIR9nffavHl4OG0HJyw+XatnVkicjXg5SDEAgLOQbhXFA0j4BwUgRLVOSkGNLwcfNez20QCzsF9zMFC2La9BSg8B6PRCGz79Bwc/rYnrms/tKCgHKyZ0zAZXXPQJ621FpGizsGBmKQhiLNDv+/8HyXyKb+NdSTjGFZiIJa04efChWUnEA75KpAuuaLjmtFbKh4uypsno/sWagA7vEdGI2Y9KQCGAegMid4+dn3OHcBuadhtFowK0/ekDWIKzDITKvMaS8MALPZ1gAzGf+SPSQBxCBISUqJMCcEQAxonADRoW//Kidn3NP50JmcTSqOhVzva+YYqYCGQpE4irrvdunAtgP0Avpxvew010+cC+BXcoTbpnfRH44XqnfWv+2yFBrdAc1ACyMFEIonS0hIkk0k4PoLQLZAKn7AIwCVXLO8YvWVdRXHm4OEccrA6oBzUGrZlwTD93/8kIjANM9v9bX2Tg1O9HAQSopQokRDcm/rdHNT6V45t39O4jzmYTmu92nGcb6gCZgZJJpNIJLrNZF9wDtbMaZiLTDno3wv1W6uLOgf7fZKG63eN/xWAv/fRRP2DMxovAoAPRBedN7as4s9+3jgcrXGovQWON+Y3lrSRtAv7mogYGFHhexmHv99S8XDRLZjVX0bMetJEemAojDOGm58RU+YW0p4KK4QqfIV1wVRYQZVnP/vnWE4bbH3rG/de0nUmqjPajhur7i5TpZ/OZx9HO2hx2qCzVC8a+qYr1nZ0m7o4k4aa6QLgNgD/hUxngUVDldvdns6VtuW2SX984QcFN0CD3vhpu3znYOPeGRcBwKJroudVVJT5ykGtNVpa2k/e+5JIJGFZhf2M+52owfP3W9ZVnLk5WN0lB4Fxhml+RqTAHFQKIXOAclApqB6ugjmO0watb33jZeZguqrzd9xdWlqWXw46DtraWrJeedZa39TxxhU55WDNnIaecxD+ZqzUWt/24tOTijoH+/UK0vW7xhtwL5/7cXJ171IjtMTvWZVIKgHH+2ESEZSXmFApG/FU/leGtbZhOxYM5evLejmKcEXh/nJi53wL7qrKx9KefmzM0u03AvgBgJyXaBdTYA4bmKW+jGFmr9OjK1ON1IZ+eOLK3W9/c/Ul/9ZPXSt6ER39rKHV8rCEJ+ayvaMdtDntWYsjz5rNNw7Dwp9EegyHhprpJXB/zm7KupEGtANIAdmgHSTF0EW55gP1j/HTdgWag6GQ4TsHE4nUyT+qRMS7kpRCMpn/7QFaa9i2A8PwPczuzM3Bg1lycEoBOehdORoIhpn1itVJSqmRWuuHJ164++1vvswc7BSNRj6rlLE8HM4xBx0H7e1tvQ3LXTNs4mZE3lzYYw7WzGnoPQdR+HT0WuukiBR9Dvb3JA2XoJd1FHJwcty1Epnmsy2c6H4pEiWmglFg3lhWXot0Z1IUN6gWm+YNs38Cd72KP+e6T2hYqN+mZU2nSo2c144SEahS9c1zPrb7g33crUFjwdp2HXFiF0ad2Fu9XeG2tY0250T6fUcZCUSUlvsfv7ks69e5oWb6BLj3GfQYCoBAJwt867RldfWOeqv3DWkICzQHJYAcjMe7z6odCplQBS7v0HUGvgIwBzNo3l9ADpoDlIOGkfMVBhGBUuqb51zIHOzUfmiBjsUiF8Zi0d5z0LZx4kRb+n1HGYmIiKj7y8Y/nvXrXDOnIccc9DUhy+r6rdVFn4P9XSBlnr0ud1Gkjfu1HKfRT2NxK4Wk0/0HSkRQVlLYGRfL9r18w5QrOq55u99GhqLmDbNfAjAd7kwqPZKQQAqtcn0QQ6BK8/u1EhGIqR6q/mS973EpQ8Vla1tbozo2o81pPxZ3EnC6zBBpaQvtTgdanDbYyO1qr0CgHPXLjbeULu36WkPN9JkAdgO4NKfGbIHOcwSStvGmtuWT+e1FQ1CgOej4zMFUyoJtd/8dEhGUlBQ2+VWhw/PSTLlieQdzMIPm/XnkoDcRQ3/zCp689xGlHqquYQ52am24rDUWi85ob287lkjE02ewBOAtMN3Rjra2FjgZ/pbNxPve/LJ03MZuOVgzpyG/HET+RZLW+k2t9aDIwcFWID394IzGkxWIqdRmP42dSGa/2mMqQSHvK5aVGDLTnBaj5g2z2wFcB3fNj6zVqBH2v1BNIVSJKiiQREmJdvS9fdClQWvB2vZDFqwrO3Qk0uy0otluxXG7BcfsZrQ6J5DQybzbVFoZ4sijG28pPbl4XkPN9BsBbAeQx0rPAh03oK3cvtfaluPQctHkF57nrE7kOwcb9844+d6nfOZgPJ7998gwCns/s4KZopo5mEXz/hxzUA1QDqoCc1CkRGvmYLr2QwsOWZZ1ZSTSEWltbUZrazNaWo6jufkYTpxoRTKZ/0l5pZQhIo+Wjtt4Mgdr5jQUkIP5rdmltT4O4KI92yYPihzstwLp+l3jR8D/AnBb0v9RES55NmlbBV2ysRwbkVTPf2CZBQ0v0LCdnsdtCwwoKfMepRDpdvOk3/HpQ1rzhtm6ecPs++D+PL2WaRspcGiIX5J5przc9lWyovqT9fyjIM2Cte0vwF2s0XHg9HafUU6UFgXgZ5tuKr+9oWb6dwHcDyCcf0sCnVBwkgrZlkDTGtApeVEnVPWkXS8c8dFtGgLGT9sVeA6WlISftQocumDbTq/3GRV6L1Gmq1LpRACl5OQjwx/UzMEeNO+frZv395KDA3D1CAAKmIT01L4iK6prmIPp2g8tOJWDjhPI+ljifpN+VjZ+0+01cxp85KBbJPXUL6+IelFrXf3i05MGTQ725xWky+B/XYDTguFerHPilvXtQho6Hov2uo3K/83FBvBbAR7O3F4JQsYYhMzRMI1h3qMCIWMkQsZoKDl53+X8KzquGZhTP4NI84bZ9XDH8//PQPcFACCBFGb3V3+ynov2pVmwtn0DAN/TGHcSLTBSBqpfnXQPgE/4bA1IKeiYASfuFUtJgU4KnJhydNS4QyeNiya/uLv3Nxw6EwSeg+tWw7EKzMFoNNbrNgX8ke3moGTJQSUIhQyEQiZM0zj5cJ8z0u97mn/F8g7mYC+a9xdZDiKQwuz+6hrmYLr2QwuCzUERGIaBiROrA8hBV2eh1Fksef92tNZ3aK0v2rNt8qDKwf4skPwOK3gDwJ+6PjmipPRLcSv1Zj4NRVIJRK3eh+c4OVbphm2fGNPSsqn2lZc+P+/ZHeur9/+pW38MVQHTGA7JMvWViAHTqICpRgDAGAC1OR38DNe8YXYbgOVwf8EHdkXmYGbMPwfutJqUZsHa9v8G8N0g2iqNlOIdL5+LivaRcP9WDeJtUABbucVSyoBOGa1w1OLJe3Z/a/KeT4wCvQAAIABJREFU57jGB3XqkxwsLS35Uipl5ZWDiUQKyWTv90nnerbatu0TbW0tm/7851c+//zzz65//fX93XPQUDDN7FM+i4hXMCmAOZiz5v1FlIPBYA5m0H5oQWA5WFJSikmT3oFhw/rmli+vQGoFsHjPtsnf2rNt8qDLwX5bB+n6XeNfAzDFRxP3Pzij8eZML7wvsnD0yJKy+jIzNKm3RjqSCRyLRXIaqtMRt2D1sGDeqLZWTGxqwtktzVBaw4Q7b7qIws5574XjTa1pqGEwVFmvx+vkOElYzokvbql4+F9z3okwZun2SwCsA/B2VaIQGtb/6z6YowKbMei9B++pXR9EQ0PFEzcMN+Cu5n1VoW2MajobY986B4LTv0/aHQsHrZNAjpM+9GAvgPdO3vNcxmEvdOYaP22X7xxs3DsjYw4u/HBkdFlZSX0oZPaag4lEEpFIDLnEfywW73G43IkTbTh6tAmtrS1IP0skIpg9ex4Mw70IZBgqr+F6juPAspwvbllXwRzMw5gpaTk4QOsfmaEAc3APczDd8Lc94TsHR44chbPPHtttEg+3qPE1O126vQDeu2fb5EGbg/1yBen6XeOnwF8oAF2GFaR7ZNjmFgBTOpKJh1NZ3sktx8axWAeOxjpyKo4crTMWR6Zl4ZzGw5jxYj1q9+1FZfNxKK1RAqBUAFMAAw5GthwFAIiE8iqOAECpMJSUreh9S0rXvGH2bgAXAXjESQYzTjdf2grsmKurP1l/VlCNDQUL1rbbcFcEry9k//GvT0blW2+HknC38HZnUApDGRWAFDQMu9OjAC5lcURdjZ+2q09zcPMvhrUAmJJIJB+2s+SgbTvo6IihoyO34shxdMbiyLIsNDU14uWXX8Rf/rIPra3NOFUcCQCB1vCKps7hPPn9uaGUglLCHMxT8/60HAzofpV8BXjM1dU1zMF07YcW+MrBcePGY+zYyowTabgz3Ik3OYuvbj4K4NLBXBwB/TfEzu8NdxrA73va4AHzt/bPwo9e2xhpqzwW63joeLTdbo5F0ByL4M32Vhxqb0V7HrN9JLosFFvR0YHz97+Guhd2450HGjAsfmrsdhmAUJcfptHNTQAAUxV2+dJQJe9a0vohTneZp+YNs1sBfAAan7bjvdwl3AecuO/pbTtVAfh+UI0NFQvWtncAWKqhj/W6cZrxDZMxor0yp7OaSpVCpKDpjb8G4AOT9zzXXsjONOT1eQ7+9iem/egD4Wvb2iKVHR2xh9rbo3YkEkMkEkNraztaW9uRSOQ++2MqdfporUikAw0N+/HSSy/gjTcOINFtHcHTf7+am5sBoHPIXN6UUu+67AOtzME8Ne/3chD4tO0MQA72sh5PHpiDGbQfWuDmoM4vB6uqxmP48BE55mBhMxHCy8E92yYP+hzslyF21/9x3CaILPLRxHMPzmickevGn/q1Gq7CodZj1dXq6DkT4Zj53edpOxrtcQvKsVF5/DgmvvUWhkc6kOlHJQSgJMMLkWEjUF93FUxjRF7HTle9d2vbhIN/egrATu/x/BffZ/V+Vy0BAMYs3V4XGh56UoVUzquOB8EcbkIK/IMggw8fvKf2l0E1NlRsuaHiYgC7BFlu6kszrGUEJh48P+83e8eJATqn4fwdAD4yec9zv83rAHRGGTf1j5vEZw427p2Rcw6qMb8eHgqFW6urq9XEiefAMPJb28+2HcRi7torzc3HcfToW4hGIz3s0f33a9iwYZg1q+7/sXfm8VVV58J+1h7OkJCEQCAHEJSiOFStaK1yFY1a6xCHoAYvrbX32jrV621tr/p1+O61vUM/qa21vdap2lta61WoRmusigOWKhFbkKpFRGaRBIJJyHSGvff6/tgZyTnJOXvvk8n1/H75ASdnrb3IOdnPedd617swcnRwX955528tO3fu6OdBq7FKeTBLJs3549+Zhvmipg2zBw3DVzW7A/j7HeuVBw9kwkHPux7MtLm9D4WFhUybNsODB52sVpvp8uD6Vw4ZNx7Me4D0xTXTDKTsRAhvJ6+6/OevP7P7u9k++eu/0+6NaNq1AJZpUD9rJntnzoQsKoxZtoPd0sb0hgam7d2DOcSJ4IWQdinSAV4/+8sI3Xu6TvmWN5j93p/7DQ93WbWOXlls/25VcHld440pl746S5jiec3UDh+ukqdCF+hFRlA52B8Bn9xx17z6IDobTzz3j4VfEVI8INJOXfTyib8dg2nlluYKXfnYTjtD7EnajLvf6J2cL6D42DDtqDWGlLJT+PTg7r99JmsPapN+d6/W5UHDMJk5cxYHHTQzqwM8bdumubmFPXsa2LdvL7adzaH36X8Pzz777J59SF7YvHkLmza91/ehtB60GquUBzMw5bBXZwlNPK+JYfSgEOhGwB5crzx4IIUznvuKEOKBoX7OhxzyCUwz9/1obiW6IX+1NuPuNxpXHvRzs84KTcpzHH9SwHTkh7k8XxdiUfffjZTFQZu3MmXnLrYdPpf2yZPSlmJ2pERv62D2+5uZ3NQ0xEeuruuQPjgCaJ00w1dwBJCMDMgsMHBP0D4RuLGr/lbr7TXGVgEbBTxmQO1NapWph72/O2UHcMTURa9dLnSxRGhihtBFXkvHSlvixB30aCCXmQQ8MOtr6y7acdc89QGgD+f8sv0Xf7iqYKruaP+ZKUjSkzpGKpLps9ugCCFAK0A6bZme8jyw+JD1b3yUe++KjxNSynN8BkdIx8nJg6KPBy0rxdatm/ngg53MnXs4kyZNThsoSSlpbW1jy5b3aWlpyuVqaR+dNGmSr+AIIBodsPDRz4Ndj7UaZTVbgY24BQpq1SpTL3s3dXlw7muXCyGWCCFmCJFnD3aVfPb7+nfhevBT6y7asV55sC/tu875RcH0P0zVNP0/MwVJuq5jGN5uP+6+JAYLkp4HFq9/5ZBx58G8ryD9Y13sCUsTVZ47kJJCRyYEfOGe+Q2/G+rp1ywTJcW61mxkeKNYmqB+xkG0lk7EMg30lEVhWzvlH3xAJJl9bja4J2qFMnzw2vDpSlrKZuXU34FM3baWT7z7etrrGqRXknTz1N8VsILe2bUdN6lVph7KF6+OSSkP1UytXQgRASK4W8kiQ3zl9ByjyCgVRmA5Bv+44655/xNQX+OKZ74cvVJztIc0KfQDA6XivZOZttvfvngpU0hnwGetO4BvHbL+jWym1hUfc2JH1D0hNM2zB93VTCcBfKFh4/whPShKl5Vomt6cuZy2xrRpM5g0qRTDMLGsFG1tbeza9QGpIQ5Qz3DFtI9++tOfpqyszEN/vWzbto133x1Q2XwoJG459H4eVKtMvZQfvjomkYdqIs8eNIxSkc2yZXb84471yoPpiE575kpN0x4SQtMP/L0vLi6mvHyar/4zrCTdAXxr/SuHjEsP5j1A+ofXY2/YQnzaa3tdSqLuiyKBb9wzv2HQ2vjXLBMLi3Xt8UwBUpCEGVicAaC9qIy3Tqn23f8xf/wthR0tPf/Wuq7p4U6zG3iNXlGsvanKOnB3rSJgZn1t3THAX3C3qvllP3D0jrvm7Qygr3FH7dWRU5E8rUlRguz6pRSSKbtmMHXPkFWPh8Rx4iCTAHHgK4esf+Nh350qPjbEjnz9DeHDg10BEnR5sGHj/EE9KEqXLdQ0/fHhSqdKFyAVFRVxyimn+O75j3/8Ix0dgZwvOcCDVmOV8mCemfWpPHhwvfJgOiKx2lOBp4XQSrp/9aWEsrIpTJky1Xf/ffYjxYGvrH/lkHHtweGoYuerAo3eG8AJ4M7rV5ffef3q8sHG/bnhmiLKdJ0PZx/nu29hxfsFRwJ3OsbjCzYNuBQ32n8V2H9njVF3Z41x5501xqI7a4yZvgesGMCOu+a9BfxbQN0VAw/N+tq64frEM6aofCD+JwSnO5pscHQHR3dwNIllBHNmohBhpNBagFNVcKTwgC8PygM8WH746jvLD189qAf9XC8IZs+e7bsPy7KCCo4gjQeNspo6o6zmTqOsZpFRVqM8mAd2rM+DBz+lPJiOeH3ln4DTpXQaHMfpCmicLPcQDo0QAillC3DqeA+OYBgCJCFp9tPeGBiFfB147PrV5Zl2XX8uNfSGskBIt3U7Hi1iX8zvURcQ2/7Xfv8O4WkbRSZM4CTcn+WjwI47a4wP7qwxlt1ZY3zjzhpj/p01hqc6x4oB/BAYmCfpjc8C1wXU17ij8oH4emABsL37sfbi/YH0LYRAhsIl247cnnUVMYWiB/dEeT/tD3zk68Bj5YevzuhBKYe9unMP0WiUWCzmu59t27YP/STvDPCgUVbzgVFWs8woq/mGUVYz3yirUR4MBuXBYSJeXznAg21tg1WfzB53RVqW7Ny57WPhwbyn2F1VF/t6ShN3emkrpKTAkZkCg9eAi++Z39BTB/6aZWIO8L4ASn2UFc16fEAB/Qs1bD3yVBoOPsZXv5qV4NMv/g9al+A03ITeYSYJrKVPSsJNVdau4R/G2GfW19YdDryJuwjolw7g2B13zdscQF/jktqrIzNwN44ehYQj3zwRw/FXMKWb9gn72XboOzee91DHfwfSoeJjQeyIuq8LTfPkwT7pdel4Dbi4YeP8Hg+K0mVzgPeBnEt7+6NXhEceeSQHH+wvtdWyLF588cUROei0DwM8aDVWKQ96YNan8uDB9cqDmYjEans9CMyde6TnQg0H0tHRzvbt227s3H3euPbgcOxBitrQ7qXWY9hxMAcf3ibgvHvmN2wGuGaZuB74OUBUE0SDq8Gfkb6FGlJmhHUVV+Do/lJtZ25czYytb/b828DdezQSGLjV+jT3KymgTbglN1uGKq9MtoteUgqgVLhV00MCLAHvAS8b8IMrFloZy4iNFWZ9bd3XgEH3DeTAn4CKHXfNC+w0vvFG7dWRycAfgBOn7JpGrP4TgfXddHA9DTO33ZfqtK+vfCAe+A20/uTLyoAjcM+V2A9si9UtH7nlAIVvYke+HgXahQcPOo6TbgWpL5uA8xo2zt8MIEqX9XhQCC2rst7B4P7XTNOkoqLCd/WyjRs3snXr1iAGFjRJ3N/NLg8OSVavuXQ3T5bS5UHccubvAS8DP7AaF459D34qDx5crzyYiUistseDkydPobzc/6puN83NTTQ0NNxn26nr4/WVgXvw5CvrB3iwbmlsWD04LAfFXlUXuzulia/m0maI1aO+7AUuuGd+w5prlokngJ5KQRM0jVAWZx/5QeCu7mgCPpjzaT447ERf/elWknkrf41h9VYSCuO/HrsE9kdK2VV2JO0FZaRCEzBS7Uxv3MCMfZsQB+yo0nGnefQgE/s8IKS0Tbd8+a2LF1pjdmPmrK+t04CXgNNzaaeFNNC6UrwciZN0uje//cuOu+b9KA9DHTfUXh0pAmqAM+e+dRzhZGFgfe/59BaaixqfS+xPnRdEkFR/8mVR4MtANXAq/dOfN+GeJv8/sbrlLWmaK8YAsSPq7haalpMHh1g96ste4IKGjfPXiNJl/TyoaRpZnCMZEII5c+Zw2GGH+erFsixWrlyJNcQ5hF4IhyNMnlxGYWEBoVCIZDLFvn2NfPTRvoxtRnrDi0TauOXLb7UaF45dD37Kowe7gvyuPTDupIHLv+xYrzw4GJFYbY8H58yZSzgc3HT7nj17aGlpfi6VSpwXRJB08pX1WXmwbmlsWDw4LAESwD+8HttgC3FENs8VUhJxJDnMP3VKR37B+XDvr4Civt8o0ARhIYI6rCwtAjB1g79WXIEV8pcMN23LOg5+r67fY26gkj0OgpZoKU0Fk2kqKGNfQRltE2cTKpiCpg0MtaSdYOb2P3Ls1pcAd+oqMuJK6I8ppWPCctzZp7rFC0dn2fKa3xqfBG4FTkNQjkBD0orkzVcbFt796LZvL2WoDdsC9KiOHtURev/XQUqJtCR2h51yks68HT+ZN64OZgua2qsjEeARPWlUHfH2CWgymBQDx7DZfdpGOvWOx868veVyr/3Un3xZGLga+DbuJvLB2Ap8Lla3/H2v11OMLLEjX98gsvRgDsFRN51SOl/Yu/fDAR4UQkPk2YPgnrdy+ukVhEL+Ulq3bNnCe++9N/QThyASiRKNFhCNFlBQUMDEiRMpLCxIu6pmWTY7dmxn+/beVavRZUGQSIc+HrQaF45KDxplNb0ehHLcD7qtwJsFBRPunlg6eWgP4r6fdF0f8L6VUiKlxLbtlOM483asVx4cjEis1vWgrlcddtgRga0qO47D7t27icc7H2vZfqZnD558ZX3OHqxbGsu7B4ctQPpKXXnYRrxhCY7JeLqqOyCijsy5eoSU0pHNbZpsH3g2nA5ENIEuRNfhrsHf9vbNOprdn1zgqw/h2Mx75WFCif4b6kJkro9pCZ3mgkl8VFBGU9dXc3QSdk8gJJhQWI5pDJ32G96/i7P+ci9FjkUW6XPDi5SE6QkU38AVxPLFCy0vh3YESs1j5gxgEVJew2AffqTkpZ1f2Fmz8+uZqyUJMEtNNGPo3wBpyzga1wghHtn0naPG5TkEQVB7dcQAHoi2TfiHORuPQQRUmyZZ3MnuUzcSb0+ce/adbc/l0rb+5MtM4EvAvwK5VM9qAM6O1S1/K5frKUYH5UfUhQW8gRDHDOYhD8FRdzunra1Z6+xMvym7O1By/x78PX7WrFkcddQnffXhOA6vvPIKiUQi6zZCiJ5AqPcr2u+D4IQJhZjm0BMk+/fvZ+3avyClM9osiOyf6dHjQatx4Yh70CyrmQEsknCNcFOj0iKBwglFO0tKJg163zNNM6sP8lLKOHR5cI3yYCYisVoDeCASif7D7NlzAvv9TyaT7N69m0Qifm7bB2fn5MGTr6z35cG6pbG8enDYAiSA61eXaxb80hLiSluA7PMCaVJiSokh/c3aOK3tyJbBK3YI+l+j6+8dRbr2Wc3NRTBwY5LuP800j/V8z9H00LtnfukWxwyX+hg6Uz7YwJy3Vw543MQNkpJ6iKaCyW4wFC3jo8Iy9kcmIgdJnygsmELIzD61qKBpCxet/UXugx8OpCRKv9fuQ9xc+/sWL7QaM7TKCzWPmeXAZcDluEvB2eWZS7jnnbvkuy3zBz4/h+DoADYB/wU8vOk7RwVT1xqovTtikOKLOFyNZDaQAtrReRb4buXX48GUxhkGaq+OaMAdk/bEbpqx03+VyW7aZu6j4aht28/4QfMh2Ty//uTLdGAxcBvgdSBrgJNjdctH5eyxYnC6ynP/UghxJQes6nTPjA+x52hI2ttbaW/3lIXSoWn6Z4UHD2qaFjrjjDNvMU3Tlwc/+OAD3n777Yzf13W9XxAUjRYSiUQG/cDnptNlvze4qamJ9W+uzWncw4UceMBIjwetxoXD6kGzrMaTBwFKJ0+VkUg07fOzDY4OoNeDa4LzYFdg8UXcFY5eD+J6MF5fOWY8GInVasAdpaWTbpo2bUZg/ba1tbFnT8P25m1nHJLN80++sj4wD9YtjeXNg8MaIHVz/eryGyT8VHblFx4YsPjF6YgjP8q5vO9T91fLi71c74L4jYuB33pp25dPrXqEaLtbDTZuRGkpKKO5oIyWgjL2F0ymLVKSU3/hUBEF0ck5j+Pod5/i6F11Qz9xBAjLtKmXceA3wF2LF1qZzeqTmsfMMuASXBlU4LFMfnNiCj9Y9widdnG/x/UJOkaBrxSwrbiCWLrpO0d5nlGsvTdSQIp/I8E3cDJsfxM46PwBm+rKm+MDl21HIbVXRwSSb8/cNvc/Jn40JbB+G4/dzt7i3aFzftqeUcr1J1+m4Z7B8j3gyAAue2GsbvnTAfSjGCHKD199A/BT8nTcRjzewf79H+Xa7CnZVO3Ng1fEA/HgqlWraG93P3MahtEvRS4aLSAczq0IWjgcoqAg99T39za+y4cfjs6CdWmCJOjjQatxYd48aJbVBOJBTdOZUj4NTetvdF3X/VZb6/XgGu8ejMRqC3DPb/oGmbeBO7hFEKrj9ZVjwoORWK0Avj1jxsz/KCmZGFi/jY2N7Nu3N9S+65yMHjz5yvrAPVi3NJY3D45IgARw/eryi4FHyFMFa5lI4jS25DIT90/3V8u7c73OBfEbBW4ZUF+nw07YtwsadlNfOovOUGHXqpBESg3Qu/7MLYwsnjAdXc89F1zEm7n81SU5txsO9K5Uu0F4EbgLqF280PJd8aTmMXMi7obny4GzyW07WEbe2HMuv970/d4HNAhNDgW17L0D+H/AQ5u+c1TWeSq190YmAjeQ4hY6KR6yAYBgP5IvAU9W3hJ8RbcgWXXb5DDwdVLie9NWHR4OtQVRbRak5rDnE9tvPvGxLXcc+L36ky8TwAXAvwOfCuSCLs/G6pafF2B/ihGg/PDVefVgMpmgpaUxl1LZ/ySbqnP34BXxQDzY2LiP3bsbmDixlFCo937YPX4vn1eKiyd4qqgXj8epW/1qzu2GgwwBUl96PGg1LvTtQbOsJi8ejEYLmTiprN9jfV93n/R6cE32HozEal0Pwi2QpQfdKmtfAp7MR0W3IJk8Z5XrQfjetGnTwn73C3YjpWTPnj0373rnxAEePPnK+rx5sG5pLG8eHLEACeD61eUnAb8HgpvO7YNMWTiNzWBndX847P5qmfOmrwviN56NW2veF03741iDjFNKcJwQ2U7W6HqY4glD7XXLdC3JRX/6AYXJ0VdVVJMy20MU3gd+Bvxy8UKrNZdr1DxmFgEXAn8PnIOb4RgoUsKDf7udvzafAbhFGYyiwM8s2QUsAR7Y9J2jMs5u1d4biQE3AddjU4S3hIHngX+uvCW+0VPrPLPqtsnn4n5gmAtgtIaZ9se5aHYw56XZhrVPt4xDZ619sRl6AqOzcYWQj0P1NsXqls/NQ7+KYab88NV59aBlpWhubsRxsqqGfJhsqs7dg1fEg/Fg034sK/M4D6hgNiS6rlNcPGQtgIzXWv3an0gmR3x7zwCyCJC66fGg1bgwJw+aZTV59yDAxElTiEYLgEBWj9LR68E1mT0YidX2evCAIic58Dzwz/H6ylHpwclzVvX3oGEwbdq0wIo22La9T9f1Q9e+NKsZegKjvHqwbmksbx4c0QAJ4PrV5XNwlyj91QXNgLRtdyUpNejeva3AnPurc/9hXBC/8QXgLK/jA0hZNs2tQ09wuKnpBjKLSlyR8ESiEe/Lp8dueIKjPnzDc/t8kUOA1M1+4EHgvxcvtLZkelLNY2YBUIk7Q1ZJMIfZDUprYiL/te5R2u3SINLrBqMB9yTzezd956ie8Kf23shs4GbgKiCMxD1+z/upEincTcP/XnlLPCcZ54tVt02eDdwJDEgbKtg1kSl/OSTIyz0JLAyFShcA/4F7mnm+SAJRdT7S+KD88NV59aBt27S0NGJZg27N2ArMkU3VuXvwirh/D6YsmpuHvm1079PK5rNLJBImGvV+K3/33Q3U7/7Qc/t8kUOA1E2PB63GhRk9aJbVDLsHhaYxZer0nop1eQiQuun14JpeD0Zitf096J8eD8brK0eFByfPWZXZgwUFTJkS6NyM68GDQsPmwXydjzTiARLA9avLy4CngPn56F9KibOvBeIZZ4Luu79aXpdrvxfEbzwB+LOvwQEtbQmSqew+lWa7kjShYCqmWeB5TIdvfJp5H7zmuX2+8BAgdSNxf3F/Avxx8UJL1jxmRoBzcWVwIe4BfcPKug/O4Jfbb8coNtAjwaxmDEIjcMeNxVe9PMd8859xZwZ7L5oCgsmi3o2bnvDwSKXdrbptchS3zOytDCL50rdmULw1GDkIoWMYhZuE0PPyIfcAmoHJKkAaP5QfvjrvHmxp2UcyGc/0lPtkU3XuHrwiHowHW9pIJrPbW5/tStKECQWYpveD2ze9t5Fduz7w3D5feAiQepv28aDVuFCaZTUj7sFwpIBJk6dgGIbvA4azoBG4o6Hhw5eTicRADwZHjwdHKu1u8pxV2XmwtJTi4myzCQdHhARGqbFJmGLYPDiuAySA61eXR3E3GF6SlwtIibO/Hdnake67l95fLR/PtcsL4jf+L+5NxTOW7dC0P6Ow0iKl6AqSMufplhTNHLD5MRdO/OvDzNk7+o4WCEnp79BcCbpki2GzW8AxAhHMXcHTWCS0w6+2/ztvWpX5XEHqR4FopiLyMAsijxLV+qRRxnHnY4LjVeCfKm+Jvxlor4Ow6rbJAneW7E7gkCEb2ILYq4cSbvb+mUAIHV2PoGl5yUDJxDOxuuWVw3lBRf4pP3x1Xj0opaS9fT8dHWknti+VTdW5e/CKuH8PWjZNTbkVVsomSCopKfKVPvT2W3+lsXGv5/b5wkeA1JctuB/iR9SD3f+TiaVlFBUV53MFqR+2bdPWup/W1hZPe9ty4FXgn+L1lcPmwclzVuXmQSAWi/k6RFaYAr1YR4sO16HUADxTtzSWNw8O6/9kMO6Z39AJLMLNjwweIdBKJiAKBwTRNu7JzjlxQfzGOVLKar/D6oznXo1SCAmD3CA1YfgKjgCm7h+F1XvSV7DLCiHBtCFiQcgWn9AQp4xocNSHy2b8kIjdPGzX65ATeabzBr7XXMsfOq6j3en6MQQ/B3MK8JfaJZGf1y6JTAq89wNYddvkwyXyD8ATZCkFdMneT2/DDuV+fIYQGoZRiGkWD3dwBPDH4b6gIv80bJyfVw8KIZgwoYRIZMCEgDcPXhEPxoOduU0SwtDnOGma8L23orU152q4eSeg4AiB+IQYRR5saf4I2x6+Y4x0XadkYinTZ8ykuGRiYPtw0nAK8JdIrPbnkVht3j04ec6qw6XM0YPA3r17se3c8+uFITAmGZjl5nAHR5BnD46aAAngnvkN9j3zG76Ou1EuLyG9NrEI+p+H8Pr91TLnT6dSypu7zorwjO04xJPeNnwIkfnTrG74+7AmrDhFieH7wJ4tJh7KwXcFRmELDEeMrgNwu1xQaOznsvIf5HsWawBxWcRzndfw/eanqe24gTYnuJKffdBwN72+V7skcm3tkuDzCF/5z9KD//j9SS9J5AaBOCcQDWINAAAgAElEQVTX9nZBisbjt+f0wUPXCzCMEQmMwK3OlHOlMcXYoGHjfLth4/y8erCoaCKm2e+9+7psqh4ZD9oO8czp74MyWJCk6/5WIizLyumw2rGCYJR5sAspHZo+yqniYiBomk5JSSnTps+kpKQ0X4FSjwcjsdprI7HawD1YOvuVgyd94o8vSSk3COHBg7ZNY2MOP38BeqmOUW6gFYxIKJF3D46qAKmbe+Y3/ASoBoK/OwmBNrFfVZucK++c13FDOe6hYb7ojPuZLcn8JjZ0f/sMy5q3+2qfD3QvqXUSQvYoDIy66bN4eELJCg5y1o/IMBJyAis6v8z3E0/zlP01WmVeJrkmA/cCa2qXRP4uiA5X3l46b+UPSh8TltgqHHGGwHtt2PjUVlrmNgz5PCE0TLMYXQ8HdhK5B66N1S0ffSUmFYHSsHF+3jzoriT1mxDJ3YOLO4LxoIfVo2wwDH+fQVtaRt8koZ/Vo9EaGPWls7ODzs602yDyjqZpFJdMdAOliXkLlHo8GInVBuLB0tkr55XOXvmYEGKrEOIM4UNM8XiclpahD5gWhsCcaqIX6iPqwbqlsbx6cFQGSAD3zG/4HW5VnJxPuhsKYRr0+SyVsxhsW97jd9bMkZJ4Ij/LybrPAKm0ZRsJZGBL+b6QEkNKBt9xla6du3Kky1EqhJQckNJ2/bSrCdtD35zyRZICXnK+xPesWh62b6NFlg3dKHeOB16tXRL5Ve2SSCzXxitvLzVX3l56+crbS/+Ew1otIaqFDOYO3XJ4PZ1TBkupERhGEULkfRNxJjqAK2N1y58dqQEohpeGjfPz5kHDMPt+uPHgQdu/Bx1JPJ6fVRq/m/1bWloYPJl9+JA+fTxaA6N0/6OG+l1Y1vCl2h2IpmkUF09k+vSZlE4qQ8tP0YjjgVcjsdpfdZUXz4nS2SvN0tkrLy+dvfJPwFohtGo/gVFfWlpa6OwcpFqTBsZUA2GO2HuqA7iybmks7x4cNUUaMnH96vK5uOVPPxFkv05zK7KtswUou79aZv3beNLuL+uTSiKduqZ5L40DdMRTtHfmvv+oG8fJXO57YvEs/HiroKNxYcXqH3UacLEJVRpM0cAYtpuslAjc6N3EWxQvHIjYo1MK2DJjtbj91iR+tPsxOoypwzumtDjM1N7mK9o3KRH78nGBVtwTtX9aecvgm/FW3l5aDlwDXAdMR4KWEIiAA2AtoTPtlcMx4gNT5wyjcKRS6gDeBK6I1S0ffZVTFHmn/PDVefFga2sznZ1tLUCZbKrO3oPn7NYnTSrp1HWfHuyI097uvXSm4zgZU4ImTiz2Nbvd0dGx8PXXV3fibnavwj2nyhguqwS41yiQfoJmsP+dEDrTZ8wkqENM/SClJBGPs2/fnpzO4MqBHg/G6ysH9WDp7JX9PYib1RD0Ko6maUybNi1twQxj0oil1EGXB+uWxobFg6M+QAK4fnX5VOBp4MSg+nRa2pCtHY/fXy0vzaVdxUfXVk4oCD3t59pSSj5qieP4+NnbdvpS35pmUlI0w8foAJi0oujmpr4PPFhjhiRyMuDkeMPN+j8ZkvKTGlwj4BLh81A6syu1blQhpZtWN0S6ve0Inmq6mbr45Tj+Pn8EgkaSLxrfZp7IeQ93tryLe8jsigO/sfL20hOBG3GrZPW8J4QFWio/N+nQRwXEXj2sX/AlhIFpej070BfvAv8GLFclvT/elB++OnAPtrW10NHR+rhsqs7Ng1UfVU6YUODfgx+14Dh+PJh+D6+maZSU+P59nbRiWVE/D5plNSHppknlapes/5MS+UncD8GXEMDhrKMtQMrl1Z5YWkZJfgsoZI3jODQ27iERD+YsjDS8i3vI7AAPls5emdaD4L8QSSZCoRCxWKxf8CVCbmrdCNDjwXyV9E7HmAiQAK5fXV4IPIJbp983XQHStfdXy/tzaXf2/uvvCoeMf/Zz7c6ERVuH93rKUmpdZb4HEjInUFjgKzXq/RVFNw9H/fqMPPKEUQ5cC3wVKPfSRyQ1isQgpVuQIUlOdkg6YV5p+yKvdXyetvyku+WA5EvGzfkMkgAeB75RKKO7cfde3AiclO6JWjz41aO+FG0pY9LbB/VeT4tgGNG8XS8NW4DbgN/G6pZ7P7pXMa4oP3x1oB7sCpCulU3VuXmwev9d4XDInwc7E7S1ed9vMliZ71DIpLDQ+zmAwPsrlhWNqAeNsid8exBGjwe9ftIUQlBcPJHiktJhKwGeCSkljXsbiOcvSIIuD0ajhUN6MB+rR30pKipi0qTePclakYZRMqyvQY8H65bGht2DIx+WZ8k98xvagYXAPYF06M48DYjUh8JxZInfS3sp7d2Ne1Bs5jeorvuecFrjtwO/LF5oNSxeaH0fOBi4Elg7wkPKHSnjpGSSTvesIxLkbIiQluDs4l/wnfJzuKT4+5RqI1l6XfCw/X1SMn+zR0JyiSmN9yVyH+5ZMGmlMBwbA1pnN3YmSjre6v63pg2bFHbizh4fEatb/msVHCn60rBxfqAetD170PHvQR/FGYY6AymAw0ZH3INW48IGq3HhmPaghLiEpJ/btXvAcRM7d2ylcW8DVsr75ye/CCGYNDmYg8UHucolhmG+L+UQHhwGWltbOxOJRK8Hw8MWMvR4sG5p7NcjERzBGAqQwC0DDtyAlLf66shxkPHktvur5dZcm0rY5OfSiaSF7TGlwA2O0u7K6QRWAz8PmYV+S9C94bN9YCxeaCUWL7R+DXwaWAD8jmxO65EjNmvWCTwGXIoQk0hwEDYP++3UIMWpocf57sSF/H3h95is7fQ/Ug9YsoCHnX8NvF9NCsLSJEqEEKYhEBMGbZD/13c5giPCLQWnABvdh/L+fqrHnSk8LFa3/IFY3fKR+xSgGNU0bJxvAzdInx50HIdkKr5NNlXn7kHp04OJJLbtLVNmkOCo14Mhc9x40GpcmLAaF+buQUbegwImAQeBfw+CpL29jd27P+CjfXtHLFDSdZ3S0smB9+tWSA0TiUQxzZAhxBAeZOizwHyyHDgiHA73ejD/EUOPB+uWxh6oWxobUQ+OmRS7vly/YsIsDGM74RCeKvsmkth7m39+f7W8IdemZ++//tiQqa/3+sZs2h/H8iAGKUV3cNQErOv6Wtv153t/Puhu++zWH4ZxN/z5meY/ZUXRza/5aJ9XHnnCOAS4Abe8bPpZTOkeCDtMckjgbp5+FHi6alFqQNnJmoeMc3BLex7i5QKaLdDt3hlRW+qsTZ7L8x1fZq/jqUvPFIq9/KeR8xEL6ZEQwsTMtYC7A3oiL3fqd4EbF9y274XuB3Ycf9YngTWGUViQpwINjcD/A+6J1S0fmfq2ijHJhJkrZhmGsT1keis5n0wmaG7e+3PZVJ27B6v3HxsKmd492LQfy8p9UrhPcJTegy8cZJ9d3RqMB5cVjVoPGmVPHMJQHuxiJDyYaqwa4EGjrMaXB4XQBqwMFhRMoLik5MAzvfJOKpWifvcHgfVnmiEMI/e3q6blpcLeu8CN+zYv6PHg8WfucD04ySjIU4GGHg/WLY2NGg+OyQDpumei12gh4z6paRAJ5xYk2Ta0dWC3dl58f7V8ysv1P9f61caQqec8hZBM2bS0ZV/SVEpsEHul1F+QUn8cxDpg+58Pujvti3Z26w8/A7ye67j6YAPFK4puHjVv0Ew88oQxATft4GvA3AO/n+ciDRZuWdxHgSerFqWGrM1d85BRiFup5iZymYdxwLD0tJJzpMabyc/yfOfV1Ntzsu7SHw4/Mk5EF/7uG0IKIoTRvMhbdu1BCk78bbh5zj9bcNu+AZsDdxx/1hd0PfobXY8EdT2AFuCHwE9jdctbg+xY8fEgOv2ZawwjdJ+maYRDkZyCJNux6ehoo7Oj9WLZVO3Ng4taG0MhM3cPJlO0tGR/fImU0gb2SilfkFI+jhsMbf/zCwel92B1azAeXFY06j1olD0xqAchrwFSPw+mGquG9KBRVuPNg7gH/2Z6j0cLCikpnog5TFXvpJR8sHOb736EEITDEc9VhwPeg9TjwX2bFwzw4PFn7viCXqL/Ri8KNCjr8WDd0tio8+DI7njzzmkAwnGQnXE3SMqmkofjQDyBdMvmvOz14rYjbwD+N5c2UspsCjN8CKwC/gisEoJ3Xp/2i1yWmz6Ty5jS8PZYCI4AFi+02oCfP/KEcS9wDvB14HPd37dF4G9uB3gRVwZPVC1K5XQuSdVVVjvwLzUPGb8FHsA9B2FINEfLKDhNOBwffp7jQiv4a/JMnu+8mg/ttI4MEI09HLx2GtuyGn9aJIQJeQuOgJ4a8MHUsvkNcMuC2/btzvSEWWtffHjnCedcoGnhvw9ARm3AT4Afx+qWNw31ZIUiI9L1oOM4xBOdhEORrCpaOY5DIhHH8etB2/HmwaELMxzgQfHO689NG14PjoHgCMBqXNgG/NwoeyKtB/NAPw+mGqty8qDVWNUO/ItRVpObB7XBA4HOjnY6O9qJRgsoLplIKOTvLMihEEKg68Za27a8exAIhcK+jmQJkN8At+zbvCCjB9e+NOvhE87deYE2QQvUg3VLY6PWg2N1Bek5LWT03AQkgGlC/wNge5ESLAuSKQTgxJPb770gcYifMZzVcv2T0bBxUbbPb21PEk8OOGbifbok0PW15fVpD3p+Qc5u/eGvcGeTvPLAiqKbr/HRfkR55AnjKOCfcX8G0QBWkSTu6/Mo8LuqRak9/kcJNQ8ZBu6M3/eBQUst6SkdLctqbY4UvJM6jec7rmanfZT/gaZBItHMlsPu5My/A5bgobqSKQ1CvrJfAKfrHCTvs6PrcdPpVmXz5B3HnxU2jMJdmhbymnzeCfw3sCRWt7zRYx8KRQ/Rac88Z5ihfh+GTcM88ADYHqSUWLZFKuVO1CWT8e2J+gsO8TOGsy5teTIaDWfvwdZ24vEBE4UDPfjcNO8erG7178FlRWPWg0bZE/08CL5Xkfp5MNVYFYgHjbKa7D2o6zkFEpFoASXFEwmF8xMouWcjJQ7bu3e3Zw8ahhlIaqDPVaT1uOl0WXnw+DN3hI3Jxi4tqvn2YN3S2Kj34NhcQZKy3y+TAEilkJYFuuauJgkNpAOOBNtG9A0EJav9DqGtI1klBL8Km/oXB3tzOl0rR4mkLYG/0jsz9qfXpz2YMVr3iN+Zs1GzMdULixdafwOue+QJ4zvA1SmNG4SUB+m5l4NejSuDZVWLUh8GPc6qqywL+FHNQ8bjuNWo0m/qkZBLJpsmJMeEXuFo8xU2pE7huc5r2G4dE8SQ+wxJkqAgUnlLfGntksiTwL/iyji7e4kEgwCW6DWQOogctzFIZItAfBu4f8Ft+7I+GHPW2hcTu06sPE9K+1Uh9KyjOyllSghxL/CDWN3yoH/fFR9jJHLAh8qUlcKyLTRNR9M0NCFwpEQ6DrZj9z9UVUr/HmzrqBJC/CocNgf3oOOuHCUSyYEefG6a8mCAWI0L/wZcZ5Q98R3cPUo3SORBHoKkHg+mGqsC96DVWGUBPzLKagb3IJBrkZx4Zwfxzg4ikSjFJRMJhwNNj0ZKiaZpkXh95dJIrDZ3D+KmDAY0GnL9+UgpW4RwPbhv84KsPbj2pVmJE6t2nSdN+aowhCcP1i2NjRkPjtEVpMijWshc5LW93ZG45L6Lkk8EMZaKj679rGloPwmZ+if7CsJ2HCzL2dMRtx63bOdp4NXXpz3YHMQ103F26w+LgWb8lduat6Lo5jcDGtKI88gThikkiw2H/9IdZgwmCIncIhD3AI9VLUrtGK4x1jxkCODzuMvNAw47MpLp9x9lg5TwXuoknuu8hi3WPH8D7cLSLBzdOXH7Lcf9ufux2iWRo4CfAmcN1V6TgigByUqCSAk0e+ifj3RL3z0lpPjKgtv27fV6yV0nVn5S00JvCKEPeiiSe1+VvxNCuylWt3xkyg4qxjWRac88apohzx5MxDsuSe65KBgPVn30WdM0fhIKmf09aDtYlrWnoyP+uGXZrgefm5Y/D1a3BuPBZUXjxoNG2RMmsBj4L8jeg6nGqmHzoFFWM6gHB9t/lA3hSISS4lLCkWDcY1kWju2cuH19rwcjsdqsPSiERiQS3Ll6QoisVti6Pu8/JYT4yr7NCzx78MSqXZ/UotobwhRDe9Dmd8IQN9UtjY05D47NAOnp8JlaJPSil7bStpP2/s6C+6tloHXVP9f61VAiac03dG2SEKKxPZ5as7r8F9lXZPDJ2a0/PAPwc4pnJ1CyoujmcVleeNly4xJN8k/A0ZpkkoSEFHwEvCEk371kkfW3kRxfzUPGZOBHwJf6Pu4nQOpGSnjfOoHnO65hk3Wi936QpIwUCE7bfstx/Zbka5dEBO7J7z8GZmXqw5A6Yf+Hw/cdFMICYaVPt+sKjPYguPK0f/3ouSAuuevEynLQ7tY040Ih+h88JqVjS2m/A3xp+ponx82HLMXoIxx7+sxQKOLJg7ZtJzs79hfIpupgPbioNZRIJOcbhu56sD2+ZvUfyofPg9WtwXhwWdG49KBR9sQl4HoQtwR3AlwPAt/tWn0aMYyymrQe9BsgdRMORygumegrOJFSkkqmAE7bvr6/ByOx2qw8qOtGHvZJia5AKX16LbAHuPKjLacF4sETq3aVo3O3FtYuFIbo70Fb2jIp30HwpTWPTR+zHhyTAdI1y4TQi6KtwtALc23rJK2ae8/vXJiPcY0kZ7f+8FbcMoleeW1F0c2nBDUehTdqHjI+C9wHfAJAtzQ0J7hNnO+lTtz9QOuPC1KyMKeDHiUSW7dxNAfgc9tvOS7t4ZK1SyIFwK1dXwMMoEuNyMCH/SMBB0TvapIENqDJ753+nabHgr8gfPiZizQpnWpgOohSkJtA/mbGG7Vj76aqGHOI0mUiWlDUqutGzh60Usmazt3njz8PVrf69+CyIuXBEcYoq+nnwe6U0aAIhyO7J5dNLdB1PTcPSolt2d2l5j+3fX16D0ZitYN6UNP0wNP++tInSJLABin5XtPW0/Piwc9c9qEmbVmNYDpQimQTkt+8UTNjzHtwTO5Bur9ayutqIzeha/fnMqsgbcdCyuvyOLSRxPvSgMuInxyugKqrrBdqHjKOwc1p/hdbd/SAAqS/AT+Ya77xaLth/kw4qWt1R0eTWSzL9w+OoGvjbzoqb4l3AP9WuyTyK9xZtIsDGPvQCEAHqct9uNWR7qm4tSmvKSLT1zzl4OboKxTDjmyqlpFptTdpmp6TBx3HtiTKgxlQHhwFWI1VLxhlNT0edBxbDyhA+hvwg0Qi/qht2T9zbOdaXdfR9OzS0/oERzCIB+P1lR3Av0VitcPrwS6k7PVg09aKvHpwzfLp49aDo6K+oBfurYw/IBOpZdk+XzpSyqR14b2V8YZ8jmsE+VhvTB1PVF1ldVRdZf0f4AQEb/QJTLzwOlAFHFN5Xfw3ldfFU0BcahLLsEgZKRzhuKloaXCEg6VbHDCGIae+Km+Jb6m8JV4FnAe81/24TeZr+WQdcBUws+LWpm/lOzhSKEYD8d2VD6RSiew9KB1ppZIXxndXKg+mR3lwlGA1VnVYjVWuB+GNPoGJF3o8GK+v/E28vtL1oJRYlkUqmcKxHTJlVDm2g5WyOGAMQ3owXl+5JV5fOcCDzoEFU4Kjx4NNWyu+le/gaLwzZgMkgHsvSCxykqmfS2fwd5q07LhMWZfce2Hi2eEa23BydusPy4GZPrtRYhhlVF1lrQfm27pzsyOcnPYKSOQK4ExgfuV18Scrr4v3vbN39jxP9AZKKT2FrdlYmoWlWySNJJZhIbUBv15ZJ3BX3hJ/FjgGN9WgHQEWgW17sHBnrk4FTqi4temXFbc2dQ7RRqEYVyTqL1iUSiV/LqUzqAdt24pbqdQliYYLx6cHq1uVB8chVmPVemC+49g3O06OHpS9HozXVz4Zr69M78E+gVIqlcK2bCzLwkpZJJNJLMtKF9Bk7cF4fWV/DwK2nXXxuKHo58GmrRW/bNpaoTwYAGMyxa4v954fv+HaJ82fCdO4T+jieDRtghAC6TgOjmyWjvNbmbJvuu/iVGDvxtGGlJzkc/9iM+5ZFIpRRtVVlg3c8eQvjKeweVFIkbFca9fKzFqBuPaC6xJ/Tvskl/iAR4QbLNnZBS85JU9X3hJPAktql0QeBpaksD5v4Kv4xB7c/PT7Km5t2uW1E4VivBDfff4N5pQnf2YY5n1C04/XujzoOI4jHafZkc5vbTt1U2rPxePYg/Iknxv5lQdHKVZjlQ3cYZQ9+RTwohDioEyvdVcgs1YIcW2i4YLcPAhIJz8ejNdXJoElkVjtw8ASy0p93mfxiR4PNm2tUB7MA2M+QAK47+LUu8DpANcs1yJ6cTRyz+fa81ZKdLQhEV8Q/tKW3lhRdPOY31A3nrn4K9Z7wMyn7g99Vkh5h5DiCNzfX10KWhDyVQl3XHRN8uUsuvM7u+SpBFDlLfFdwBdql0TuTcjkQ2FCh+YYJK0BfgYsq7i1adgqYykUY4HU3ot7PKhNWh6JFhRH2j/43MfIg3zBZ52zN1YsK1IeHMVYjRe/B8wMTX3qs1KKO4To9SDIFil5FeQdyT0XjVoPxusrdwFfiMRq700mEw+FQuFDcwySejzYtLVCeTCPjIsAqS/3X+bEyTAzMI6p8Nk+q7SCedsfNCy7fZZANOt6Qcu6g78caIlYxdBcdE3yBeA4n934/f3wVX6n8pb4qtolkSNT0rrTQP+qRubdt9JdF3tGQ3y/4tam1/1cV6H4uOB8dJnyYO5k58EzthuWbc8S0Kzresu6lw9WHhxmknsuGvMejNdXrorEao+0rNSdum58VRukCkXXuXrPCKF9v2lrhfLgMDHuAqSPGxVNdxm6zmSf3WSs3HP05h+Zmhb5rkC/QghjtqEXCnB/YY/bdn8biNeE0J7H3Ry4bt3BX27yORZF/hmRmbO+VN4St4Abn7294P8a6D/W0C4FUaQhhETi4OyV8BLI73721laV9qJQKDJSsbDJ0HU9fx5csNnUNO27Aq4QQsw2dL3XgxXb2oDXhBC9Hnz5YOXB0c+IezBeX2kBNxZMf/b/6rrxY03TLhWCIiE0IaXEcZy9IF+Sku+27vys8uAwowKksc+nAN1nHwNmzo7e/KNy4Hpdi96saeGCA7/vLgnrE4DPdX0BMG/7g9twJbG26891wO51B39ZpS6MHkZ05qwv597a0YxbdecqgJW3l4YFInXWrft9lSxSKBQfK/LjwQWbuzyo3axpWgYPMtCDZ2zfRjoPvnyw8uDoYdR4sOPDc/t5sHT2yrAQIrV/x1nKgyOICpDGPqchwet+dylJvVB884fd/z56849Owj1pe5GuTwhpIue3yCFdX30PIdwzb/uDfUWxDtiy7uAvq1/+kWHEZ84yofYWKRQKD5yGlOBxw7uUMvXC8uJeDy7Y3MeDekjLvd9DSOfBM7YP9ODLBysPjgyj1oNqb9HoQAVIY5/TpNTAY+lkKbWtR2/+URhYBNxI10F7mhbBQ3CUianAucC5hhHGMMIIROqUPY83SeQG6dj/sTq26IWgLqYYklEzc6ZQKBQBcJqfc2WklFuPXrA5jQc1PARHmejjQQPDMBCC1CmVe5qkZIOUzn+s/kNMeXD4UB5UDIoKkMYwFU13CWCBIzU0aXuaPOuIiz0gdwJTeh/V0EQ4qGECEDILCIcnoGk9WRAmrjCmAqcvaHxyf8qKX1IXu/zFQC+sSIffmTMlBoVCMSqoWNjU5UGJJqWnsskdnfE9wAEeJMjgCIBQyCQcDtNnP35/D17YuD+Vsi6pezamPJh/lAcVgzKmD4pVcCQwGQSOzP2ldByNjk55KgOkYPqpzT+ASLiIaLSkb3A0AF03i0OhwhV/17D8psAurMiE35mzvKUWKBQKRY50eRCGODM+LY7j0NHRmcaDIlgPRsJEo1EGKVaGruvFoVBoxd+d36A8mH+UBxWDogKksc1p3X9xHB3Hyf5m7khBytKw02TmCeF3r2sv4XAR4fCErJ6rCU2YZvTHJ9c/elZgA1CkQ6UWKBSK8UIfDzo4TvZbehwpSVkWdhoRBhkchcNhwuHssjI0TQjTNH988rn1yoP5RXlQMSgqQBrbnNb7V4HtGNiOxlCTaI4jsG0DK8OZ6kEFSELohEOFObYRGHr44YqmZ4LNbVD0JXNqgY6beNv9lR41c6ZQKEYLp/X9h+042I7DUHuSHMfBtm2sDCIMKkASQhAOh3JuYxj6wxVVTcqD+WPUFmlQjA5UgDRG6dp/dFr/RwWOY2DbBs4BgZKUbmBkWQa2YwKClJVeIJJgKpFGwhM8ScYwQuWJRPtXAhmEIh39Z84EEAYKQUQFItL7RWHX9/q/jGrmTKFQjDhd+49OO/Dx7uDHOSBQ6jpbBsuysLtWmlKp9AFSUPW4I5GwRw8a5YlEQnkwf2RcQRJd6ZVi8DRL5cFxjgqQxi6HADPSfUOiYTsGlh0iZZmkLBPLDmE7JrLPS55KZVCADOJgcIFpep9gEUJUBjAIRXp6Z840IArCTC8CIQTCFFBA31NG1MyZQqEYDRxCRg+6q0mWbZOyLFKWhWXb7upSn+elUqn0PfuoitcX0zQ9t1UezCsDVpAyBUQZHlceHOeoAGnsMmDWLD2CdIckSSmxMsRBjsyQe5cDpuFt1qwbTdM/6XsQiky4M2cCNzjShn6dhBDufJl7x1AzZwqFYjSQpQfTI6XEyiBCLwUfDsQ0DZ8e1JQH80e/FaRsXqcDnqM8OM5RAdLYxZcYMqXXAUiZQvpcRfKzetRFbpuXFLngzpyFc8uzF0K46XZq5kyhUIwO/HkwQ3oduMGTn7OVwN/qURfKg/mjZwUpZw+6KA+Oc1SANEaRUvoUw+A3ftvxs39RYBj+zlGS0tnsqwPFYCTQQRi5z2wKXYBBaR7GpFAoFDnh34MZ0uu6sHOoiJcOw/B31KSUUnkwfyTAWzGOrjbKg+McFSCNQSqa7pomhDjUTx+ZKth1I8lRwb8AAButSURBVKWFZbd7mkEzzYjvCkBSyr/46kCRke23HCfR8b5EaKhZTYVCMbJULGwKwIODi9BNRbc9etD/eYLKg/lj+/rjJPjwoFrdG/eoAGkMYlmyyk97KeWgKXa9z0th223IHPckmaa/1FwpJQhxl69OFIOj+SjSpA1SAFyhUCiGAcuy/HtwkBS7vs+zPQRJftPr3OspD+YZPzmUyoPjHPUCj0Gk5O/9tB9q9ajftbCx7DZAR9NMhDAQ6BlnxrrOMfIzPKR03npt6qVbfXWiGBwtTeWObBE+2ioUCkUASCl9ejB7EUrA6jpMVtM0t6oZmdOzus4x8jM8pJRvvfbMVOXB/OLHZcqD4xwVII1BhOBYP+2zWT0aiI3j2BawHLjb0EsahRDHA/P6fE0yDP/pdUJoP/XVgWJoBBZ9C3crFArFGEII4c+DWawepcNxnD4e1DN40F/1OgAhhPJg/lEeVGREBUhjEUGBn+YeAqQG4F7g/rfnfPPDPo+/C/wWYN72BwUwMxIu+j14D+CklJYQ4nGv7RVZk6S7Jp1CoVCMOYQ/D+YeIPV6cNWc9B48Y7vrwUhYeXBsoDyoyIgKkMYgwkeKk3vuQ9YBUh3wM2D523O+mRzsiesO/rKsaHomARztdWwAQogVK0vP/8hPH4qsiANFHtsGdci8QqFQeEL4WKJxPZh1gNTrwVVzBvfgywfLiqqmYDxYU6o8mH+UBxUZUQHSGMRxaNc1Jnppa9tDHhCeAP4X+O+353zzzzl2fyn+C3/8r8/2iiwQQgxe31ahUChGMY7jtOu65tGDQxZd6PXgqjnKg+MU5UHFYKgAaQxi23KlaQhPFXziiYznOuwE7gF+8facb+71OLTLPbbrJgk86bMPRZ7xm1uvUCgUfrFte6VpGt48GE9k+lavB1fNUR5UZER5cPyjAqQxiBD8q5SyKtdfUEdKEokBs2YrcdMHnnp7zje97VoFKpqemQ4s8Nq+iz+sLD2/xWcfCoVCoRjnCCG8edCRJBIDAqSVdHtw1RzvHqxqCsaDNaXKgwrFCKMCpDHI6vKb3jpp951PRyPiglzadXY63UmzHcCvgbvfnvPNtwIaVjX+y14+GsRAFAqFQjG+Wf1M+Vsnnbv76Wg0kqMHO7vTzHs9uGqO8qBCoeiHCpDGKFJyUSolN5qmOCyb53fGHTrjcgtwN/DLt+d8syngIflNK+gEfh/EQBQKhUIx/pFSXpRKpTaappmdBzvjdHbGez24ao7yoEKhSIvfjYSKEWLN9JtkypJHdsad3w+22dRxJJ1xZ1N7h3MBcNjbc77546CDo4qmZw4G5vvspnZl6fltQYxHoVAoFOOfNc9Nl6mUdWRnZ3wIDzp0dsY3tbd3uB5cNefHQQdHFVVNwXiwplR5UKEYBagVpDHMmuk32cBF8+vvPEYil+iaOE7XmexIkA77HCnfTCTkd9fO+sZf8jyURQH0odIKFAqFQpETa56b7nrw/PpjpGSJrmvH6bo+2XEkUjr7HEe+mUgkvrv2xVnKgwqFImtUgDQOWB276S3gvBEcgt+0gnbgGT8dHLFxhWka0Ss1zbhCIqcKRLuUcpftpO5459DTXvU5PoVCoVCMYlY/E1MenL/RNA3jSk3TrpAwVUCXB5073vnTocqDCkUOqABJ4YuKpmcOBU7w2c1TK0vP7/DScO6GZ2Mhs+CuaKT0Mk3TD0wZPdGQ4arjtq3ZZVmJK94+dMFKn+NUKBQKhaIfFVVNwXiwptSbB0/aEAuZ5l3RSOQyTdPSeFBWHVexbZdlWVe8/adDV/ocp0LxsUDtQVL4ZUTSCuZuePbouRuefTAUKvwgHC5alCY4AtyzCnTdnGGa0ZeO2fzqF/wPVYH/Kk0KhUIxnhgZD5604ei5J214MBQKfRAOhxelCY6Abg/qM0zTfOmYBZuVB4NBeXCco1aQFH7xm1awH3g2myfO3fCsAM4GvgGcY5oFhEMTsrqIpunCNKO/Ofr9VfvePnRBVtcb5wx6jLxCoVAosmb4PHjShgM8aBIOhbK6iKZpwjTN3xx96vv73v7TocqDyoOKQVABksIzFU3PHAEc67ObmpWl52c81hxg7oZnw8DncYVwNIAQGuFQYU4XcmfRQg8B0z2OVaFQKBSKHiqqmoLxYE3p4B48aUMaD4qsg6NuulaTlAcViiFQKXYKP/idNYNB0grmbnh28twNz34H2AY8RJcUAEKhQoTI/e1rGKFpx255LYhxKxQKhUKRXw+etGHy3JM2ZPBgCCFyz/QyDGPasadtUR5UKAZBrSApPFHR9IzAvxiagBcOfHDuhmfnAl8H/gGIpmuoa6bniwpN/z+ocqoKhUKh8EFFVVP+PHjShiw86H2OW2ia8qBCMQgqQFJ45WjgSJ99PL6y9Pwk9OwvOg03feBChtgAqWne37q6Zh51ws514b/MnDdoSsN44ugnN0eAciAGxMxCsxANNE1D6AKhid4/NYF0JNKR2AmbZFsSaalUbYVCoTiAYDxYU+p60N1flIMHvQdIuqYddcJZO8N/eXHmx8eDpx7gQdMshC4PCjHgS0qJlBLbtkkmkwx2GLFi/KECJIUnpOTzHlb2D+TRuRueNYHLgG+SdZlU4SmtoKe1ECHgHOApz52MAo5+crMJTKHrZk+fG3+af5f0bRueGB607+5ASTM0zEKTVEeKRNPHxqMKhUIxJFLKz/txURePzj1pgwcPojwIHH2qDw+Gh/BgV6CkaRqmaZJKpUgklAc/LqgASZEzFU3PCAnX+tGClDTubhDzgAeBmTm2xnFsNE33MQI+zygXwzErthRisxD38MMyaUsbizAwFfdmP5lhKjVqFpgITRDfFx+OyykUCsWopqKqKQAPysbd9Q0ePQiO4/haRWIsePC0LYXIPh6U0oYR8qBpIoQgHlce/DigAiRFzqQscaFpyFI/fXR0UgLidq/tHWmj4StAuuiEnesm/GXmvDY/neSDY57dUobgaUxOEkbvfV/gLvmTAhkf/qV+I2IQnhgm0axm0BQKxcebVMq60DQNnx7sLAF8eFD6rbR10Qln7Zzwlxdnjj4PLthSBjyN4CShpfGgZERS3gzDIBwOq5WkjwGqip3CA/KLfnvojAvvVRYA2/J9c4oCF/ntJGiOeXbL5ZjsFiFxUrr0CSEEIiQQEwT+4kNvGAUGQlfn4ykUio85Av8e7Iz79KDldwij04MLtlyOYLfQBvFgVxr4SGAYhq/0RsXYQAVIipwRMM9Pe8cBv/f1lBXIEvfiIDoJimOe3XIsJr8VmhhyZVdoAlEghv03WAiBOcGX0xUKhWLM49+DDpZPEab8B0gw2jy4YMuxCH4rRBYeFCMTJAkhME3lwfGOCpAUOSMEk/20t2xBNOrvpialg20nffUBnHPCznWT/HYSBMes2KJj8IrQsj/cSQiB8Plz9IIeGoGlK4VCoRhFCCH8edCyiUbTVu/Omu4Kaz4554Szdo4OD562RUfwisjhkMORCpJ0XXlwvKMCJEXOSPfcBs+kLIGmCSIRf+MIYBXJBC7120lA3C50MTHXRkIXw76TcKTSGhQKhWK04N+DFpqmEfEpwgBWkUaXB4UHD45AuptKsRv/qABJkTPSEZu9tnUc9wvANAV+VqktKxHEJs0RTy849uWtk9D5qtf2whzeG7XQhDoMQqFQfKyRjuPDgw5OlwhN0/SVrmVZ1vjw4OlbJ4EPDw5zwCKE8uB4RwVIipyRcK/XtilL0Lci5xDHEAw+jqzS7DQ0rQBdL+r50rRw3zFUnLBz3XTvowiE7wkhvOdaDPNKv2M5+4b3igqFQjG68OXBVP9Vn6HO4xl0HFmm2Wm6hm7oPV8HlAevOOGsnWPbg8O8oOM4yoPjHRUgKXLmtann/c6y2ZZrO8eBZKr/XUwIQSjkfSxWxjQ7DcMoIRSajGEUouuRni/DKMY0J6PrheDeVi/3PgJ/HPvy1mOA60fq+l5wUs6bIz0GhUKhGEleq536O8uyt+XaznEckqlUv8dcD3oX4WDFHgzTIBQOYRgGuq73fBmmgRkyu/fSjKwHTx+DHnSUB8c7KkBSeMKyxOdzWdWXEhJJjXTTPH7S7FJp0uyE0DHNiWhaZuEIIdD1AgyjGBBXeB+Bd459easA7mJECnZ7QzpSIrhppMehUCgUI41lW5/PJb1NSkkikT7rwU+aXSpNmp0QAjNkDnqQrBAC3dAxDANgZDx4+hj0oPvDVh4c56gASeGJuth5q+MJ7Vu2M/RzpYR4QsOy06+Ba943/f8Z5GLg970PCQxjIkJkd6/VtDCGUXT8CTvXHep1ED64FDjDdy++ixhlT6oj9ZuNi494e/iuqFAoFKOTuj/EVsfjiW/ZztAilFISjyewMqTDDRbIDMGfcfcQ/b7vg4aZ/Vk9mq5hGP+/vfuPrau87zj+ec65TkwCFVPbpS1RJydUiSk4S8JglgrGQIsVbVrLpnXtNGmrWml/tFOnrfvVP1ot0kSn0W1UKpqqakXrGKrasY3CAqKKXJjAAauSk0aJCzE0btfLgAaIf9zz67s//ESJEzu+55znOrn2+yVFSex7vvdEiu9Hn/PraezZe8fJ7s3BVbwjKE3Tbx4fIwfXOgoSKsty96W5uehbSeq01EE0MynNpNn55cvRGSXurzRJ/ynpVkk3TfaPPOSce/DMN+N4k0o8IVTSQkmKot7Pl9qopoGDU5sk3RtilqWrkwzZfDZeJMXvr8qbAUAXyPL8S3Nzc99K0nTJhyWYmdIs0+zc/LLl6IwSDxpYnINj/eflYFz6oQVRHCmKotXNwaGAOVj/QRVtybJsvCjIwfVglR8QjLVkfOtdtnf68U+2Erenldi1cSydecCZScozJwt35+ScpH+W9A+T/SM/Ou97j0ialaJNUVTtHs8ouuK3Jf1BvV0s5XOS3lt3iBUmBVkr8KLvYelset/k7/Z/trPvBADdZfzJrbb3zulPtlrJnlYruTaO44WrIsznYJ4teQCxorM5ONa/TA5qUxRXO/YdxVF35uAqlCMzszRN75s8RA6uF261WjfWrr3Tj+81szHX7nVt5ykK08zMst/+maSvSPqnyf6RZZ8as/fkDx6M400f8w9eKG3hSUAzm5+7ZudspQElDByc+iVJxyTVXAlKKmaLoAXJzEymxAprFWnRtMK+42J377GP7ng13LsAwNqy987pmjlYaGb5IDybg2P9y+fgHScfjOP4Y3Gj2u08/ol4m5974prO5+BQwBxs51r/Evw9RomZtYqiaJrZd5xz9x57lhxcTziDhNrGt941vufkgc9LuqfK9ss8gOewFk69PzTZP9JqY8y/RVFv5bUcnHNyLrpT0n9VnVHC3ylAKFhW6uzR61oI2Z9Jap7z50V/d869euTD21fxriYA6H7jT24d33PHyRo5uOSH+dkcHOtvLwfjqF4OynVXDpY7yN9+Dj5NDq53FCQE4Zz72zy3T8Wx215mOzNTsvihPge0EAjfm+wfafuTr6fn7afK3nu0hI6vAzFwcGpY0m/VnWNmsnmblfRTLf+Bf+Zrrxz5je3thCsAoKKFHMw/FcdxhRxcFIRnc3Csv/0c3NBzKsCCqZ3PwaGAOViUyMGnyUG0j4KEIMa33mU3nDhwp3N2NIraX+yt1ZLMlEj6F0l/P9k/8sMq7+9c9DtVtlvMHq0/Y3kDB6caku4LNO7+I7++vfKq4wCAsMaf3Go33HriTufc0ajEDbGtVktmdjYHx/or5qALkIPqbA4OBc7Bp8lBdAYFCcEc3jby0vUvHri+0bDDcew2Xey1/szRTJrqXklfnewfaVZ938Hm9AbVXOTOLM8PvWfHyToz2vCHkq4PMOc159yqPm0IALCyw9/f9tL1t7x4faPROBzHcRs5mMykabqQg2P91XNwXzNADlp+6In3kIOAeMw3AjuyfeREnmtbmtqjRWFL3jmZ5zbXaumeJNE7J/tHvlCnHHkjkt5eZ4BZ/nzNfbiogYNT75C0P9C4v5oY7vt5oFkAgICOPLX9RJ7n29I0fbQoll4kKc/zuVardU+SJO+cHOv/Qp1y5AXIQetsDg4FzsFRchCdwxkkBHd420hT0q+9/4UDV0aRfdo5bZP0bknTRaH7j2wfmQj8lrVXAHeu8WchduQi9ku6OsCcH0j6eoA5AIAOOfz9bQs5+IEXroyi6NPOuXNysLj/yFPbL8McdOQg4PGYb3S1web01Vq4CXNj1Rlm9lPn3NZntmztyA/DwMGp3ZLGpSCLQt0yMdz3dIA5AIA1YHBfM1wOPralMzk4FDgHR8lBdBaX2KHb/aZqhIIkOee+3sFy5LRwQ2qIUHiQcgQAOE+YHOxcOQqbg5QjrAIKErpd7csKJH0zwIzlfFTSBwLMmZHU6csfAADdhxwEAqMgoWsNNqffK+m2mmMOPbNl62SA3bnAwMGpzVpYDC+Ev5kY7vtJoFkAgDVgcF8zTA4+tqUzOTgUOAdHyUGsDgoSutnHA8zo5FGzv5R0TYA5JyR9OcAcAMDaQg4CHUBBQlcabE47Sb9Xc0wu6aEAu3OBgYNT2yT9aaBxfzwx3DcfaBYAYA0Y3Ne8vHNwKHAOjpKDWD085hvd6pclXVdzxoFntmz9v3ZeeO1TP3RauAn2Kv/rbef9vuhrG7Xx7lhxrZtmvcclPRJgDgBgbQmTg49taS8HbyyZg70b745jchDdiYKEblX7plQz+9f3PX/0IzJ9SE43yNSwzGaUKZN0pS78wO9pZ25URIoV1909ScokfXZiuI9n8QMAzhcmB3/l6EckfUjSDZIaZjYj1czBOFIcB8zBUXIQq4t1kNB1BpvTDUknJb2r6gwzy15vnnbOuQs+wc1MNm+ypMLPhkm9ea+iMFevfnliuO9PQgwCAKwdg/uaYXLwtZ8vn4P+VxW9V/QqigLl4Cg5iNXHGSR0o9tVIxQkKZnPGs4tvSSDc07uCifbYCpmCqlEPjSsEaocvSLpr0MMAgCsOfVzsJVcPAedk5mpKIpScxuNRqhyRA7ikuEhDehGtS8raM1lK77GxU7RphI/Iib1FG1dfdCOv5gY7nsj1DAAwJpSPwdbyYqvcc6VLjs9GwLm4Cg5iEuDgoSuMtic3izp7jozirxQluZtvdY1nFxve4t/xxbLBVkoXM9JeiDEIADA2jK4rxkmB7OVDxRKZ88mtSOO47ZfuwJyEJcUBQnd5sOSNtcZ0JpvLxTOcBvaL0iB/NHEcF+5axoAAOtF/RxMVj57dK62C1IjYA6OkoO4dChI6DZ113xQUrYgOdfW3XrOghw1e2BiuO/ZEIMAAGtS/RxstUq9vt2CFOjs0QMTo+QgLi0KErrGYHP6XWb2wTozsjRXnpU/KOXiIB/6K3lLC6uOAwBwgcF9zfo5mGXK8wo5GKb8rIQcxGWBgoSuYWYfd87V+j9b9uxRKfWzY//EcN//BtgTAMAaFCQH23g4Q2X1V47ZPzFKDuLSoyChaxSF/Xmd7c2s9P1HZzde+SWZq16+TPa6pH+sPAAAsOYVRVE/B0vef1RGltfIQSMHcfmgIKEr3Hjy5ZviOPrFOjOyJJcV1Q5vtbNd7nJZxcNnucu/ODHc18HDegCAbnbjB39yUxzH9XIwzarnYBuLxuZZXnlx2TzPvzgxSg7i8kBBQlco8uJzdWdUPXtkuUntbOqkNEpLz89dfvjobe/7Svk9AwCsF0We18/BimePypSeNK2Qg3l++Oj/kIO4fFCQ0BVc5HbV2d7MlLQqFqSk/WDIXFbqUrtc+Zu5y3+1yn4BANaPMDnY+YKUpZmytEQO5vmbeU4O4vJCQUJXiCL3C3W2T+azSjePFklRqiDJSUmUKHXpRS+3M5lyl08Urth5bGjHbPk9AwCsJ1EU1cvBpPyZHUkqiqL0ZXNJkihN0otuZ2bKs3yiKIqdx54hB3F5aWN1F+DSs8KqfbJ7VZ5eVySFbK5Cq3JSGqfKLFOjaCiySJE/FmGyOXP2cu7y/ceGdjxYfjgAYD2qnYMl1z6SqpWjM9I0VZZlavQ0FEWRosjnoNmcmb2c5/n+Y8+Qg7g8UZDQFQqzI5LeXWnbolCa5G2/3jJTMV9IZzfJtbA2w5v+93b+/KY5eyuN04WvmU5HFr0xOdQ/U+XfAABY32rnYInL3sxMRbForaRqOWj2VpqkZ752OoqiNyYPkYO4/FGQ0B1M35BUaXG81tzKoWBmR5VrzFJ70hI7psUf9nMv3PL++qs7AABQmX1DVXOwjbNHZnZU0piZPWm2RA4+Tw5i/XBVT50Cq2nHxDF31dW9r/RsbLyjzHZFXujUa7NL3X+USxqV9LCk/zg+sHM6zJ4CABDejpuPuaveduUrPT095XKwKHTq1Bsr5+AYOQicQUFC19g9NXXzxisazzrn2t7m9Bvz595/1JL0hBbC4JHjAztfDb+XAAB0xu7bf3zzxo0byuXg6Zlzn163OAfHyEFgKRQkdJVdL774id4rer4WxdFFn8BoZpp5s6VkPjst6VFJ/y7pv48P7HxrVXYUAIAO2HXbS5/o7d34tShqIwdnZpW0ksU5OEYOAiuhIKHr7J6aui5uRN9t9ER9Sx1Fy5I8m59Nn0ha2Vclfe/4wM751d9LAAA6Y/ftP74ujqPvNhqNpXMwzbL5+fknkiRdyMExchAog4KErjXwoxd29GxofMbMdskpd3LNNMm/3ZpLHz4+sLPaqrAAAHSJgVtP7Ojp6fmMyXZJLndOzTTJvt1qtR4+PkYOAlVRkAAAAADAu+j1qwAAAACwnlCQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACAR0ECAAAAAI+CBAAAAAAeBQkAAAAAPAoSAAAAAHgUJAAAAADwKEgAAAAA4FGQAAAAAMCjIAEAAACA9/8EV9gtmi1osgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-01-02 19:22:03,628 Running model_4\n",
            "2023-01-02 19:22:20,603 model_4 took 15.1s (3 recycles) with pLDDT 96.8 and ptmscore 0.775\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 900x450 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2023-01-02 19:22:22,601 reranking models by plddt\n",
            "2023-01-02 19:22:23,975 Done\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KK7X9T44pWb7",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 497
        },
        "outputId": "40bf1afd-e15c-4fd7-e627-5eff53d38ff8"
      },
      "source": [
        "#@title Display 3D structure {run: \"auto\"}\n",
        "import py3Dmol\n",
        "import glob\n",
        "import matplotlib.pyplot as plt\n",
        "from colabfold.colabfold import plot_plddt_legend\n",
        "rank_num = 3 #@param [\"1\", \"2\", \"3\", \"4\", \"5\"] {type:\"raw\"}\n",
        "color = \"chain\" #@param [\"chain\", \"lDDT\", \"rainbow\"]\n",
        "show_sidechains = True #@param {type:\"boolean\"}\n",
        "show_mainchains = True #@param {type:\"boolean\"}\n",
        "\n",
        "jobname_prefix = \".custom\" if msa_mode == \"custom\" else \"\"\n",
        "\n",
        "pdb_filename = f\"{jobname}{jobname_prefix}_unrelaxed_rank_{rank_num}_model_*.pdb\"\n",
        "\n",
        "pdb_file = glob.glob(pdb_filename)\n",
        "\n",
        "def show_pdb(rank_num=1, show_sidechains=False, show_mainchains=False, color=\"lDDT\"):\n",
        "  model_name = f\"rank_{rank_num}\"\n",
        "  view = py3Dmol.view(js='https://3dmol.org/build/3Dmol.js',)\n",
        "  view.addModel(open(pdb_file[0],'r').read(),'pdb')\n",
        "\n",
        "  if color == \"lDDT\":\n",
        "    view.setStyle({'cartoon': {'colorscheme': {'prop':'b','gradient': 'roygb','min':50,'max':90}}})\n",
        "  elif color == \"rainbow\":\n",
        "    view.setStyle({'cartoon': {'color':'spectrum'}})\n",
        "  elif color == \"chain\":\n",
        "    chains = len(queries[0][1]) + 1 if is_complex else 1\n",
        "    for n,chain,color in zip(range(chains),list(\"ABCDEFGH\"),\n",
        "                     [\"lime\",\"cyan\",\"magenta\",\"yellow\",\"salmon\",\"white\",\"blue\",\"orange\"]):\n",
        "      view.setStyle({'chain':chain},{'cartoon': {'color':color}})\n",
        "  if show_sidechains:\n",
        "    BB = ['C','O','N']\n",
        "    view.addStyle({'and':[{'resn':[\"GLY\",\"PRO\"],'invert':True},{'atom':BB,'invert':True}]},\n",
        "                        {'stick':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})\n",
        "    view.addStyle({'and':[{'resn':\"GLY\"},{'atom':'CA'}]},\n",
        "                        {'sphere':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})\n",
        "    view.addStyle({'and':[{'resn':\"PRO\"},{'atom':['C','O'],'invert':True}]},\n",
        "                        {'stick':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})  \n",
        "  if show_mainchains:\n",
        "    BB = ['C','O','N','CA']\n",
        "    view.addStyle({'atom':BB},{'stick':{'colorscheme':f\"WhiteCarbon\",'radius':0.3}})\n",
        "\n",
        "  view.zoomTo()\n",
        "  return view\n",
        "\n",
        "\n",
        "show_pdb(rank_num,show_sidechains, show_mainchains, color).show()\n",
        "if color == \"lDDT\":\n",
        "  plot_plddt_legend().show() "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/3dmoljs_load.v0": "<div id=\"3dmolviewer_16559102159225733\"  style=\"position: relative; width: 640px; height: 480px\">\n        <p id=\"3dmolwarning_16559102159225733\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason).  You need to install the 3dmol extension: <br>\n        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n        </div>\n<script>\n\nvar loadScriptAsync = function(uri){\n  return new Promise((resolve, reject) => {\n    var tag = document.createElement('script');\n    tag.src = uri;\n    tag.async = true;\n    tag.onload = () => {\n      resolve();\n    };\n  var firstScriptTag = document.getElementsByTagName('script')[0];\n  firstScriptTag.parentNode.insertBefore(tag, firstScriptTag);\n});\n};\n\nif(typeof $3Dmolpromise === 'undefined') {\n$3Dmolpromise = null;\n  $3Dmolpromise = loadScriptAsync('https://3dmol.org/build/3Dmol.js');\n}\n\nvar viewer_16559102159225733 = null;\nvar warn = document.getElementById(\"3dmolwarning_16559102159225733\");\nif(warn) {\n    warn.parentNode.removeChild(warn);\n}\n$3Dmolpromise.then(function() {\nviewer_16559102159225733 = $3Dmol.createViewer($(\"#3dmolviewer_16559102159225733\"),{backgroundColor:\"white\"});\nviewer_16559102159225733.zoomTo();\n\tviewer_16559102159225733.addModel(\"MODEL     1                                                                     \\nATOM      1  N   PRO A   1     -11.442   2.489   7.618  1.00 96.71           N  \\nATOM      2  CA  PRO A   1     -10.198   3.236   7.418  1.00 96.71           C  \\nATOM      3  C   PRO A   1      -9.479   2.852   6.127  1.00 96.71           C  \\nATOM      4  CB  PRO A   1      -9.360   2.858   8.642  1.00 96.71           C  \\nATOM      5  O   PRO A   1      -9.478   1.679   5.742  1.00 96.71           O  \\nATOM      6  CG  PRO A   1     -10.349   2.348   9.640  1.00 96.71           C  \\nATOM      7  CD  PRO A   1     -11.459   1.657   8.900  1.00 96.71           C  \\nATOM      8  N   ILE A   2      -9.118   3.989   5.496  1.00 98.09           N  \\nATOM      9  CA  ILE A   2      -8.375   3.737   4.265  1.00 98.09           C  \\nATOM     10  C   ILE A   2      -6.935   4.222   4.424  1.00 98.09           C  \\nATOM     11  CB  ILE A   2      -9.041   4.424   3.052  1.00 98.09           C  \\nATOM     12  O   ILE A   2      -6.698   5.354   4.851  1.00 98.09           O  \\nATOM     13  CG1 ILE A   2     -10.471   3.905   2.864  1.00 98.09           C  \\nATOM     14  CG2 ILE A   2      -8.209   4.209   1.785  1.00 98.09           C  \\nATOM     15  CD1 ILE A   2     -11.288   4.695   1.851  1.00 98.09           C  \\nATOM     16  N   ALA A   3      -5.925   3.314   4.140  1.00 98.19           N  \\nATOM     17  CA  ALA A   3      -4.509   3.669   4.088  1.00 98.19           C  \\nATOM     18  C   ALA A   3      -3.992   3.650   2.653  1.00 98.19           C  \\nATOM     19  CB  ALA A   3      -3.690   2.719   4.959  1.00 98.19           C  \\nATOM     20  O   ALA A   3      -4.230   2.693   1.913  1.00 98.19           O  \\nATOM     21  N   GLN A   4      -3.443   4.817   2.318  1.00 98.38           N  \\nATOM     22  CA  GLN A   4      -2.747   4.895   1.038  1.00 98.38           C  \\nATOM     23  C   GLN A   4      -1.233   4.907   1.235  1.00 98.38           C  \\nATOM     24  CB  GLN A   4      -3.185   6.139   0.264  1.00 98.38           C  \\nATOM     25  O   GLN A   4      -0.701   5.762   1.946  1.00 98.38           O  \\nATOM     26  CG  GLN A   4      -4.646   6.115  -0.164  1.00 98.38           C  \\nATOM     27  CD  GLN A   4      -5.051   7.354  -0.940  1.00 98.38           C  \\nATOM     28  NE2 GLN A   4      -5.422   7.167  -2.203  1.00 98.38           N  \\nATOM     29  OE1 GLN A   4      -5.032   8.469  -0.410  1.00 98.38           O  \\nATOM     30  N   ILE A   5      -0.616   3.926   0.624  1.00 97.78           N  \\nATOM     31  CA  ILE A   5       0.827   3.771   0.766  1.00 97.78           C  \\nATOM     32  C   ILE A   5       1.495   3.874  -0.603  1.00 97.78           C  \\nATOM     33  CB  ILE A   5       1.188   2.428   1.439  1.00 97.78           C  \\nATOM     34  O   ILE A   5       1.083   3.205  -1.553  1.00 97.78           O  \\nATOM     35  CG1 ILE A   5       0.488   2.306   2.797  1.00 97.78           C  \\nATOM     36  CG2 ILE A   5       2.706   2.291   1.591  1.00 97.78           C  \\nATOM     37  CD1 ILE A   5       0.633   0.937   3.448  1.00 97.78           C  \\nATOM     38  N   HIS A   6       2.442   4.787  -0.634  1.00 96.66           N  \\nATOM     39  CA  HIS A   6       3.287   4.915  -1.816  1.00 96.66           C  \\nATOM     40  C   HIS A   6       4.661   4.296  -1.581  1.00 96.66           C  \\nATOM     41  CB  HIS A   6       3.435   6.385  -2.212  1.00 96.66           C  \\nATOM     42  O   HIS A   6       5.325   4.607  -0.590  1.00 96.66           O  \\nATOM     43  CG  HIS A   6       2.146   7.034  -2.603  1.00 96.66           C  \\nATOM     44  CD2 HIS A   6       1.676   7.423  -3.812  1.00 96.66           C  \\nATOM     45  ND1 HIS A   6       1.168   7.357  -1.687  1.00 96.66           N  \\nATOM     46  CE1 HIS A   6       0.149   7.916  -2.319  1.00 96.66           C  \\nATOM     47  NE2 HIS A   6       0.433   7.968  -3.609  1.00 96.66           N  \\nATOM     48  N   ILE A   7       5.006   3.373  -2.491  1.00 96.24           N  \\nATOM     49  CA  ILE A   7       6.313   2.732  -2.395  1.00 96.24           C  \\nATOM     50  C   ILE A   7       6.977   2.707  -3.770  1.00 96.24           C  \\nATOM     51  CB  ILE A   7       6.199   1.299  -1.829  1.00 96.24           C  \\nATOM     52  O   ILE A   7       6.306   2.858  -4.794  1.00 96.24           O  \\nATOM     53  CG1 ILE A   7       5.373   0.416  -2.772  1.00 96.24           C  \\nATOM     54  CG2 ILE A   7       5.590   1.319  -0.424  1.00 96.24           C  \\nATOM     55  CD1 ILE A   7       5.347  -1.055  -2.379  1.00 96.24           C  \\nATOM     56  N   LEU A   8       8.367   2.616  -3.738  1.00 95.09           N  \\nATOM     57  CA  LEU A   8       9.058   2.434  -5.010  1.00 95.09           C  \\nATOM     58  C   LEU A   8       8.745   1.066  -5.608  1.00 95.09           C  \\nATOM     59  CB  LEU A   8      10.570   2.589  -4.826  1.00 95.09           C  \\nATOM     60  O   LEU A   8       8.548   0.094  -4.875  1.00 95.09           O  \\nATOM     61  CG  LEU A   8      11.072   3.996  -4.497  1.00 95.09           C  \\nATOM     62  CD1 LEU A   8      12.549   3.956  -4.119  1.00 95.09           C  \\nATOM     63  CD2 LEU A   8      10.841   4.936  -5.675  1.00 95.09           