Example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "from samcc.bundleClass import bundleClass\n",
    "from samcc.wrappers import run_dssp\n",
    "from samcc.wrappers import run_socket\n",
    "from samcc.socket_parser import parse_socket_output\n",
    "from samcc.socketClass import socket_class"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Before you start, please take a look at our <a href=\"https://academic.oup.com/bioinformatics/article/36/22-23/5368/6039120\" target=\"_blank\">paper</a> and get acquainted with the following terms:\n",
    "\n",
    "* Knobs-into-holes packing\n",
    "* Bundle layers\n",
    "* Bundle periodicity vs. helical periodicity\n",
    "* Crick angle and helix axial rotation\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's analyze <a href=\"https://www.rcsb.org/structure/3tsi\" target=\"_blank\">this</a> structure!\n",
    "\n",
    "\n",
    "![](./example_in/3tsi_view.png)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pdbpath='./example_in/3tsi.pdb'\n",
    "\n",
    "dssp_binary = '/opt/apps/dssp-2.3.0/mkdssp' # do not use newer version!\n",
    "socket_binary = '/opt/apps/socket/socket'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# predict secondary structure with DSSP\n",
    "dssppath = run_dssp(pdbpath, dssp_binary)\n",
    "\n",
    "# predict coiled-coil regions with SOCKET\n",
    "socketpath = run_socket(pdbpath, dssppath, socket_binary)\n",
    "\n",
    "# parse SOCKET data\n",
    "socket_data = parse_socket_output(socketpath)\n",
    "s = socket_class(socket_data, pdbpath)\n",
    "\n",
    "# remove temporary files\n",
    "os.remove(dssppath)\n",
    "os.remove(socketpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# raw SOCKET data suggests that this structure contains two coiled-coil domains\n",
    "# what is kind of strange, given how the 3tsi structure looks like\n",
    "len(socket_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define a bundle object for each detected domain\n",
    "bundles = s.get_bundles(res_num_layer_detection=5, distance_threshold='auto', search_layer_setting_num=9) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['10', '11'] bundles detected...\n"
     ]
    }
   ],
   "source": [
    "# bundle object provides various measurement methods \n",
    "bundle_dfs = {}\n",
    "\n",
    "for bundle in bundles: \n",
    "    bundle.calc_bundleaxis() # define bundle axis\n",
    "    bundle.calc_radius() # define bundle radius\n",
    "    bundle.calc_periodicity() # define helical and bundle periodicity\n",
    "    bundle_dfs[bundle.socket_cc_id] = bundle.gendf() # export a pandas data frame with all the data\n",
    "    \n",
    "print(f'{list(bundle_dfs.keys())} bundles detected...') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <td>7.085469</td>\n",
       "      <td>3.524167</td>\n",
       "      <td>3.677469</td>\n",
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       "      <td>68</td>\n",
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       "      <td>False</td>\n",
       "      <td>7.232128</td>\n",
       "      <td>3.513896</td>\n",
       "      <td>3.645082</td>\n",
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       "      <th>0</th>\n",
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       "      <td>A</td>\n",
       "      <td>False</td>\n",
       "      <td>7.011739</td>\n",
       "      <td>3.505912</td>\n",
       "      <td>3.706534</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>VAL</td>\n",
       "      <td>71</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>7.045562</td>\n",
       "      <td>3.499052</td>\n",
       "      <td>3.679608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>VAL</td>\n",
       "      <td>71</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.106508</td>\n",
       "      <td>3.497931</td>\n",
       "      <td>3.753702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>VAL</td>\n",
       "      <td>71</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.085141</td>\n",
       "      <td>3.523177</td>\n",
       "      <td>3.649385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">11</th>\n",
       "      <th>0</th>\n",
       "      <td>ALA</td>\n",
       "      <td>72</td>\n",
       "      <td>A</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ALA</td>\n",
       "      <td>72</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ALA</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ALA</td>\n",
       "      <td>72</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            res_name  res_number chain_name  chain_ap    radius         P  \\\n",
       "layer chain                                                                 \n",
       "0     0          ILE          61          A     False       NaN       NaN   \n",
       "      1          ILE          61          B     False       NaN       NaN   \n",
       "      2          ILE          61          C     False       NaN       NaN   \n",
       "      3          ILE          61          D     False       NaN       NaN   \n",
       "1     0          THR          62          A     False  7.036590  3.571958   \n",
       "      1          THR          62          B     False  7.738209  3.538782   \n",
       "      2          THR          62          C     False  8.067684  3.516832   \n",
       "      3          THR          62          D     False  7.667452  3.562139   \n",
       "2     0          ASP          63          A     False  6.960430  3.567233   \n",
       "      1          ASP          63          B     False  7.578200  3.538318   \n",
       "      2          ASP          63          C     False  7.917295  3.514318   \n",
       "      3          ASP          63          D     False  7.493927  3.567301   \n",
       "3     0          LEU          64          A     False  7.027660  3.548049   \n",
       "      1          LEU          64          B     False  7.434930  3.535288   \n",
       "      2          LEU          64          C     False  7.723458  3.515569   \n",
       "      3          LEU          64          D     False  7.441125  3.560884   \n",
       "4     0          LEU          65          A     False  6.979624  3.538554   \n",
       "      1          LEU          65          B     False  7.348637  3.533707   \n",
       "      2          LEU          65          C     False  7.572345  3.521251   \n",
       "      3          LEU          65          D     False  7.331884  3.544873   \n",
       "5     0          ASN          66          A     False  6.981897  3.535228   \n",
       "      1          ASN          66          B     False  7.222234  3.534190   \n",
       "      2          ASN          66          C     False  7.453273  3.515992   \n",
       "      3          ASN          66          D     False  7.284371  3.533471   \n",
       "6     0          ASN          67          A     False  6.970837  3.525327   \n",
       "      1          ASN          67          B     False  7.107838  3.532816   \n",
       "      2          ASN          67          C     False  7.336192  3.513986   \n",
       "      3          ASN          67          D     False  7.177512  3.536031   \n",
       "7     0          ILE          68          A     False  6.959516  3.521887   \n",
       "      1          ILE          68          B     False  7.085469  3.524167   \n",
       "      2          ILE          68          C     False  7.232128  3.513896   \n",
       "      3          ILE          68          D     False  7.116015  3.531873   \n",
       "8     0          LEU          69          A     False  6.966346  3.519830   \n",
       "      1          LEU          69          B     False  7.059060  3.515143   \n",
       "      2          LEU          69          C     False  7.209570  3.504348   \n",
       "      3          LEU          69          D     False  7.094555  3.522417   \n",
       "9     0          SER          70          A     False  6.955199  3.512679   \n",
       "      1          SER          70          B     False  7.022403  3.506439   \n",
       "      2          SER          70          C     False  7.144721  3.498985   \n",
       "      3          SER          70          D     False  7.032019  3.524853   \n",
       "10    0          VAL          71          A     False  7.011739  3.505912   \n",
       "      1          VAL          71          B     False  7.045562  3.499052   \n",
       "      2          VAL          71          C     False  7.106508  3.497931   \n",
       "      3          VAL          71          D     False  7.085141  3.523177   \n",
       "11    0          ALA          72          A     False       NaN       NaN   \n",
       "      1          ALA          72          B     False       NaN       NaN   \n",
       "      2          ALA          72          C     False       NaN       NaN   \n",
       "      3          ALA          72          D     False       NaN       NaN   \n",
       "\n",
       "                    p  \n",
       "layer chain            \n",
       "0     0           NaN  \n",
       "      1           NaN  \n",
       "      2           NaN  \n",
       "      3           NaN  \n",
       "1     0      3.654319  \n",
       "      1      3.551030  \n",
       "      2      3.726579  \n",
       "      3      3.645644  \n",
       "2     0      3.684627  \n",
       "      1      3.566128  \n",
       "      2      3.678419  \n",
       "      3      3.668617  \n",
       "3     0      3.640959  \n",
       "      1      3.583972  \n",
       "      2      3.628983  \n",
       "      3      3.673169  \n",
       "4     0      3.552879  \n",
       "      1      3.612964  \n",
       "      2      3.637430  \n",
       "      3      3.602100  \n",
       "5     0      3.585816  \n",
       "      1      3.616998  \n",
       "      2      3.672585  \n",
       "      3      3.597415  \n",
       "6     0      3.650477  \n",
       "      1      3.643931  \n",