C  \\nATOM     64  N   GLU A   9       8.751   0.959  -6.932  1.00 95.26           N  \\nATOM     65  CA  GLU A   9       8.532  -0.331  -7.580  1.00 95.26           C  \\nATOM     66  C   GLU A   9       9.681  -1.294  -7.294  1.00 95.26           C  \\nATOM     67  CB  GLU A   9       8.360  -0.151  -9.090  1.00 95.26           C  \\nATOM     68  O   GLU A   9      10.768  -0.871  -6.894  1.00 95.26           O  \\nATOM     69  CG  GLU A   9       9.620   0.321  -9.801  1.00 95.26           C  \\nATOM     70  CD  GLU A   9       9.419   0.545 -11.292  1.00 95.26           C  \\nATOM     71  OE1 GLU A   9      10.416   0.797 -12.007  1.00 95.26           O  \\nATOM     72  OE2 GLU A   9       8.257   0.470 -11.748  1.00 95.26           O  \\nATOM     73  N   GLY A  10       9.445  -2.625  -7.435  1.00 94.59           N  \\nATOM     74  CA  GLY A  10      10.532  -3.582  -7.299  1.00 94.59           C  \\nATOM     75  C   GLY A  10      10.347  -4.533  -6.131  1.00 94.59           C  \\nATOM     76  O   GLY A  10      11.139  -5.459  -5.946  1.00 94.59           O  \\nATOM     77  N   ARG A  11       9.232  -4.324  -5.403  1.00 96.53           N  \\nATOM     78  CA  ARG A  11       8.928  -5.250  -4.317  1.00 96.53           C  \\nATOM     79  C   ARG A  11       8.178  -6.473  -4.834  1.00 96.53           C  \\nATOM     80  CB  ARG A  11       8.108  -4.554  -3.229  1.00 96.53           C  \\nATOM     81  O   ARG A  11       7.398  -6.374  -5.783  1.00 96.53           O  \\nATOM     82  CG  ARG A  11       8.758  -3.295  -2.679  1.00 96.53           C  \\nATOM     83  CD  ARG A  11      10.122  -3.585  -2.067  1.00 96.53           C  \\nATOM     84  NE  ARG A  11      10.872  -2.358  -1.816  1.00 96.53           N  \\nATOM     85  NH1 ARG A  11      12.763  -3.431  -1.033  1.00 96.53           N  \\nATOM     86  NH2 ARG A  11      12.699  -1.142  -1.140  1.00 96.53           N  \\nATOM     87  CZ  ARG A  11      12.110  -2.313  -1.330  1.00 96.53           C  \\nATOM     88  N   SER A  12       8.433  -7.584  -4.170  1.00 98.02           N  \\nATOM     89  CA  SER A  12       7.746  -8.810  -4.564  1.00 98.02           C  \\nATOM     90  C   SER A  12       6.279  -8.780  -4.147  1.00 98.02           C  \\nATOM     91  CB  SER A  12       8.434 -10.031  -3.952  1.00 98.02           C  \\nATOM     92  O   SER A  12       5.902  -8.035  -3.240  1.00 98.02           O  \\nATOM     93  OG  SER A  12       8.221 -10.079  -2.552  1.00 98.02           O  \\nATOM     94  N   ASP A  13       5.466  -9.629  -4.780  1.00 97.67           N  \\nATOM     95  CA  ASP A  13       4.063  -9.749  -4.395  1.00 97.67           C  \\nATOM     96  C   ASP A  13       3.929 -10.148  -2.927  1.00 97.67           C  \\nATOM     97  CB  ASP A  13       3.347 -10.767  -5.284  1.00 97.67           C  \\nATOM     98  O   ASP A  13       3.021  -9.685  -2.233  1.00 97.67           O  \\nATOM     99  CG  ASP A  13       3.120 -10.262  -6.699  1.00 97.67           C  \\nATOM    100  OD1 ASP A  13       3.335  -9.059  -6.959  1.00 97.67           O  \\nATOM    101  OD2 ASP A  13       2.719 -11.074  -7.560  1.00 97.67           O  \\nATOM    102  N   GLU A  14       4.832 -10.987  -2.480  1.00 98.33           N  \\nATOM    103  CA  GLU A  14       4.816 -11.429  -1.089  1.00 98.33           C  \\nATOM    104  C   GLU A  14       5.038 -10.258  -0.135  1.00 98.33           C  \\nATOM    105  CB  GLU A  14       5.878 -12.506  -0.854  1.00 98.33           C  \\nATOM    106  O   GLU A  14       4.379 -10.162   0.902  1.00 98.33           O  \\nATOM    107  CG  GLU A  14       5.576 -13.828  -1.547  1.00 98.33           C  \\nATOM    108  CD  GLU A  14       5.893 -13.811  -3.034  1.00 98.33           C  \\nATOM    109  OE1 GLU A  14       5.379 -14.681  -3.773  1.00 98.33           O  \\nATOM    110  OE2 GLU A  14       6.663 -12.922  -3.462  1.00 98.33           O  \\nATOM    111  N   GLN A  15       5.952  -9.420  -0.471  1.00 98.29           N  \\nATOM    112  CA  GLN A  15       6.215  -8.248   0.358  1.00 98.29           C  \\nATOM    113  C   GLN A  15       5.003  -7.322   0.402  1.00 98.29           C  \\nATOM    114  CB  GLN A  15       7.438  -7.488  -0.159  1.00 98.29           C  \\nATOM    115  O   GLN A  15       4.653  -6.798   1.462  1.00 98.29           O  \\nATOM    116  CG  GLN A  15       8.760  -8.195   0.107  1.00 98.29           C  \\nATOM    117  CD  GLN A  15       9.946  -7.469  -0.499  1.00 98.29           C  \\nATOM    118  NE2 GLN A  15      10.870  -7.032   0.350  1.00 98.29           N  \\nATOM    119  OE1 GLN A  15      10.032  -7.303  -1.720  1.00 98.29           O  \\nATOM    120  N   LYS A  16       4.378  -7.065  -0.695  1.00 98.34           N  \\nATOM    121  CA  LYS A  16       3.195  -6.210  -0.753  1.00 98.34           C  \\nATOM    122  C   LYS A  16       2.047  -6.803   0.059  1.00 98.34           C  \\nATOM    123  CB  LYS A  16       2.757  -5.998  -2.203  1.00 98.34           C  \\nATOM    124  O   LYS A  16       1.332  -6.079   0.753  1.00 98.34           O  \\nATOM    125  CG  LYS A  16       3.724  -5.160  -3.026  1.00 98.34           C  \\nATOM    126  CD  LYS A  16       3.170  -4.869  -4.415  1.00 98.34           C  \\nATOM    127  CE  LYS A  16       3.289  -6.081  -5.329  1.00 98.34           C  \\nATOM    128  NZ  LYS A  16       2.824  -5.776  -6.715  1.00 98.34           N  \\nATOM    129  N   GLU A  17       1.953  -8.154  -0.014  1.00 98.40           N  \\nATOM    130  CA  GLU A  17       0.932  -8.822   0.787  1.00 98.40           C  \\nATOM    131  C   GLU A  17       1.189  -8.632   2.279  1.00 98.40           C  \\nATOM    132  CB  GLU A  17       0.872 -10.314   0.449  1.00 98.40           C  \\nATOM    133  O   GLU A  17       0.261  -8.370   3.046  1.00 98.40           O  \\nATOM    134  CG  GLU A  17       0.254 -10.612  -0.909  1.00 98.40           C  \\nATOM    135  CD  GLU A  17       0.230 -12.095  -1.244  1.00 98.40           C  \\nATOM    136  OE1 GLU A  17      -0.148 -12.454  -2.383  1.00 98.40           O  \\nATOM    137  OE2 GLU A  17       0.590 -12.904  -0.361  1.00 98.40           O  \\nATOM    138  N   THR A  18       2.457  -8.838   2.589  1.00 98.50           N  \\nATOM    139  CA  THR A  18       2.843  -8.663   3.984  1.00 98.50           C  \\nATOM    140  C   THR A  18       2.562  -7.236   4.448  1.00 98.50           C  \\nATOM    141  CB  THR A  18       4.332  -8.991   4.198  1.00 98.50           C  \\nATOM    142  O   THR A  18       2.048  -7.025   5.548  1.00 98.50           O  \\nATOM    143  CG2 THR A  18       4.749  -8.738   5.643  1.00 98.50           C  \\nATOM    144  OG1 THR A  18       4.562 -10.370   3.881  1.00 98.50           O  \\nATOM    145  N   LEU A  19       2.904  -6.242   3.632  1.00 98.43           N  \\nATOM    146  CA  LEU A  19       2.655  -4.839   3.942  1.00 98.43           C  \\nATOM    147  C   LEU A  19       1.169  -4.591   4.181  1.00 98.43           C  \\nATOM    148  CB  LEU A  19       3.158  -3.941   2.809  1.00 98.43           C  \\nATOM    149  O   LEU A  19       0.791  -3.968   5.175  1.00 98.43           O  \\nATOM    150  CG  LEU A  19       2.905  -2.441   2.969  1.00 98.43           C  \\nATOM    151  CD1 LEU A  19       3.573  -1.923   4.238  1.00 98.43           C  \\nATOM    152  CD2 LEU A  19       3.407  -1.681   1.746  1.00 98.43           C  \\nATOM    153  N   ILE A  20       0.301  -5.051   3.331  1.00 98.49           N  \\nATOM    154  CA  ILE A  20      -1.140  -4.854   3.440  1.00 98.49           C  \\nATOM    155  C   ILE A  20      -1.650  -5.476   4.738  1.00 98.49           C  \\nATOM    156  CB  ILE A  20      -1.886  -5.457   2.228  1.00 98.49           C  \\nATOM    157  O   ILE A  20      -2.431  -4.858   5.465  1.00 98.49           O  \\nATOM    158  CG1 ILE A  20      -1.619  -4.624   0.969  1.00 98.49           C  \\nATOM    159  CG2 ILE A  20      -3.388  -5.554   2.512  1.00 98.49           C  \\nATOM    160  CD1 ILE A  20      -2.067  -5.295  -0.323  1.00 98.49           C  \\nATOM    161  N   ARG A  21      -1.182  -6.671   5.042  1.00 98.61           N  \\nATOM    162  CA  ARG A  21      -1.609  -7.370   6.249  1.00 98.61           C  \\nATOM    163  C   ARG A  21      -1.211  -6.595   7.501  1.00 98.61           C  \\nATOM    164  CB  ARG A  21      -1.014  -8.779   6.294  1.00 98.61           C  \\nATOM    165  O   ARG A  21      -2.041  -6.360   8.382  1.00 98.61           O  \\nATOM    166  CG  ARG A  21      -1.414  -9.578   7.524  1.00 98.61           C  \\nATOM    167  CD  ARG A  21      -0.786 -10.965   7.525  1.00 98.61           C  \\nATOM    168  NE  ARG A  21       0.669 -10.898   7.415  1.00 98.61           N  \\nATOM    169  NH1 ARG A  21       1.055 -12.853   8.582  1.00 98.61           N  \\nATOM    170  NH2 ARG A  21       2.815 -11.637   7.761  1.00 98.61           N  \\nATOM    171  CZ  ARG A  21       1.510 -11.796   7.920  1.00 98.61           C  \\nATOM    172  N   GLU A  22      -0.016  -6.213   7.493  1.00 98.58           N  \\nATOM    173  CA  GLU A  22       0.499  -5.565   8.695  1.00 98.58           C  \\nATOM    174  C   GLU A  22      -0.140  -4.194   8.899  1.00 98.58           C  \\nATOM    175  CB  GLU A  22       2.022  -5.430   8.623  1.00 98.58           C  \\nATOM    176  O   GLU A  22      -0.474  -3.820  10.025  1.00 98.58           O  \\nATOM    177  CG  GLU A  22       2.761  -6.758   8.699  1.00 98.58           C  \\nATOM    178  CD  GLU A  22       2.582  -7.469  10.031  1.00 98.58           C  \\nATOM    179  OE1 GLU A  22       2.511  -8.719  10.047  1.00 98.58           O  \\nATOM    180  OE2 GLU A  22       2.511  -6.770  11.067  1.00 98.58           O  \\nATOM    181  N   VAL A  23      -0.287  -3.397   7.924  1.00 98.44           N  \\nATOM    182  CA  VAL A  23      -0.922  -2.086   8.006  1.00 98.44           C  \\nATOM    183  C   VAL A  23      -2.375  -2.241   8.447  1.00 98.44           C  \\nATOM    184  CB  VAL A  23      -0.851  -1.336   6.656  1.00 98.44           C  \\nATOM    185  O   VAL A  23      -2.849  -1.503   9.314  1.00 98.44           O  \\nATOM    186  CG1 VAL A  23      -1.741  -0.095   6.680  1.00 98.44           C  \\nATOM    187  CG2 VAL A  23       0.593  -0.956   6.333  1.00 98.44           C  \\nATOM    188  N   SER A  24      -3.073  -3.170   7.819  1.00 98.56           N  \\nATOM    189  CA  SER A  24      -4.466  -3.418   8.177  1.00 98.56           C  \\nATOM    190  C   SER A  24      -4.606  -3.741   9.661  1.00 98.56           C  \\nATOM    191  CB  SER A  24      -5.039  -4.563   7.341  1.00 98.56           C  \\nATOM    192  O   SER A  24      -5.475  -3.192  10.342  1.00 98.56           O  \\nATOM    193  OG  SER A  24      -5.045  -4.226   5.965  1.00 98.56           O  \\nATOM    194  N   GLU A  25      -3.716  -4.628  10.214  1.00 98.62           N  \\nATOM    195  CA  GLU A  25      -3.751  -5.012  11.622  1.00 98.62           C  \\nATOM    196  C   GLU A  25      -3.431  -3.825  12.525  1.00 98.62           C  \\nATOM    197  CB  GLU A  25      -2.772  -6.158  11.891  1.00 98.62           C  \\nATOM    198  O   GLU A  25      -4.053  -3.652  13.576  1.00 98.62           O  \\nATOM    199  CG  GLU A  25      -3.239  -7.504  11.356  1.00 98.62           C  \\nATOM    200  CD  GLU A  25      -2.211  -8.610  11.536  1.00 98.62           C  \\nATOM    201  OE1 GLU A  25      -2.523  -9.784  11.235  1.00 98.62           O  \\nATOM    202  OE2 GLU A  25      -1.084  -8.300  11.984  1.00 98.62           O  \\nATOM    203  N   ALA A  26      -2.456  -3.042  12.060  1.00 98.52           N  \\nATOM    204  CA  ALA A  26      -2.077  -1.868  12.841  1.00 98.52           C  \\nATOM    205  C   ALA A  26      -3.244  -0.891  12.963  1.00 98.52           C  \\nATOM    206  CB  ALA A  26      -0.872  -1.176  12.209  1.00 98.52           C  \\nATOM    207  O   ALA A  26      -3.518  -0.375  14.049  1.00 98.52           O  \\nATOM    208  N   ILE A  27      -3.878  -0.639  11.879  1.00 98.49           N  \\nATOM    209  CA  ILE A  27      -4.994   0.299  11.843  1.00 98.49           C  \\nATOM    210  C   ILE A  27      -6.156  -0.250  12.669  1.00 98.49           C  \\nATOM    211  CB  ILE A  27      -5.452   0.579  10.394  1.00 98.49           C  \\nATOM    212  O   ILE A  27      -6.763   0.478  13.458  1.00 98.49           O  \\nATOM    213  CG1 ILE A  27      -4.407   1.427   9.659  1.00 98.49           C  \\nATOM    214  CG2 ILE A  27      -6.821   1.265  10.383  1.00 98.49           C  \\nATOM    215  CD1 ILE A  27      -4.699   1.620   8.177  1.00 98.49           C  \\nATOM    216  N   SER A  28      -6.475  -1.527  12.433  1.00 98.55           N  \\nATOM    217  CA  SER A  28      -7.553  -2.146  13.197  1.00 98.55           C  \\nATOM    218  C   SER A  28      -7.298  -2.044  14.697  1.00 98.55           C  \\nATOM    219  CB  SER A  28      -7.718  -3.614  12.798  1.00 98.55           C  \\nATOM    220  O   SER A  28      -8.181  -1.638  15.455  1.00 98.55           O  \\nATOM    221  OG  SER A  28      -8.717  -4.239  13.585  1.00 98.55           O  \\nATOM    222  N   ARG A  29      -6.054  -2.409  15.154  1.00 98.40           N  \\nATOM    223  CA  ARG A  29      -5.687  -2.389  16.566  1.00 98.40           C  \\nATOM    224  C   ARG A  29      -5.695  -0.966  17.114  1.00 98.40           C  \\nATOM    225  CB  ARG A  29      -4.309  -3.021  16.773  1.00 98.40           C  \\nATOM    226  O   ARG A  29      -6.170  -0.726  18.226  1.00 98.40           O  \\nATOM    227  CG  ARG A  29      -4.321  -4.541  16.762  1.00 98.40           C  \\nATOM    228  CD  ARG A  29      -2.959  -5.119  17.122  1.00 98.40           C  \\nATOM    229  NE  ARG A  29      -1.879  -4.432  16.419  1.00 98.40           N  \\nATOM    230  NH1 ARG A  29      -0.178  -5.547  17.514  1.00 98.40           N  \\nATOM    231  NH2 ARG A  29       0.316  -3.970  15.926  1.00 98.40           N  \\nATOM    232  CZ  ARG A  29      -0.583  -4.651  16.621  1.00 98.40           C  \\nATOM    233  N   SER A  30      -5.247   0.039  16.433  1.00 98.44           N  \\nATOM    234  CA  SER A  30      -5.071   1.417  16.882  1.00 98.44           C  \\nATOM    235  C   SER A  30      -6.408   2.145  16.966  1.00 98.44           C  \\nATOM    236  CB  SER A  30      -4.128   2.170  15.943  1.00 98.44           C  \\nATOM    237  O   SER A  30      -6.625   2.954  17.871  1.00 98.44           O  \\nATOM    238  OG  SER A  30      -2.826   1.612  15.983  1.00 98.44           O  \\nATOM    239  N   LEU A  31      -7.273   1.785  16.044  1.00 98.16           N  \\nATOM    240  CA  LEU A  31      -8.500   2.567  15.937  1.00 98.16           C  \\nATOM    241  C   LEU A  