       "      2      3.671667  \n",
       "      3      3.656200  \n",
       "7     0      3.653144  \n",
       "      1      3.677469  \n",
       "      2      3.645082  \n",
       "      3      3.631741  \n",
       "8     0      3.657403  \n",
       "      1      3.654407  \n",
       "      2      3.653197  \n",
       "      3      3.598894  \n",
       "9     0      3.689754  \n",
       "      1      3.663948  \n",
       "      2      3.707753  \n",
       "      3      3.625069  \n",
       "10    0      3.706534  \n",
       "      1      3.679608  \n",
       "      2      3.753702  \n",
       "      3      3.649385  \n",
       "11    0           NaN  \n",
       "      1           NaN  \n",
       "      2           NaN  \n",
       "      3           NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now, let's take a look at the two domains.\n",
    "# P and p denote bundle and helical periodicity, respectively.\n",
    "bundle_dfs['10']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>res_name</th>\n",
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       "      <td>3.567009</td>\n",
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       "      <td>PRO</td>\n",
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       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.737620</td>\n",
       "      <td>3.657901</td>\n",
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       "      <th>0</th>\n",
       "      <td>LEU</td>\n",
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       "      <td>3.640626</td>\n",
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       "      <td>LEU</td>\n",
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       "      <td>LEU</td>\n",
       "      <td>85</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.891293</td>\n",
       "      <td>3.647823</td>\n",
       "      <td>3.605697</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LEU</td>\n",
       "      <td>85</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.655243</td>\n",
       "      <td>3.642792</td>\n",
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       "      <th rowspan=\"4\" valign=\"top\">3</th>\n",
       "      <th>0</th>\n",
       "      <td>GLN</td>\n",
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       "      <td>False</td>\n",
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       "      <td>3.640281</td>\n",
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       "      <td>GLN</td>\n",
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       "      <td>3.651146</td>\n",
       "      <td>3.624244</td>\n",
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       "      <th>3</th>\n",
       "      <td>GLN</td>\n",
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       "      <td>D</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">4</th>\n",
       "      <th>0</th>\n",
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       "      <td>3.629298</td>\n",
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       "      <th>1</th>\n",
       "      <td>LEU</td>\n",
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       "      <td>False</td>\n",
       "      <td>7.787281</td>\n",
       "      <td>3.662848</td>\n",
       "      <td>3.592058</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LEU</td>\n",
       "      <td>87</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.934494</td>\n",
       "      <td>3.650698</td>\n",
       "      <td>3.642253</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LEU</td>\n",
       "      <td>87</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.599870</td>\n",
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       "      <td>3.624172</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">5</th>\n",
       "      <th>0</th>\n",
       "      <td>ASP</td>\n",
       "      <td>88</td>\n",
       "      <td>A</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ASP</td>\n",
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       "      <td>False</td>\n",
       "      <td>7.796716</td>\n",
       "      <td>3.657196</td>\n",
       "      <td>3.614704</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ASP</td>\n",
       "      <td>88</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.900749</td>\n",
       "      <td>3.655130</td>\n",
       "      <td>3.608444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ASP</td>\n",
       "      <td>88</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.558544</td>\n",
       "      <td>3.644225</td>\n",
       "      <td>3.659191</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">6</th>\n",
       "      <th>0</th>\n",
       "      <td>THR</td>\n",
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       "      <td>False</td>\n",
       "      <td>7.681119</td>\n",
       "      <td>3.644050</td>\n",
       "      <td>3.651458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>THR</td>\n",