31      -9.705   1.752  16.394  1.00 98.16           C  \\nATOM    242  CB  LEU A  31      -8.708   3.045  14.498  1.00 98.16           C  \\nATOM    243  O   LEU A  31     -10.838   2.239  16.360  1.00 98.16           O  \\nATOM    244  CG  LEU A  31      -7.616   3.945  13.918  1.00 98.16           C  \\nATOM    245  CD1 LEU A  31      -7.992   4.395  12.510  1.00 98.16           C  \\nATOM    246  CD2 LEU A  31      -7.377   5.149  14.823  1.00 98.16           C  \\nATOM    247  N   ASP A  32      -9.427   0.552  16.903  1.00 97.71           N  \\nATOM    248  CA  ASP A  32     -10.505  -0.336  17.329  1.00 97.71           C  \\nATOM    249  C   ASP A  32     -11.561  -0.482  16.236  1.00 97.71           C  \\nATOM    250  CB  ASP A  32     -11.149   0.181  18.617  1.00 97.71           C  \\nATOM    251  O   ASP A  32     -12.756  -0.333  16.496  1.00 97.71           O  \\nATOM    252  CG  ASP A  32     -11.984  -0.871  19.326  1.00 97.71           C  \\nATOM    253  OD1 ASP A  32     -11.695  -2.078  19.182  1.00 97.71           O  \\nATOM    254  OD2 ASP A  32     -12.943  -0.489  20.032  1.00 97.71           O  \\nATOM    255  N   ALA A  33     -11.215  -0.582  14.978  1.00 97.67           N  \\nATOM    256  CA  ALA A  33     -12.076  -0.838  13.826  1.00 97.67           C  \\nATOM    257  C   ALA A  33     -11.964  -2.290  13.369  1.00 97.67           C  \\nATOM    258  CB  ALA A  33     -11.726   0.106  12.679  1.00 97.67           C  \\nATOM    259  O   ALA A  33     -10.916  -2.919  13.533  1.00 97.67           O  \\nATOM    260  N   PRO A  34     -13.231  -2.868  12.934  1.00 98.24           N  \\nATOM    261  CA  PRO A  34     -13.135  -4.226  12.395  1.00 98.24           C  \\nATOM    262  C   PRO A  34     -12.138  -4.335  11.243  1.00 98.24           C  \\nATOM    263  CB  PRO A  34     -14.559  -4.515  11.913  1.00 98.24           C  \\nATOM    264  O   PRO A  34     -12.081  -3.450  10.385  1.00 98.24           O  \\nATOM    265  CG  PRO A  34     -15.414  -3.520  12.629  1.00 98.24           C  \\nATOM    266  CD  PRO A  34     -14.588  -2.299  12.914  1.00 98.24           C  \\nATOM    267  N   LEU A  35     -11.395  -5.427  11.278  1.00 97.96           N  \\nATOM    268  CA  LEU A  35     -10.378  -5.651  10.256  1.00 97.96           C  \\nATOM    269  C   LEU A  35     -10.992  -5.609   8.861  1.00 97.96           C  \\nATOM    270  CB  LEU A  35      -9.680  -6.995  10.480  1.00 97.96           C  \\nATOM    271  O   LEU A  35     -10.387  -5.076   7.928  1.00 97.96           O  \\nATOM    272  CG  LEU A  35      -8.469  -7.285   9.592  1.00 97.96           C  \\nATOM    273  CD1 LEU A  35      -7.387  -6.232   9.810  1.00 97.96           C  \\nATOM    274  CD2 LEU A  35      -7.925  -8.683   9.870  1.00 97.96           C  \\nATOM    275  N   THR A  36     -12.171  -6.012   8.733  1.00 98.01           N  \\nATOM    276  CA  THR A  36     -12.850  -6.126   7.447  1.00 98.01           C  \\nATOM    277  C   THR A  36     -13.187  -4.746   6.890  1.00 98.01           C  \\nATOM    278  CB  THR A  36     -14.137  -6.963   7.567  1.00 98.01           C  \\nATOM    279  O   THR A  36     -13.493  -4.608   5.704  1.00 98.01           O  \\nATOM    280  CG2 THR A  36     -13.819  -8.411   7.926  1.00 98.01           C  \\nATOM    281  OG1 THR A  36     -14.972  -6.401   8.587  1.00 98.01           O  \\nATOM    282  N   SER A  37     -13.147  -3.780   7.762  1.00 98.04           N  \\nATOM    283  CA  SER A  37     -13.490  -2.423   7.351  1.00 98.04           C  \\nATOM    284  C   SER A  37     -12.256  -1.659   6.883  1.00 98.04           C  \\nATOM    285  CB  SER A  37     -14.162  -1.669   8.499  1.00 98.04           C  \\nATOM    286  O   SER A  37     -12.370  -0.552   6.352  1.00 98.04           O  \\nATOM    287  OG  SER A  37     -13.230  -1.384   9.528  1.00 98.04           O  \\nATOM    288  N   VAL A  38     -10.999  -2.191   6.892  1.00 98.48           N  \\nATOM    289  CA  VAL A  38      -9.740  -1.540   6.541  1.00 98.48           C  \\nATOM    290  C   VAL A  38      -9.418  -1.797   5.071  1.00 98.48           C  \\nATOM    291  CB  VAL A  38      -8.579  -2.031   7.435  1.00 98.48           C  \\nATOM    292  O   VAL A  38      -9.496  -2.934   4.601  1.00 98.48           O  \\nATOM    293  CG1 VAL A  38      -7.258  -1.401   6.998  1.00 98.48           C  \\nATOM    294  CG2 VAL A  38      -8.866  -1.716   8.902  1.00 98.48           C  \\nATOM    295  N   ARG A  39      -9.147  -0.778   4.334  1.00 98.58           N  \\nATOM    296  CA  ARG A  39      -8.650  -0.847   2.964  1.00 98.58           C  \\nATOM    297  C   ARG A  39      -7.236  -0.284   2.866  1.00 98.58           C  \\nATOM    298  CB  ARG A  39      -9.582  -0.092   2.014  1.00 98.58           C  \\nATOM    299  O   ARG A  39      -6.940   0.767   3.439  1.00 98.58           O  \\nATOM    300  CG  ARG A  39     -10.918  -0.781   1.786  1.00 98.58           C  \\nATOM    301  CD  ARG A  39     -11.949  -0.373   2.829  1.00 98.58           C  \\nATOM    302  NE  ARG A  39     -13.267  -0.924   2.528  1.00 98.58           N  \\nATOM    303  NH1 ARG A  39     -13.869  -1.236   4.737  1.00 98.58           N  \\nATOM    304  NH2 ARG A  39     -15.320  -1.809   3.057  1.00 98.58           N  \\nATOM    305  CZ  ARG A  39     -14.149  -1.322   3.442  1.00 98.58           C  \\nATOM    306  N   VAL A  40      -6.342  -1.028   2.187  1.00 98.46           N  \\nATOM    307  CA  VAL A  40      -4.973  -0.601   1.918  1.00 98.46           C  \\nATOM    308  C   VAL A  40      -4.741  -0.529   0.411  1.00 98.46           C  \\nATOM    309  CB  VAL A  40      -3.944  -1.552   2.571  1.00 98.46           C  \\nATOM    310  O   VAL A  40      -4.968  -1.506  -0.307  1.00 98.46           O  \\nATOM    311  CG1 VAL A  40      -2.519  -1.106   2.251  1.00 98.46           C  \\nATOM    312  CG2 VAL A  40      -4.161  -1.615   4.082  1.00 98.46           C  \\nATOM    313  N   ILE A  41      -4.368   0.630  -0.026  1.00 98.49           N  \\nATOM    314  CA  ILE A  41      -4.064   0.853  -1.435  1.00 98.49           C  \\nATOM    315  C   ILE A  41      -2.574   1.144  -1.602  1.00 98.49           C  \\nATOM    316  CB  ILE A  41      -4.905   2.011  -2.018  1.00 98.49           C  \\nATOM    317  O   ILE A  41      -2.055   2.104  -1.028  1.00 98.49           O  \\nATOM    318  CG1 ILE A  41      -6.398   1.764  -1.771  1.00 98.49           C  \\nATOM    319  CG2 ILE A  41      -4.619   2.186  -3.513  1.00 98.49           C  \\nATOM    320  CD1 ILE A  41      -7.264   3.007  -1.925  1.00 98.49           C  \\nATOM    321  N   ILE A  42      -1.920   0.229  -2.362  1.00 98.21           N  \\nATOM    322  CA  ILE A  42      -0.506   0.434  -2.657  1.00 98.21           C  \\nATOM    323  C   ILE A  42      -0.352   1.041  -4.050  1.00 98.21           C  \\nATOM    324  CB  ILE A  42       0.289  -0.888  -2.558  1.00 98.21           C  \\nATOM    325  O   ILE A  42      -0.908   0.527  -5.023  1.00 98.21           O  \\nATOM    326  CG1 ILE A  42       0.231  -1.439  -1.129  1.00 98.21           C  \\nATOM    327  CG2 ILE A  42       1.738  -0.681  -3.007  1.00 98.21           C  \\nATOM    328  CD1 ILE A  42       0.871  -2.812  -0.969  1.00 98.21           C  \\nATOM    329  N   THR A  43       0.334   2.227  -4.044  1.00 97.66           N  \\nATOM    330  CA  THR A  43       0.757   2.844  -5.296  1.00 97.66           C  \\nATOM    331  C   THR A  43       2.271   2.746  -5.463  1.00 97.66           C  \\nATOM    332  CB  THR A  43       0.325   4.320  -5.366  1.00 97.66           C  \\nATOM    333  O   THR A  43       3.026   3.253  -4.631  1.00 97.66           O  \\nATOM    334  CG2 THR A  43       0.683   4.934  -6.716  1.00 97.66           C  \\nATOM    335  OG1 THR A  43      -1.093   4.406  -5.176  1.00 97.66           O  \\nATOM    336  N   GLU A  44       2.607   2.069  -6.548  1.00 96.48           N  \\nATOM    337  CA  GLU A  44       4.030   1.924  -6.843  1.00 96.48           C  \\nATOM    338  C   GLU A  44       4.519   3.040  -7.762  1.00 96.48           C  \\nATOM    339  CB  GLU A  44       4.312   0.559  -7.475  1.00 96.48           C  \\nATOM    340  O   GLU A  44       3.889   3.333  -8.780  1.00 96.48           O  \\nATOM    341  CG  GLU A  44       4.008  -0.618  -6.560  1.00 96.48           C  \\nATOM    342  CD  GLU A  44       4.286  -1.967  -7.204  1.00 96.48           C  \\nATOM    343  OE1 GLU A  44       5.426  -2.472  -7.085  1.00 96.48           O  \\nATOM    344  OE2 GLU A  44       3.358  -2.522  -7.833  1.00 96.48           O  \\nATOM    345  N   MET A  45       5.717   3.602  -7.315  1.00 94.79           N  \\nATOM    346  CA  MET A  45       6.325   4.673  -8.099  1.00 94.79           C  \\nATOM    347  C   MET A  45       7.580   4.181  -8.812  1.00 94.79           C  \\nATOM    348  CB  MET A  45       6.665   5.868  -7.206  1.00 94.79           C  \\nATOM    349  O   MET A  45       8.448   3.562  -8.193  1.00 94.79           O  \\nATOM    350  CG  MET A  45       5.462   6.458  -6.488  1.00 94.79           C  \\nATOM    351  SD  MET A  45       5.871   8.001  -5.583  1.00 94.79           S  \\nATOM    352  CE  MET A  45       7.683   7.915  -5.607  1.00 94.79           C  \\nATOM    353  N   ALA A  46       7.531   4.411 -10.106  1.00 93.83           N  \\nATOM    354  CA  ALA A  46       8.775   4.157 -10.828  1.00 93.83           C  \\nATOM    355  C   ALA A  46       9.909   5.026 -10.289  1.00 93.83           C  \\nATOM    356  CB  ALA A  46       8.584   4.404 -12.322  1.00 93.83           C  \\nATOM    357  O   ALA A  46       9.695   6.189  -9.939  1.00 93.83           O  \\nATOM    358  N   LYS A  47      11.130   4.449 -10.208  1.00 88.39           N  \\nATOM    359  CA  LYS A  47      12.282   5.155  -9.653  1.00 88.39           C  \\nATOM    360  C   LYS A  47      12.567   6.437 -10.430  1.00 88.39           C  \\nATOM    361  CB  LYS A  47      13.517   4.253  -9.658  1.00 88.39           C  \\nATOM    362  O   LYS A  47      13.068   7.412  -9.866  1.00 88.39           O  \\nATOM    363  CG  LYS A  47      13.450   3.105  -8.662  1.00 88.39           C  \\nATOM    364  CD  LYS A  47      14.744   2.302  -8.647  1.00 88.39           C  \\nATOM    365  CE  LYS A  47      14.679   1.153  -7.649  1.00 88.39           C  \\nATOM    366  NZ  LYS A  47      15.957   0.381  -7.608  1.00 88.39           N  \\nATOM    367  N   GLY A  48      12.176   6.523 -11.665  1.00 93.04           N  \\nATOM    368  CA  GLY A  48      12.368   7.700 -12.499  1.00 93.04           C  \\nATOM    369  C   GLY A  48      11.334   8.781 -12.251  1.00 93.04           C  \\nATOM    370  O   GLY A  48      11.498   9.918 -12.699  1.00 93.04           O  \\nATOM    371  N   HIS A  49      10.354   8.530 -11.529  1.00 92.01           N  \\nATOM    372  CA  HIS A  49       9.259   9.456 -11.264  1.00 92.01           C  \\nATOM    373  C   HIS A  49       9.249   9.894  -9.803  1.00 92.01           C  \\nATOM    374  CB  HIS A  49       7.917   8.818 -11.629  1.00 92.01           C  \\nATOM    375  O   HIS A  49       8.441  10.739  -9.409  1.00 92.01           O  \\nATOM    376  CG  HIS A  49       7.797   8.461 -13.077  1.00 92.01           C  \\nATOM    377  CD2 HIS A  49       8.654   8.636 -14.110  1.00 92.01           C  \\nATOM    378  ND1 HIS A  49       6.680   7.847 -13.601  1.00 92.01           N  \\nATOM    379  CE1 HIS A  49       6.858   7.658 -14.898  1.00 92.01           C  \\nATOM    380  NE2 HIS A  49       8.047   8.128 -15.232  1.00 92.01           N  \\nATOM    381  N   PHE A  50      10.200   9.314  -9.048  1.00 93.15           N  \\nATOM    382  CA  PHE A  50      10.239   9.615  -7.622  1.00 93.15           C  \\nATOM    383  C   PHE A  50      11.481  10.425  -7.274  1.00 93.15           C  \\nATOM    384  CB  PHE A  50      10.205   8.324  -6.798  1.00 93.15           C  \\nATOM    385  O   PHE A  50      12.606   9.978  -7.508  1.00 93.15           O  \\nATOM    386  CG  PHE A  50       9.812   8.532  -5.360  1.00 93.15           C  \\nATOM    387  CD1 PHE A  50      10.779   8.601  -4.364  1.00 93.15           C  \\nATOM    388  CD2 PHE A  50       8.476   8.658  -5.005  1.00 93.15           C  \\nATOM    389  CE1 PHE A  50      10.418   8.793  -3.032  1.00 93.15           C  \\nATOM    390  CE2 PHE A  50       8.107   8.850  -3.676  1.00 93.15           C  \\nATOM    391  CZ  PHE A  50       9.080   8.917  -2.692  1.00 93.15           C  \\nATOM    392  N   GLY A  51      11.284  11.723  -6.759  1.00 92.18           N  \\nATOM    393  CA  GLY A  51      12.375  12.612  -6.394  1.00 92.18           C  \\nATOM    394  C   GLY A  51      12.572  12.730  -4.894  1.00 92.18           C  \\nATOM    395  O   GLY A  51      11.601  12.747  -4.135  1.00 92.18           O  \\nATOM    396  N   ILE A  52      13.811  12.642  -4.482  1.00 92.04           N  \\nATOM    397  CA  ILE A  52      14.175  12.878  -3.089  1.00 92.04           C  \\nATOM    398  C   ILE A  52      15.210  13.998  -3.009  1.00 92.04           C  \\nATOM    399  CB  ILE A  52      14.721  11.595  -2.423  1.00 92.04           C  \\nATOM    400  O   ILE A  52      16.318  13.867  -3.535  1.00 92.04           O  \\nATOM    401  CG1 ILE A  52      13.720  10.445  -2.578  1.00 92.04           C  \\nATOM    402  CG2 ILE A  52      15.040  11.848  -0.946  1.00 92.04           C  \\nATOM    403  CD1 ILE A  52      14.297   9.074  -2.253  1.00 92.04           C  \\nATOM    404  N   GLY A  53      14.812  15.164  -2.359  1.00 90.76           N  \\nATOM    405  CA  GLY A  53      15.751  16.265  -2.208  1.00 90.76           C  \\nATOM    406  C   GLY A  53      16.263  16.798  -3.533  1.00 90.76           C  \\nATOM    407  O   GLY A  53      17.432  17.171  -3.648  1.00 90.76           O  \\nATOM    408  N   GLY A  54      15.464  16.765  -4.611  1.00 92.33           N  \\nATOM    409  CA  GLY A  54      15.784  17.346  -5.905  1.00 92.33           C  \\nATOM    410  C   GLY A  54      16.478  16.375  -6.840  1.00 92.33           C  \\nATOM    411  O   GLY A  54      16.912  16.756  -7.929  1.00 92.33           O  \\nATOM    412  N   GLU A  55      16.677  15.104  -6.412  1.00 92.75           N  \\nATOM    413  CA  GLU A  55      17.312  14.073  -7.227  1.00 92.75           C  \\nATOM    414  C   GLU A  55      16.390  12.872  -7.416  1.00 92.75           C  \\nATOM    415  CB  GLU A  55      18.634  13.626  -6.596  1.00 92.75           C  \\nATOM    416  O   GLU A  55      15.656  12.496  -6.500  1.00 92.75           O  \\nATOM    417  CG  GLU A  55      19.679  14.729  -6.513  1.00 92.75           C  \\nATOM    418  CD  GLU A  55      21.022  14.245  -5.990  1.00 92.75           C  \\nATOM    419  OE1 GLU A  55      21.973  15.056  -5.917  1.00 92.75           O  \\nATOM    420  OE2 GLU A  55      21.124  13.045  -5.650  1.00 92.75           O  \\nATOM    421  N   LEU A  56      16.502  12.358  -8.671  1.00 90.94           N  \\nATOM    422  CA  LEU A  56      15.716  11.155  -8.929  1.00 90.94           C  \\nATOM    423  C   LEU A  56      16.149  10.016  -8.012  1.00 90.94           C  \\nATOM    424  CB  LEU A  56      15.855  10.728 -10.393  1.00 90.94           C  \\nATOM    425  O   LEU A  56      17.344   9.822  -7.777  1.00 90.94           O  \\nATOM    426  CG  LEU A  56      15.129  11.594 -11.424  1.00 90.94           C  \\nATOM    427  CD1 LEU A  56      15.515  11.171 -12.837  1.00 90.94           C  \\nATOM    428  CD2 LEU A  56      13.620  11.507 -11.227  1.00 90.94           C  \\nATOM    429  N   ALA A  57      15.110   9.344  -7.521  1.00 89.07           N  \\nATOM    430  CA  ALA A  57      15.412   8.192  -6.675  1.00 89.07           C  \\nATOM    431  C   ALA A  57      16.193   7.133  -7.447  1.00 89.07           C  \\nATOM    432  CB  ALA A  57      14.124   7.594  -6.112  1.00 89.07           C  \\nATOM    433  O   ALA A  57      16.916   6.329  -6.853  1.00 89.07           O  \\nATOM    434  N   SER A  58      16.133   7.139  -8.641  1.00 87.98           N  \\nATOM    435  CA  SER A  58      16.824   6.198  -9.516  1.00 87.98           C  \\nATOM    436  C   SER A  58      18.317   6.502  -9.587  1.00 87.98           C  \\nATOM    437  CB  SER A  58      16.221   6.231 -10.921  1.00 87.98           C  \\nATOM    438  O   SER A  58      19.113   5.643  -9.972  1.00 87.98           O  \\nATOM    439  OG  SER A  58      16.306   7.533 -11.474  1.00 87.98           O  \\nATOM    440  N   LYS A  59      18.687   7.833  -9.290  1.00 81.15           N  \\nATOM    441  CA  LYS A  59      20.089   8.237  -9.363  1.00 81.15           C  \\nATOM    442  C   LYS A  59      20.838   7.855  -8.090  1.00 81.15           C  \\nATOM    443  CB  LYS A  59      20.201   9.743  -9.605  1.00 81.15           C  \\nATOM    444  O   LYS A  59      21.997   7.438  -8.147  1.00 81.15           O  \\nATOM    445  CG  LYS A  59      19.928  10.161 -11.042  1.00 81.15           C  \\nATOM    446  CD  LYS A  59      20.300  11.619 -11.281  1.00 81.15           C  \\nATOM    447  CE  LYS A  59      19.997  12.048 -12.710  1.00 81.15           C  \\nATOM    448  NZ  LYS A  59      20.393  13.466 -12.958  1.00 81.15           N  \\nTER     449      LYS A  59                                                      \\nENDMDL                                                                          \\nEND                                                                             \\n\",\"pdb\");\n\tviewer_16559102159225733.setStyle({\"chain\": \"A\"},{\"cartoon\": {\"color\": \"lime\"}});\n\tviewer_16559102159225733.addStyle({\"and\": [{\"resn\": [\"GLY\", \"PRO\"], \"invert\": 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            "text/html": [
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              "        <p id=\"3dmolwarning_16559102159225733\" style=\"background-color:#ffcccc;color:black\">You appear to be running in JupyterLab (or JavaScript failed to load for some other reason).  You need to install the 3dmol extension: <br>\n",
              "        <tt>jupyter labextension install jupyterlab_3dmol</tt></p>\n",
              "        </div>\n",
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              "  $3Dmolpromise = loadScriptAsync('https://3dmol.org/build/3Dmol.js');\n",
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              "\n",
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              "var warn = document.getElementById(\"3dmolwarning_16559102159225733\");\n",
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              "    warn.parentNode.removeChild(warn);\n",
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              "$3Dmolpromise.then(function() {\n",
              "viewer_16559102159225733 = $3Dmol.createViewer($(\"#3dmolviewer_16559102159225733\"),{backgroundColor:\"white\"});\n",
              "viewer_16559102159225733.zoomTo();\n",
              "\tviewer_16559102159225733.addModel(\"MODEL     1                                                                     \\nATOM      1  N   PRO A   1     -11.442   2.489   7.618  1.00 96.71           N  \\nATOM      2  CA  PRO A   1     -10.198   3.236   7.418  1.00 96.71           C  \\nATOM      3  C   PRO A   1      -9.479   2.852   6.127  1.00 96.71           C  \\nATOM      4  CB  PRO A   1      -9.360   2.858   8.642  1.00 96.71           C  \\nATOM      5  O   PRO A   1      -9.478   1.679   5.742  1.00 96.71           O  \\nATOM      6  CG  PRO A   1     -10.349   2.348   9.640  1.00 96.71           C  \\nATOM      7  CD  PRO A   1     -11.459   1.657   8.900  1.00 96.71           C  \\nATOM      8  N   ILE A   2      -9.118   3.989   5.496  1.00 98.09           N  \\nATOM      9  CA  ILE A   2      -8.375   3.737   4.265  1.00 98.09           C  \\nATOM     10  C   ILE A   2      -6.935   4.222   4.424  1.00 98.09           C  \\nATOM     11  CB  ILE A   2      -9.041   4.424   3.052  1.00 98.09           C  \\nATOM     12  O   ILE A   2      -6.698   5.354   4.851  1.00 98.09           O  \\nATOM     13  CG1 ILE A   2     -10.471   3.905   2.864  1.00 98.09           C  \\nATOM     14  CG2 ILE A   2      -8.209   4.209   1.785  1.00 98.09           C  \\nATOM     15  CD1 ILE A   2     -11.288   4.695   1.851  1.00 98.09           C  \\nATOM     16  N   ALA A   3      -5.925   3.314   4.140  1.00 98.19           N  \\nATOM     17  CA  ALA A   3      -4.509   3.669   4.088  1.00 98.19           C  \\nATOM     18  C   ALA A   3      -3.992   3.650   2.653  1.00 98.19           C  \\nATOM     19  CB  ALA A   3      -3.690   2.719   4.959  1.00 98.19           C  \\nATOM     20  O   ALA A   3      -4.230   2.693   1.913  1.00 98.19           O  \\nATOM     21  N   GLN A   4      -3.443   4.817   2.318  1.00 98.38           N  \\nATOM     22  CA  GLN A   4      -2.747   4.895   1.038  1.00 98.38           C  \\nATOM     23  C   GLN A   4      -1.233   4.907   1.235  1.00 98.38           C  \\nATOM     24  CB  GLN A   4      -3.185   6.139   0.264  1.00 98.38           C  \\nATOM     25  O   GLN A   4      -0.701   5.762   1.946  1.00 98.38           O  \\nATOM     26  CG  GLN A   4      -4.646   6.115  -0.164  1.00 98.38           C  \\nATOM     27  CD  GLN A   4      -5.051   7.354  -0.940  1.00 98.38           C  \\nATOM     28  NE2 GLN A   4      -5.422   7.167  -2.203  1.00 98.38           N  \\nATOM     29  OE1 GLN A   4      -5.032   8.469  -0.410  1.00 98.38           O  \\nATOM     30  N   ILE A   5      -0.616   3.926   0.624  1.00 97.78           N  \\nATOM     31  CA  ILE A   5       0.827   3.771   0.766  1.00 97.78           C  \\nATOM     32  C   ILE A   5       1.495   3.874  -0.603  1.00 97.78           C  \\nATOM     33  CB  ILE A   5       1.188   2.428   1.439  1.00 97.78           C  \\nATOM     34  O   ILE A   5       1.083   3.205  -1.553  1.00 97.78           O  \\nATOM     35  CG1 ILE A   5       0.488   2.306   2.797  1.00 97.78           C  \\nATOM     36  CG2 ILE A   5       2.706   2.291   1.591  1.00 97.78           C  \\nATOM     37  CD1 ILE A   5       0.633   0.937   3.448  1.00 97.78           C  \\nATOM     38  N   HIS A   6       2.442   4.787  -0.634  1.00 96.66           N  \\nATOM     39  CA  HIS A   6       3.287   4.915  -1.816  1.00 96.66           C  \\nATOM     40  C   HIS A   6       4.661   4.296  -1.581  1.00 96.66           C  \\nATOM     41  CB  HIS A   6       3.435   6.385  -2.212  1.00 96.66           C  \\nATOM     42  O   HIS A   6       5.325   4.607  -0.590  1.00 96.66           O  \\nATOM     43  CG  HIS A   6       2.146   7.034  -2.603  1.00 96.66           C  \\nATOM     44  CD2 HIS A   6       1.676   7.423  -3.812  1.00 96.66           C  \\nATOM     45  ND1 HIS A   6       1.168   7.357  -1.687  1.00 96.66           N  \\nATOM     46  CE1 HIS A   6       0.149   7.916  -2.319  1.00 96.66           C  \\nATOM     47  NE2 HIS A   6       0.433   7.968  -3.609  1.00 96.66           N  \\nATOM     48  N   ILE A   7       5.006   3.373  -2.491  1.00 96.24           N  \\nATOM     49  CA  ILE A   7       6.313   2.732  -2.395  1.00 96.24           C  \\nATOM     50  C   ILE A   7       6.977   2.707  -3.770  1.00 96.24           C  \\nATOM     51  CB  ILE A   7       6.199   1.299  -1.829  1.00 96.24           C  \\nATOM     52  O   ILE A   7       6.306   2.858  -4.794  1.00 96.24           O  \\nATOM     53  CG1 ILE A   7       5.373   0.416  -2.772  1.00 96.24           C  \\nATOM     54  CG2 ILE A   7       5.590   1.319  -0.424  1.00 96.24           C  \\nATOM     55  CD1 ILE A   7       5.347  -1.055  -2.379  1.00 96.24           C  \\nATOM     56  N   LEU A   8       8.367   2.616  -3.738  1.00 95.09           N  \\nATOM     57  CA  LEU A   8       9.058   2.434  -5.010  1.00 95.09           C  \\nATOM     58  C   LEU A   8       8.745   1.066  -5.608  1.00 95.09           C  \\nATOM     59  CB  LEU A   8      10.570   2.589  -4.826  1.00 95.09           C  \\nATOM     60  O   LEU A   8       8.548   0.094  -4.875  1.00 95.09           O  \\nATOM     61  CG  LEU A   8      11.072   3.996  -4.497  1.00 95.09           C  \\nATOM     62  CD1 LEU A   8      12.549   3.956  -4.119  1.00 95.09           C  \\nATOM     63  CD2 LEU A   8      10.841   4.936  -5.675  1.00 95.09           C  \\nATOM     64  N   GLU A   9       8.751   0.959  -6.932  1.00 95.26           N  \\nATOM     65  CA  GLU A   9       8.532  -0.331  -7.580  1.00 95.26           C  \\nATOM     66  C   GLU A   9       9.681  -1.294  -7.294  1.00 95.26           C  \\nATOM     67  CB  GLU A   9       8.360  -0.151  -9.090  1.00 95.26           C  \\nATOM     68  O   GLU A   9      10.768  -0.871  -6.894  1.00 95.26           O  \\nATOM     69  CG  GLU A   9       9.620   0.321  -9.801  1.00 95.26           C  \\nATOM     70  CD  GLU A   9       9.419   0.545 -11.292  1.00 95.26           C  \\nATOM     71  OE1 GLU A   9      10.416   0.797 -12.007  1.00 95.26           O  \\nATOM     72  OE2 GLU A   9       8.257   0.470 -11.748  1.00 95.26           O  \\nATOM     73  N   GLY A  10       9.445  -2.625  -7.435  1.00 94.59           N  \\nATOM     74  CA  GLY A  10      10.532  -3.582  -7.299  1.00 94.59           C  \\nATOM     75  C   GLY A  10      10.347  -4.533  -6.131  1.00 94.59           C  \\nATOM     76  O   GLY A  10      11.139  -5.459  -5.946  1.00 94.59           O  \\nATOM     77  N   ARG A  11       9.232  -4.324  -5.403  1.00 96.53           N  \\nATOM     78  CA  ARG A  11       8.928  -5.250  -4.317  1.00 96.53           C  \\nATOM     79  C   ARG A  11       8.178  -6.473  -4.834  1.00 96.53           C  \\nATOM     80  CB  ARG A  11       8.108  -4.554  -3.229  1.00 96.53           C  \\nATOM     81  O   ARG A  11       7.398  -6.374  -5.783  1.00 96.53           O  \\nATOM     82  CG  ARG A  11       8.758  -3.295  -2.679  1.00 96.53           C  \\nATOM     83  CD  ARG A  11      10.122  -3.585  -2.067  1.00 96.53           C  \\nATOM     84  NE  ARG A  11      10.872  -2.358  -1.816  1.00 96.53           N  \\nATOM     85  NH1 ARG A  11      12.763  -3.431  -1.033  1.00 96.53           N  \\nATOM     86  NH2 ARG A  11      12.699  -1.142  -1.140  1.00 96.53           N  \\nATOM     87  CZ  ARG A  11      12.110  -2.313  -1.330  1.00 96.53           C  \\nATOM     88  N   SER A  12       8.433  -7.584  -4.170  1.00 98.02           N  \\nATOM     89  CA  SER A  12       7.746  -8.810  -4.564  1.00 98.02           C  \\nATOM     90  C   SER A  12       6.279  -8.780  -4.147  1.00 98.02           C  \\nATOM     91  CB  SER A  12       8.434 -10.031  -3.952  1.00 98.02           C  \\nATOM     92  O   SER A  12       5.902  -8.035  -3.240  1.00 98.02           O  \\nATOM     93  OG  SER A  12       8.221 -10.079  -2.552  1.00 98.02           O  \\nATOM     94  N   ASP A  13       5.466  -9.629  -4.780  1.00 97.67           N  \\nATOM     95  CA  ASP A  13       4.063  -9.749  -4.395  1.00 97.67           C  \\nATOM     96  C   ASP A  13       3.929 -10.148  -2.927  1.00 97.67           C  \\nATOM     97  CB  ASP A  13       3.347 -10.767  -5.284  1.00 97.67           C  \\nATOM     98  O   ASP A  13       3.021  -9.685  -2.233  1.00 97.67           O  \\nATOM     99  CG  ASP A  13       3.120 -10.262  -6.699  1.00 97.67           C  \\nATOM    100  OD1 ASP A  13       3.335  -9.059  -6.959  1.00 97.67           O  \\nATOM    101  OD2 ASP A  13       2.719 -11.074  -7.560  1.00 97.67           O  \\nATOM    102  N   GLU A  14       4.832 -10.987  -2.480  1.00 98.33           N  \\nATOM    103  CA  GLU A  14       4.816 -11.429  -1.089  1.00 98.33           C  \\nATOM    104  C   GLU A  14       5.038 -10.258  -0.135  1.00 98.33           C  \\nATOM    105  CB  GLU A  14       5.878 -12.506  -0.854  1.00 98.33           C  \\nATOM    106  O   GLU A  14       4.379 -10.162   0.902  1.00 98.33           O  \\nATOM    107  CG  GLU A  14       5.576 -13.828  -1.547  1.00 98.33           C  \\nATOM    108  CD  GLU A  14       5.893 -13.811  -3.034  1.00 98.33           C  \\nATOM    109  OE1 GLU A  14       5.379 -14.681  -3.773  1.00 98.33           O  \\nATOM    110  OE2 GLU A  14       6.663 -12.922  -3.462  1.00 98.33           O  \\nATOM    111  N   GLN A  15       5.952  -9.420  -0.471  1.00 98.29           N  \\nATOM    112  CA  GLN A  15       6.215  -8.248   0.358  1.00 98.29           C  \\nATOM    113  C   GLN A  15       5.003  -7.322   0.402  1.00 98.29           C  \\nATOM    114  CB  GLN A  15       7.438  -7.488  -0.159  1.00 98.29           C  \\nATOM    115  O   GLN A  15       4.653  -6.798   1.462  1.00 98.29           O  \\nATOM    116  CG  GLN A  15       8.760  -8.195   0.107  1.00 98.29           C  \\nATOM    117  CD  GLN A  15       9.946  -7.469  -0.499  1.00 98.29           C  \\nATOM    118  NE2 GLN A  15      10.870  -7.032   0.350  1.00 98.29           N  \\nATOM    119  OE1 GLN A  15      10.032  -7.303  -1.720  1.00 98.29           O  \\nATOM    120  N   LYS A  16       4.378  -7.065  -0.695  1.00 98.34           N  \\nATOM    121  CA  LYS A  16       3.195  -6.210  -0.753  1.00 98.34           C  \\nATOM    122  C   LYS A  16       2.047  -6.803   0.059  1.00 98.34           C  \\nATOM    123  CB  LYS A  16       2.757  -5.998  -2.203  1.00 98.34           C  \\nATOM    124  O   LYS A  16       1.332  -6.079   0.753  1.00 98.34           O  \\nATOM    125  CG  LYS A  16       3.724  -5.160  -3.026  1.00 