       "      <td>89</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>7.788975</td>\n",
       "      <td>3.648330</td>\n",
       "      <td>3.659564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>THR</td>\n",
       "      <td>89</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.890719</td>\n",
       "      <td>3.649954</td>\n",
       "      <td>3.570419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>THR</td>\n",
       "      <td>89</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.565168</td>\n",
       "      <td>3.647419</td>\n",
       "      <td>3.638641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">7</th>\n",
       "      <th>0</th>\n",
       "      <td>LEU</td>\n",
       "      <td>90</td>\n",
       "      <td>A</td>\n",
       "      <td>False</td>\n",
       "      <td>7.604975</td>\n",
       "      <td>3.655490</td>\n",
       "      <td>3.631477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LEU</td>\n",
       "      <td>90</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>7.743872</td>\n",
       "      <td>3.647420</td>\n",
       "      <td>3.618760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LEU</td>\n",
       "      <td>90</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.822314</td>\n",
       "      <td>3.657222</td>\n",
       "      <td>3.656269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LEU</td>\n",
       "      <td>90</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.461780</td>\n",
       "      <td>3.665765</td>\n",
       "      <td>3.582190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">8</th>\n",
       "      <th>0</th>\n",
       "      <td>GLU</td>\n",
       "      <td>91</td>\n",
       "      <td>A</td>\n",
       "      <td>False</td>\n",
       "      <td>7.576451</td>\n",
       "      <td>3.654418</td>\n",
       "      <td>3.709208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GLU</td>\n",
       "      <td>91</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>7.661929</td>\n",
       "      <td>3.653039</td>\n",
       "      <td>3.633819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GLU</td>\n",
       "      <td>91</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.692617</td>\n",
       "      <td>3.677681</td>\n",
       "      <td>3.677449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>GLU</td>\n",
       "      <td>91</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.531798</td>\n",
       "      <td>3.660383</td>\n",
       "      <td>3.674417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">9</th>\n",
       "      <th>0</th>\n",
       "      <td>SER</td>\n",
       "      <td>92</td>\n",
       "      <td>A</td>\n",
       "      <td>False</td>\n",
       "      <td>7.474844</td>\n",
       "      <td>3.668310</td>\n",
       "      <td>3.709854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SER</td>\n",
       "      <td>92</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>7.587125</td>\n",
       "      <td>3.660643</td>\n",
       "      <td>3.693908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SER</td>\n",
       "      <td>92</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.632944</td>\n",
       "      <td>3.671030</td>\n",
       "      <td>3.623409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SER</td>\n",
       "      <td>92</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.506989</td>\n",
       "      <td>3.658281</td>\n",
       "      <td>3.731073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">10</th>\n",
       "      <th>0</th>\n",
       "      <td>THR</td>\n",
       "      <td>93</td>\n",
       "      <td>A</td>\n",
       "      <td>False</td>\n",
       "      <td>7.402265</td>\n",
       "      <td>3.687230</td>\n",
       "      <td>3.616123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>THR</td>\n",
       "      <td>93</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>7.500638</td>\n",
       "      <td>3.662270</td>\n",
       "      <td>3.672518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>THR</td>\n",
       "      <td>93</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>7.604820</td>\n",
       "      <td>3.661331</td>\n",
       "      <td>3.602152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>THR</td>\n",
       "      <td>93</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>7.432345</td>\n",
       "      <td>3.669773</td>\n",
       "      <td>3.715579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">11</th>\n",
       "      <th>0</th>\n",
       "      <td>LEU</td>\n",
       "      <td>94</td>\n",
       "      <td>A</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LEU</td>\n",
       "      <td>94</td>\n",
       "      <td>B</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LEU</td>\n",
       "      <td>94</td>\n",
       "      <td>C</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LEU</td>\n",
       "      <td>94</td>\n",