98.34           C  \\nATOM    126  CD  LYS A  16       3.170  -4.869  -4.415  1.00 98.34           C  \\nATOM    127  CE  LYS A  16       3.289  -6.081  -5.329  1.00 98.34           C  \\nATOM    128  NZ  LYS A  16       2.824  -5.776  -6.715  1.00 98.34           N  \\nATOM    129  N   GLU A  17       1.953  -8.154  -0.014  1.00 98.40           N  \\nATOM    130  CA  GLU A  17       0.932  -8.822   0.787  1.00 98.40           C  \\nATOM    131  C   GLU A  17       1.189  -8.632   2.279  1.00 98.40           C  \\nATOM    132  CB  GLU A  17       0.872 -10.314   0.449  1.00 98.40           C  \\nATOM    133  O   GLU A  17       0.261  -8.370   3.046  1.00 98.40           O  \\nATOM    134  CG  GLU A  17       0.254 -10.612  -0.909  1.00 98.40           C  \\nATOM    135  CD  GLU A  17       0.230 -12.095  -1.244  1.00 98.40           C  \\nATOM    136  OE1 GLU A  17      -0.148 -12.454  -2.383  1.00 98.40           O  \\nATOM    137  OE2 GLU A  17       0.590 -12.904  -0.361  1.00 98.40           O  \\nATOM    138  N   THR A  18       2.457  -8.838   2.589  1.00 98.50           N  \\nATOM    139  CA  THR A  18       2.843  -8.663   3.984  1.00 98.50           C  \\nATOM    140  C   THR A  18       2.562  -7.236   4.448  1.00 98.50           C  \\nATOM    141  CB  THR A  18       4.332  -8.991   4.198  1.00 98.50           C  \\nATOM    142  O   THR A  18       2.048  -7.025   5.548  1.00 98.50           O  \\nATOM    143  CG2 THR A  18       4.749  -8.738   5.643  1.00 98.50           C  \\nATOM    144  OG1 THR A  18       4.562 -10.370   3.881  1.00 98.50           O  \\nATOM    145  N   LEU A  19       2.904  -6.242   3.632  1.00 98.43           N  \\nATOM    146  CA  LEU A  19       2.655  -4.839   3.942  1.00 98.43           C  \\nATOM    147  C   LEU A  19       1.169  -4.591   4.181  1.00 98.43           C  \\nATOM    148  CB  LEU A  19       3.158  -3.941   2.809  1.00 98.43           C  \\nATOM    149  O   LEU A  19       0.791  -3.968   5.175  1.00 98.43           O  \\nATOM    150  CG  LEU A  19       2.905  -2.441   2.969  1.00 98.43           C  \\nATOM    151  CD1 LEU A  19       3.573  -1.923   4.238  1.00 98.43           C  \\nATOM    152  CD2 LEU A  19       3.407  -1.681   1.746  1.00 98.43           C  \\nATOM    153  N   ILE A  20       0.301  -5.051   3.331  1.00 98.49           N  \\nATOM    154  CA  ILE A  20      -1.140  -4.854   3.440  1.00 98.49           C  \\nATOM    155  C   ILE A  20      -1.650  -5.476   4.738  1.00 98.49           C  \\nATOM    156  CB  ILE A  20      -1.886  -5.457   2.228  1.00 98.49           C  \\nATOM    157  O   ILE A  20      -2.431  -4.858   5.465  1.00 98.49           O  \\nATOM    158  CG1 ILE A  20      -1.619  -4.624   0.969  1.00 98.49           C  \\nATOM    159  CG2 ILE A  20      -3.388  -5.554   2.512  1.00 98.49           C  \\nATOM    160  CD1 ILE A  20      -2.067  -5.295  -0.323  1.00 98.49           C  \\nATOM    161  N   ARG A  21      -1.182  -6.671   5.042  1.00 98.61           N  \\nATOM    162  CA  ARG A  21      -1.609  -7.370   6.249  1.00 98.61           C  \\nATOM    163  C   ARG A  21      -1.211  -6.595   7.501  1.00 98.61           C  \\nATOM    164  CB  ARG A  21      -1.014  -8.779   6.294  1.00 98.61           C  \\nATOM    165  O   ARG A  21      -2.041  -6.360   8.382  1.00 98.61           O  \\nATOM    166  CG  ARG A  21      -1.414  -9.578   7.524  1.00 98.61           C  \\nATOM    167  CD  ARG A  21      -0.786 -10.965   7.525  1.00 98.61           C  \\nATOM    168  NE  ARG A  21       0.669 -10.898   7.415  1.00 98.61           N  \\nATOM    169  NH1 ARG A  21       1.055 -12.853   8.582  1.00 98.61           N  \\nATOM    170  NH2 ARG A  21       2.815 -11.637   7.761  1.00 98.61           N  \\nATOM    171  CZ  ARG A  21       1.510 -11.796   7.920  1.00 98.61           C  \\nATOM    172  N   GLU A  22      -0.016  -6.213   7.493  1.00 98.58           N  \\nATOM    173  CA  GLU A  22       0.499  -5.565   8.695  1.00 98.58           C  \\nATOM    174  C   GLU A  22      -0.140  -4.194   8.899  1.00 98.58           C  \\nATOM    175  CB  GLU A  22       2.022  -5.430   8.623  1.00 98.58           C  \\nATOM    176  O   GLU A  22      -0.474  -3.820  10.025  1.00 98.58           O  \\nATOM    177  CG  GLU A  22       2.761  -6.758   8.699  1.00 98.58           C  \\nATOM    178  CD  GLU A  22       2.582  -7.469  10.031  1.00 98.58           C  \\nATOM    179  OE1 GLU A  22       2.511  -8.719  10.047  1.00 98.58           O  \\nATOM    180  OE2 GLU A  22       2.511  -6.770  11.067  1.00 98.58           O  \\nATOM    181  N   VAL A  23      -0.287  -3.397   7.924  1.00 98.44           N  \\nATOM    182  CA  VAL A  23      -0.922  -2.086   8.006  1.00 98.44           C  \\nATOM    183  C   VAL A  23      -2.375  -2.241   8.447  1.00 98.44           C  \\nATOM    184  CB  VAL A  23      -0.851  -1.336   6.656  1.00 98.44           C  \\nATOM    185  O   VAL A  23      -2.849  -1.503   9.314  1.00 98.44           O  \\nATOM    186  CG1 VAL A  23      -1.741  -0.095   6.680  1.00 98.44           C  \\nATOM    187  CG2 VAL A  23       0.593  -0.956   6.333  1.00 98.44           C  \\nATOM    188  N   SER A  24      -3.073  -3.170   7.819  1.00 98.56           N  \\nATOM    189  CA  SER A  24      -4.466  -3.418   8.177  1.00 98.56           C  \\nATOM    190  C   SER A  24      -4.606  -3.741   9.661  1.00 98.56           C  \\nATOM    191  CB  SER A  24      -5.039  -4.563   7.341  1.00 98.56           C  \\nATOM    192  O   SER A  24      -5.475  -3.192  10.342  1.00 98.56           O  \\nATOM    193  OG  SER A  24      -5.045  -4.226   5.965  1.00 98.56           O  \\nATOM    194  N   GLU A  25      -3.716  -4.628  10.214  1.00 98.62           N  \\nATOM    195  CA  GLU A  25      -3.751  -5.012  11.622  1.00 98.62           C  \\nATOM    196  C   GLU A  25      -3.431  -3.825  12.525  1.00 98.62           C  \\nATOM    197  CB  GLU A  25      -2.772  -6.158  11.891  1.00 98.62           C  \\nATOM    198  O   GLU A  25      -4.053  -3.652  13.576  1.00 98.62           O  \\nATOM    199  CG  GLU A  25      -3.239  -7.504  11.356  1.00 98.62           C  \\nATOM    200  CD  GLU A  25      -2.211  -8.610  11.536  1.00 98.62           C  \\nATOM    201  OE1 GLU A  25      -2.523  -9.784  11.235  1.00 98.62           O  \\nATOM    202  OE2 GLU A  25      -1.084  -8.300  11.984  1.00 98.62           O  \\nATOM    203  N   ALA A  26      -2.456  -3.042  12.060  1.00 98.52           N  \\nATOM    204  CA  ALA A  26      -2.077  -1.868  12.841  1.00 98.52           C  \\nATOM    205  C   ALA A  26      -3.244  -0.891  12.963  1.00 98.52           C  \\nATOM    206  CB  ALA A  26      -0.872  -1.176  12.209  1.00 98.52           C  \\nATOM    207  O   ALA A  26      -3.518  -0.375  14.049  1.00 98.52           O  \\nATOM    208  N   ILE A  27      -3.878  -0.639  11.879  1.00 98.49           N  \\nATOM    209  CA  ILE A  27      -4.994   0.299  11.843  1.00 98.49           C  \\nATOM    210  C   ILE A  27      -6.156  -0.250  12.669  1.00 98.49           C  \\nATOM    211  CB  ILE A  27      -5.452   0.579  10.394  1.00 98.49           C  \\nATOM    212  O   ILE A  27      -6.763   0.478  13.458  1.00 98.49           O  \\nATOM    213  CG1 ILE A  27      -4.407   1.427   9.659  1.00 98.49           C  \\nATOM    214  CG2 ILE A  27      -6.821   1.265  10.383  1.00 98.49           C  \\nATOM    215  CD1 ILE A  27      -4.699   1.620   8.177  1.00 98.49           C  \\nATOM    216  N   SER A  28      -6.475  -1.527  12.433  1.00 98.55           N  \\nATOM    217  CA  SER A  28      -7.553  -2.146  13.197  1.00 98.55           C  \\nATOM    218  C   SER A  28      -7.298  -2.044  14.697  1.00 98.55           C  \\nATOM    219  CB  SER A  28      -7.718  -3.614  12.798  1.00 98.55           C  \\nATOM    220  O   SER A  28      -8.181  -1.638  15.455  1.00 98.55           O  \\nATOM    221  OG  SER A  28      -8.717  -4.239  13.585  1.00 98.55           O  \\nATOM    222  N   ARG A  29      -6.054  -2.409  15.154  1.00 98.40           N  \\nATOM    223  CA  ARG A  29      -5.687  -2.389  16.566  1.00 98.40           C  \\nATOM    224  C   ARG A  29      -5.695  -0.966  17.114  1.00 98.40           C  \\nATOM    225  CB  ARG A  29      -4.309  -3.021  16.773  1.00 98.40           C  \\nATOM    226  O   ARG A  29      -6.170  -0.726  18.226  1.00 98.40           O  \\nATOM    227  CG  ARG A  29      -4.321  -4.541  16.762  1.00 98.40           C  \\nATOM    228  CD  ARG A  29      -2.959  -5.119  17.122  1.00 98.40           C  \\nATOM    229  NE  ARG A  29      -1.879  -4.432  16.419  1.00 98.40           N  \\nATOM    230  NH1 ARG A  29      -0.178  -5.547  17.514  1.00 98.40           N  \\nATOM    231  NH2 ARG A  29       0.316  -3.970  15.926  1.00 98.40           N  \\nATOM    232  CZ  ARG A  29      -0.583  -4.651  16.621  1.00 98.40           C  \\nATOM    233  N   SER A  30      -5.247   0.039  16.433  1.00 98.44           N  \\nATOM    234  CA  SER A  30      -5.071   1.417  16.882  1.00 98.44           C  \\nATOM    235  C   SER A  30      -6.408   2.145  16.966  1.00 98.44           C  \\nATOM    236  CB  SER A  30      -4.128   2.170  15.943  1.00 98.44           C  \\nATOM    237  O   SER A  30      -6.625   2.954  17.871  1.00 98.44           O  \\nATOM    238  OG  SER A  30      -2.826   1.612  15.983  1.00 98.44           O  \\nATOM    239  N   LEU A  31      -7.273   1.785  16.044  1.00 98.16           N  \\nATOM    240  CA  LEU A  31      -8.500   2.567  15.937  1.00 98.16           C  \\nATOM    241  C   LEU A  31      -9.705   1.752  16.394  1.00 98.16           C  \\nATOM    242  CB  LEU A  31      -8.708   3.045  14.498  1.00 98.16           C  \\nATOM    243  O   LEU A  31     -10.838   2.239  16.360  1.00 98.16           O  \\nATOM    244  CG  LEU A  31      -7.616   3.945  13.918  1.00 98.16           C  \\nATOM    245  CD1 LEU A  31      -7.992   4.395  12.510  1.00 98.16           C  \\nATOM    246  CD2 LEU A  31      -7.377   5.149  14.823  1.00 98.16           C  \\nATOM    247  N   ASP A  32      -9.427   0.552  16.903  1.00 97.71           N  \\nATOM    248  CA  ASP A  32     -10.505  -0.336  17.329  1.00 97.71           C  \\nATOM    249  C   ASP A  32     -11.561  -0.482  16.236  1.00 97.71           C  \\nATOM    250  CB  ASP A  32     -11.149   0.181  18.617  1.00 97.71           C  \\nATOM    251  O   ASP A  32     -12.756  -0.333  16.496  1.00 97.71           O  \\nATOM    252  CG  ASP A  32     -11.984  -0.871  19.326  1.00 97.71           C  \\nATOM    253  OD1 ASP A  32     -11.695  -2.078  19.182  1.00 97.71           O  \\nATOM    254  OD2 ASP A  32     -12.943  -0.489  20.032  1.00 97.71           O  \\nATOM    255  N   ALA A  33     -11.215  -0.582  14.978  1.00 97.67           N  \\nATOM    256  CA  ALA A  33     -12.076  -0.838  13.826  1.00 97.67           C  \\nATOM    257  C   ALA A  33     -11.964  -2.290  13.369  1.00 97.67           C  \\nATOM    258  CB  ALA A  33     -11.726   0.106  12.679  1.00 97.67           C  \\nATOM    259  O   ALA A  33     -10.916  -2.919  13.533  1.00 97.67           O  \\nATOM    260  N   PRO A  34     -13.231  -2.868  12.934  1.00 98.24           N  \\nATOM    261  CA  PRO A  34     -13.135  -4.226  12.395  1.00 98.24           C  \\nATOM    262  C   PRO A  34     -12.138  -4.335  11.243  1.00 98.24           C  \\nATOM    263  CB  PRO A  34     -14.559  -4.515  11.913  1.00 98.24           C  \\nATOM    264  O   PRO A  34     -12.081  -3.450  10.385  1.00 98.24           O  \\nATOM    265  CG  PRO A  34     -15.414  -3.520  12.629  1.00 98.24           C  \\nATOM    266  CD  PRO A  34     -14.588  -2.299  12.914  1.00 98.24           C  \\nATOM    267  N   LEU A  35     -11.395  -5.427  11.278  1.00 97.96           N  \\nATOM    268  CA  LEU A  35     -10.378  -5.651  10.256  1.00 97.96           C  \\nATOM    269  C   LEU A  35     -10.992  -5.609   8.861  1.00 97.96           C  \\nATOM    270  CB  LEU A  35      -9.680  -6.995  10.480  1.00 97.96           C  \\nATOM    271  O   LEU A  35     -10.387  -5.076   7.928  1.00 97.96           O  \\nATOM    272  CG  LEU A  35      -8.469  -7.285   9.592  1.00 97.96           C  \\nATOM    273  CD1 LEU A  35      -7.387  -6.232   9.810  1.00 97.96           C  \\nATOM    274  CD2 LEU A  35      -7.925  -8.683   9.870  1.00 97.96           C  \\nATOM    275  N   THR A  36     -12.171  -6.012   8.733  1.00 98.01           N  \\nATOM    276  CA  THR A  36     -12.850  -6.126   7.447  1.00 98.01           C  \\nATOM    277  C   THR A  36     -13.187  -4.746   6.890  1.00 98.01           C  \\nATOM    278  CB  THR A  36     -14.137  -6.963   7.567  1.00 98.01           C  \\nATOM    279  O   THR A  36     -13.493  -4.608   5.704  1.00 98.01           O  \\nATOM    280  CG2 THR A  36     -13.819  -8.411   7.926  1.00 98.01           C  \\nATOM    281  OG1 THR A  36     -14.972  -6.401   8.587  1.00 98.01           O  \\nATOM    282  N   SER A  37     -13.147  -3.780   7.762  1.00 98.04           N  \\nATOM    283  CA  SER A  37     -13.490  -2.423   7.351  1.00 98.04           C  \\nATOM    284  C   SER A  37     -12.256  -1.659   6.883  1.00 98.04           C  \\nATOM    285  CB  SER A  37     -14.162  -1.669   8.499  1.00 98.04           C  \\nATOM    286  O   SER A  37     -12.370  -0.552   6.352  1.00 98.04           O  \\nATOM    287  OG  SER A  37     -13.230  -1.384   9.528  1.00 98.04           O  \\nATOM    288  N   VAL A  38     -10.999  -2.191   6.892  1.00 98.48           N  \\nATOM    289  CA  VAL A  38      -9.740  -1.540   6.541  1.00 98.48           C  \\nATOM    290  C   VAL A  38      -9.418  -1.797   5.071  1.00 98.48           C  \\nATOM    291  CB  VAL A  38      -8.579  -2.031   7.435  1.00 98.48           C  \\nATOM    292  O   VAL A  38      -9.496  -2.934   4.601  1.00 98.48           O  \\nATOM    293  CG1 VAL A  38      -7.258  -1.401   6.998  1.00 98.48           C  \\nATOM    294  CG2 VAL A  38      -8.866  -1.716   8.902  1.00 98.48           C  \\nATOM    295  N   ARG A  39      -9.147  -0.778   4.334  1.00 98.58           N  \\nATOM    296  CA  ARG A  39      -8.650  -0.847   2.964  1.00 98.58           C  \\nATOM    297  C   ARG A  39      -7.236  -0.284   2.866  1.00 98.58           C  \\nATOM    298  CB  ARG A  39      -9.582  -0.092   2.014  1.00 98.58           C  \\nATOM    299  O   ARG A  39      -6.940   0.767   3.439  1.00 98.58           O  \\nATOM    300  CG  ARG A  39     -10.918  -0.781   1.786  1.00 98.58           C  \\nATOM    301  CD  ARG A  39     -11.949  -0.373   2.829  1.00 98.58           C  \\nATOM    302  NE  ARG A  39     -13.267  -0.924   2.528  1.00 98.58           N  \\nATOM    303  NH1 ARG A  39     -13.869  -1.236   4.737  1.00 98.58           N  \\nATOM    304  NH2 ARG A  39     -15.320  -1.809   3.057  1.00 98.58           N  \\nATOM    305  CZ  ARG A  39     -14.149  -1.322   3.442  1.00 98.58           C  \\nATOM    306  N   VAL A  40      -6.342  -1.028   2.187  1.00 98.46           N  \\nATOM    307  CA  VAL A  40      -4.973  -0.601   1.918  1.00 98.46           C  \\nATOM    308  C   VAL A  40      -4.741  -0.529   0.411  1.00 98.46           C  \\nATOM    309  CB  VAL A  40      -3.944  -1.552   2.571  1.00 98.46           C  \\nATOM    310  O   VAL A  40      -4.968  -1.506  -0.307  1.00 98.46           O  \\nATOM    311  CG1 VAL A  40      -2.519  -1.106   2.251  1.00 98.46           C  \\nATOM    312  CG2 VAL A  40      -4.161  -1.615   4.082  1.00 98.46           C  \\nATOM    313  N   ILE A  41      -4.368   0.630  -0.026  1.00 98.49           N  \\nATOM    314  CA  ILE A  41      -4.064   0.853  -1.435  1.00 98.49           C  \\nATOM    315  C   ILE A  41      -2.574   1.144  -1.602  1.00 98.49           C  \\nATOM    316  CB  ILE A  41      -4.905   2.011  -2.018  1.00 98.49           C  \\nATOM    317  O   ILE A  41      -2.055   2.104  -1.028  1.00 98.49           O  \\nATOM    318  CG1 ILE A  41      -6.398   1.764  -1.771  1.00 98.49           C  \\nATOM    319  CG2 ILE A  41      -4.619   2.186  -3.513  1.00 98.49           C  \\nATOM    320  CD1 ILE A  41      -7.264   3.007  -1.925  1.00 98.49           C  \\nATOM    321  N   ILE A  42      -1.920   0.229  -2.362  1.00 98.21           N  \\nATOM    322  CA  ILE A  42      -0.506   0.434  -2.657  1.00 98.21           C  \\nATOM    323  C   ILE A  42      -0.352   1.041  -4.050  1.00 98.21           C  \\nATOM    324  CB  ILE A  42       0.289  -0.888  -2.558  1.00 98.21           C  \\nATOM    325  O   ILE A  42      -0.908   0.527  -5.023  1.00 98.21           O  \\nATOM    326  CG1 ILE A  42       0.231  -1.439  -1.129  1.00 98.21           C  \\nATOM    327  CG2 ILE A  42       1.738  -0.681  -3.007  1.00 98.21           C  \\nATOM    328  CD1 ILE A  42       0.871  -2.812  -0.969  1.00 98.21           C  \\nATOM    329  N   THR A  43       0.334   2.227  -4.044  1.00 97.66           N  \\nATOM    330  CA  THR A  43       0.757   2.844  -5.296  1.00 97.66           C  \\nATOM    331  C   THR A  43       2.271   2.746  -5.463  1.00 97.66           C  \\nATOM    332  CB  THR A  43       0.325   4.320  -5.366  1.00 97.66           C  \\nATOM    333  O   THR A  43       3.026   3.253  -4.631  1.00 97.66           O  \\nATOM    334  CG2 THR A  43       0.683   4.934  -6.716  1.00 97.66           C  \\nATOM    335  OG1 THR A  43      -1.093   4.406  -5.176  1.00 97.66           O  \\nATOM    336  N   GLU A  44       2.607   2.069  -6.548  1.00 96.48           N  \\nATOM    337  CA  GLU A  44       4.030   1.924  -6.843  1.00 96.48           C  \\nATOM    338  C   GLU A  44       4.519   3.040  -7.762  1.00 96.48           C  \\nATOM    339  CB  GLU A  44       4.312   0.559  -7.475  1.00 96.48           C  \\nATOM    340  O   GLU A  44       3.889   3.333  -8.780  1.00 96.48           O  \\nATOM    341  CG  GLU A  44       4.008  -0.618  -6.560  1.00 96.48           C  \\nATOM    342  CD  GLU A  44       4.286  -1.967  -7.204  1.00 96.48           C  \\nATOM    343  OE1 GLU A  44       5.426  -2.472  -7.085  1.00 96.48           O  \\nATOM    344  OE2 GLU A  44       3.358  -2.522  -7.833  1.00 96.48           O  \\nATOM    345  N   MET A  45       5.717   3.602  -7.315  1.00 94.79           N  \\nATOM    346  CA  MET A  45       6.325   4.673  -8.099  1.00 94.79           C  \\nATOM    347  C   MET A  45       7.580   4.181  -8.812  1.00 94.79           C  \\nATOM    348  CB  MET A  45       6.665   5.868  -7.206  1.00 94.79           C  \\nATOM    349  O   MET A  45       8.448   3.562  -8.193  1.00 94.79           O  \\nATOM    350  CG  MET A  45       5.462   6.458  -6.488  1.00 94.79           C  \\nATOM    351  SD  MET A  45       5.871   8.001  -5.583  1.00 94.79           S  \\nATOM    352  CE  MET A  45       7.683   7.915  -5.607  1.00 94.79           C  \\nATOM    353  N   ALA A  46       7.531   4.411 -10.106  1.00 93.83           N  \\nATOM    354  CA  ALA A  46       8.775   4.157 -10.828  1.00 93.83           C  \\nATOM    355  C   ALA A  46       9.909   5.026 -10.289  1.00 93.83           C  \\nATOM    356  CB  ALA A  46       8.584   4.404 -12.322  1.00 93.83           C  \\nATOM    357  O   ALA A  46       9.695   6.189  -9.939  1.00 93.83           O  \\nATOM    358  N   LYS A  47      11.130   4.449 -10.208  1.00 88.39           N  \\nATOM    359  CA  LYS A  47      12.282   5.155  -9.653  1.00 88.39           C  \\nATOM    360  C   LYS A  47      12.567   6.437 -10.430  1.00 88.39           C  \\nATOM    361  CB  LYS A  47      13.517   4.253  -9.658  1.00 88.39           C  \\nATOM    362  O   LYS A  47      13.068   7.412  -9.866  1.00 88.39           O  \\nATOM    363  CG  LYS A  47      13.450   3.105  -8.662  1.00 88.39           C  \\nATOM    364  CD  LYS A  47      14.744   2.302  -8.647  1.00 88.39           C  \\nATOM    365  CE  LYS A  47      14.679   1.153  -7.649  1.00 88.39           C  \\nATOM    366  NZ  LYS A  47      15.957   0.381  -7.608  1.00 88.39           N  \\nATOM    367  N   GLY A  48      12.176   6.523 -11.665  1.00 93.04           N  \\nATOM    368  CA  GLY A  48      12.368   7.700 -12.499  1.00 93.04           C  \\nATOM    369  C   GLY A  48      11.334   8.781 -12.251  1.00 93.04           C  \\nATOM    370  O   GLY A  48      11.498   9.918 -12.699  1.00 93.04           O  \\nATOM    371  N   HIS A  49      10.354   8.530 -11.529  1.00 92.01           N  \\nATOM    372  CA  HIS A  49       9.259   9.456 -11.264  1.00 92.01           C  \\nATOM    373  C   HIS A  49       9.249   9.894  -9.803  1.00 92.01           C  \\nATOM    374  CB  HIS A  49       7.917   8.818 -11.629  1.00 92.01           C  \\nATOM    375  O   HIS A  49       8.441  10.739  -9.409  1.00 92.01           O  \\nATOM    376  CG  HIS A  49       7.797   8.461 -13.077  1.00 92.01           C  \\nATOM    377  CD2 HIS A  49       8.654   8.636 -14.110  1.00 92.01           C  \\nATOM    378  ND1 HIS A  49       6.680   7.847 -13.601  1.00 92.01           N  \\nATOM    379  CE1 HIS A  49       6.858   7.658 -14.898  1.00 92.01           C  \\nATOM    380  NE2 HIS A  49       8.047   8.128 -15.232  1.00 92.01           N  \\nATOM    381  N   PHE A  50      10.200   9.314  -9.048  1.00 93.15           N  \\nATOM    382  CA  PHE A  50      10.239   9.615  -7.622  1.00 93.15           C  \\nATOM    383  C   PHE A  50      11.481  10.425  -7.274  1.00 93.15           C  \\nATOM    384  CB  PHE A  50      10.205   8.324  -6.798  1.00 93.15           C  \\nATOM    385  O   PHE A  50      12.606   9.978  -7.508  1.00 93.15           O  \\nATOM    386  CG  PHE A  50       9.812   8.532  -5.360  1.00 93.15           C  \\nATOM    387  CD1 PHE A  50      10.779   8.601  -4.364  1.00 93.15           C  \\nATOM    388  CD2 PHE A  50       8.476   8.658  -5.005  1.00 93.15           C  \\nATOM    389  CE1 PHE A  50      10.418   8.793  -3.032  1.00 93.15           C  \\nATOM    390  CE2 PHE A  50       8.107   8.850  -3.676  1.00 93.15           C  \\nATOM    391  CZ  PHE A  50       9.080   8.917  -2.692  1.00 93.15           C  \\nATOM    392  N   GLY A  51      11.284  11.723  -6.759  1.00 92.18           N  \\nATOM    393  CA  GLY A  51      12.375  12.612  -6.394  1.00 92.18           C  \\nATOM    394  C   GLY A  51      12.572  12.730  -4.894  1.00 92.18           C  \\nATOM    395  O   GLY A  51      11.601  12.747  -4.135  1.00 92.18           O  \\nATOM    396  N   ILE A  52      13.811  12.642  -4.482  1.00 92.04           N  \\nATOM    397  CA  ILE A  52      14.175  12.878  -3.089  1.00 92.04           C  \\nATOM    398  C   ILE A  52      15.210  13.998  -3.009  1.00 92.04           C  \\nATOM    399  CB  ILE A  52      14.721  11.595  -2.423  1.00 92.04           C  \\nATOM    400  O   ILE A  52      16.318  13.867  -3.535  1.00 92.04           O  \\nATOM    401  CG1 ILE A  52      13.720  10.445  -2.578  1.00 92.04           C  \\nATOM    402  CG2 ILE A  52      15.040  11.848  -0.946  1.00 92.04           C  \\nATOM    403  CD1 ILE A  52      14.297   9.074  -2.253  1.00 92.04           C  \\nATOM    404  N   GLY A  53      14.812  15.164  -2.359  1.00 90.76           N  \\nATOM    405  CA  GLY A  53      15.751  16.265  -2.208  1.00 90.76           C  \\nATOM    406  C   GLY A  53      16.263  16.798  -3.533  1.00 90.76           C  \\nATOM    407  O   GLY A  53      17.432  17.171  -3.648  1.00 90.76           O  \\nATOM    408  N   GLY A  54      15.464  16.765  -4.611  1.00 92.33           N  \\nATOM    409  CA  GLY A  54      15.784  17.346  -5.905  1.00 92.33           C  \\nATOM    410  C   GLY A  54      16.478  16.375  -6.840  1.00 92.33           C  \\nATOM    411  O   GLY A  54      16.912  16.756  -7.929  1.00 92.33           O  \\nATOM    412  N   GLU A  55      16.677  15.104  -6.412  1.00 92.75           N  \\nATOM    413  CA  GLU A  55      17.312  14.073  -7.227  1.00 92.75           C  \\nATOM    414  C   GLU A  55      16.390  12.872  -7.416  1.00 92.75           C  \\nATOM    415  CB  GLU A  55      18.634  13.626  -6.596  1.00 92.75           C  \\nATOM    416  O   GLU A  55      15.656  12.496  -6.500  1.00 92.75           O  \\nATOM    417  CG  GLU A  55      19.679  14.729  -6.513  1.00 92.75           C  \\nATOM    418  CD  GLU A  55      21.022  14.245  -5.990  1.00 92.75           C  \\nATOM    419  OE1 GLU A  55      21.973  15.056  -5.917  1.00 92.75           O  \\nATOM    420  OE2 GLU A  55      21.124  13.045  -5.650  1.00 92.75           O  \\nATOM    421  N   LEU A  56      16.502  12.358  -8.671  1.00 90.94           N  \\nATOM    422  CA  LEU A  56      15.716  11.155  -8.929  1.00 90.94           C  \\nATOM    423  C   LEU A  56      16.149  10.016  -8.012  1.00 90.94           C  \\nATOM    424  CB  LEU A  56      15.855  10.728 -10.393  1.00 90.94           C  \\nATOM    425  O   LEU A  56      17.344   9.822  -7.777  1.00 90.94           O  \\nATOM    426  CG  LEU A  56      15.129  11.594 -11.424  1.00 90.94           C  \\nATOM    427  CD1 LEU A  56      15.515  11.171 -12.837  1.00 90.94           C  \\nATOM    428  CD2 LEU A  56      13.620  11.507 -11.227  1.00 90.94           C  \\nATOM    429  N   ALA A  57      15.110   9.344  -7.521  1.00 89.07           N  \\nATOM    430  CA  ALA A  57      15.412   8.192  -6.675  1.00 89.07           C  \\nATOM    431  C   ALA A  57      16.193   7.133  -7.447  1.00 89.07           C  \\nATOM    432  CB  ALA A  57      14.124   7.594  -6.112  1.00 89.07           C  \\nATOM    433  O   ALA A  57      16.916   6.329  -6.853  1.00 89.07           O  \\nATOM    434  N   SER A  58      16.133   7.139  -8.641  1.00 87.98           N  \\nATOM    435  CA  SER A  58      16.824   6.198  -9.516  1.00 87.98           C  \\nATOM    436  C   SER A  58      18.317   6.502  -9.587  1.00 87.98           C  \\nATOM    437  CB  SER A  58      16.221   6.231 -10.921  1.00 87.98           C  \\nATOM    438  O   SER A  58      19.113   5.643  -9.972  1.00 87.98           O  \\nATOM    439  OG  SER A  58      16.306   7.533 -11.474  1.00 87.98           O  \\nATOM    440  N   LYS A  59      18.687   7.833  -9.290  1.00 81.15           N  \\nATOM    441  CA  LYS A  59      20.089   8.237  -9.363  1.00 81.15           C  \\nATOM    442  C   LYS A  59      20.838   7.855  -8.090  1.00 81.15           C  \\nATOM    443  CB  LYS A  59      20.201   9.743  -9.605  1.00 81.15           C  \\nATOM    444  O   LYS A  59      21.997   7.438  -8.147  1.00 81.15           O  \\nATOM    445  CG  LYS A  59      19.928  10.161 -11.042  1.00 81.15           C  \\nATOM    446  CD  LYS A  59      20.300  11.619 -11.281  1.00 81.15           C  \\nATOM    447  CE  LYS A  59      19.997  12.048 -12.710  1.00 81.15           C  \\nATOM    448  NZ  LYS A  59      20.393  13.466 -12.958  1.00 81.15           N  \\nTER     449      LYS A  59                                                      \\nENDMDL                                                                          \\nEND                                                                             \\n\",\"pdb\");\n",
              "\tviewer_16559102159225733.setStyle({\"chain\": \"A\"},{\"cartoon\": {\"color\": \"lime\"}});\n",
              "\tviewer_16559102159225733.addStyle({\"and\": [{\"resn\": [\"GLY\", \"PRO\"], \"invert\": true}, {\"atom\": [\"C\", \"O\", \"N\"], \"invert\": true}]},{\"stick\": {\"colorscheme\": \"WhiteCarbon\", \"radius\": 0.3}});\n",
              "\tviewer_16559102159225733.addStyle({\"and\": [{\"resn\": \"GLY\"}, {\"atom\": \"CA\"}]},{\"sphere\": {\"colorscheme\": \"WhiteCarbon\", \"radius\": 0.3}});\n",
              "\tviewer_16559102159225733.addStyle({\"and\": [{\"resn\": \"PRO\"}, {\"atom\": [\"C\", \"O\"], \"invert\": true}]},{\"stick\": {\"colorscheme\": \"WhiteCarbon\", \"radius\": 0.3}});\n",
              "\tviewer_16559102159225733.addStyle({\"atom\": [\"C\", \"O\", \"N\", \"CA\"]},{\"stick\": {\"colorscheme\": \"WhiteCarbon\", \"radius\": 0.3}});\n",
              "\tviewer_16559102159225733.zoomTo();\n",
              "viewer_16559102159225733.render();\n",
              "});\n",
              "</script>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "33g5IIegij5R",
        "cellView": "form"
      },
      "source": [
        "#@title Package and download results\n",
        "#@markdown If you are having issues downloading the result archive, try disabling your adblocker and run this cell again. If that fails click on the little folder icon to the left, navigate to file: `jobname.result.zip`, right-click and select \\\"Download\\\" (see [screenshot](https://pbs.twimg.com/media/E6wRW2lWUAEOuoe?format=jpg&name=small)).\n",
        "\n",
        "if msa_mode == \"custom\":\n",
        "  print(\"Don't forget to cite your custom MSA generation method.\")\n",
        "\n",
        "!zip -FSr $jobname\".result.zip\" config.json $jobname*\".json\" $jobname*\".a3m\" $jobname*\"relaxed_rank_\"*\".pdb\" \"cite.bibtex\" $jobname*\".png\"\n",
        "files.download(f\"{jobname}.result.zip\")\n",
        "\n",
        "if save_to_google_drive == True and drive:\n",
        "  uploaded = drive.CreateFile({'title': f\"{jobname}.result.zip\"})\n",
        "  uploaded.SetContentFile(f\"{jobname}.result.zip\")\n",
        "  uploaded.Upload()\n",
        "  print(f\"Uploaded {jobname}.result.zip to Google Drive with ID {uploaded.get('id')}\")"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}