       "      <td>D</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            res_name  res_number chain_name  chain_ap    radius         P  \\\n",
       "layer chain                                                                 \n",
       "0     0          LEU          83          A     False       NaN       NaN   \n",
       "      1          LEU          83          B     False       NaN       NaN   \n",
       "      2          LEU          83          C     False       NaN       NaN   \n",
       "      3          LEU          83          D     False       NaN       NaN   \n",
       "1     0          PRO          84          A     False  7.722204  3.649544   \n",
       "      1          PRO          84          B     False  7.741549  3.654085   \n",
       "      2          PRO          84          C     False  7.900789  3.644428   \n",
       "      3          PRO          84          D     False  7.737620  3.657901   \n",
       "2     0          LEU          85          A     False  7.676671  3.640626   \n",
       "      1          LEU          85          B     False  7.763567  3.659496   \n",
       "      2          LEU          85          C     False  7.891293  3.647823   \n",
       "      3          LEU          85          D     False  7.655243  3.642792   \n",
       "3     0          GLN          86          A     False  7.702822  3.635028   \n",
       "      1          GLN          86          B     False  7.764489  3.662547   \n",
       "      2          GLN          86          C     False  7.905324  3.651146   \n",
       "      3          GLN          86          D     False  7.633406  3.631901   \n",
       "4     0          LEU          87          A     False  7.701939  3.639101   \n",
       "      1          LEU          87          B     False  7.787281  3.662848   \n",
       "      2          LEU          87          C     False  7.934494  3.650698   \n",
       "      3          LEU          87          D     False  7.599870  3.643559   \n",
       "5     0          ASP          88          A     False  7.716392  3.638150   \n",
       "      1          ASP          88          B     False  7.796716  3.657196   \n",
       "      2          ASP          88          C     False  7.900749  3.655130   \n",
       "      3          ASP          88          D     False  7.558544  3.644225   \n",
       "6     0          THR          89          A     False  7.681119  3.644050   \n",
       "      1          THR          89          B     False  7.788975  3.648330   \n",
       "      2          THR          89          C     False  7.890719  3.649954   \n",
       "      3          THR          89          D     False  7.565168  3.647419   \n",
       "7     0          LEU          90          A     False  7.604975  3.655490   \n",
       "      1          LEU          90          B     False  7.743872  3.647420   \n",
       "      2          LEU          90          C     False  7.822314  3.657222   \n",
       "      3          LEU          90          D     False  7.461780  3.665765   \n",
       "8     0          GLU          91          A     False  7.576451  3.654418   \n",
       "      1          GLU          91          B     False  7.661929  3.653039   \n",
       "      2          GLU          91          C     False  7.692617  3.677681   \n",
       "      3          GLU          91          D     False  7.531798  3.660383   \n",
       "9     0          SER          92          A     False  7.474844  3.668310   \n",
       "      1          SER          92          B     False  7.587125  3.660643   \n",
       "      2          SER          92          C     False  7.632944  3.671030   \n",
       "      3          SER          92          D     False  7.506989  3.658281   \n",
       "10    0          THR          93          A     False  7.402265  3.687230   \n",
       "      1          THR          93          B     False  7.500638  3.662270   \n",
       "      2          THR          93          C     False  7.604820  3.661331   \n",
       "      3          THR          93          D     False  7.432345  3.669773   \n",
       "11    0          LEU          94          A     False       NaN       NaN   \n",
       "      1          LEU          94          B     False       NaN       NaN   \n",
       "      2          LEU          94          C     False       NaN       NaN   \n",
       "      3          LEU          94          D     False       NaN       NaN   \n",
       "\n",
       "                    p  \n",
       "layer chain            \n",
       "0     0           NaN  \n",
       "      1           NaN  \n",
       "      2           NaN  \n",
       "      3           NaN  \n",
       "1     0      3.548694  \n",
       "      1      3.646930  \n",
       "      2      3.567009  \n",
       "      3      3.494544  \n",
       "2     0      3.582121  \n",
       "      1      3.609481  \n",
       "      2      3.605697  \n",
       "      3      3.562106  \n",
       "3     0      3.640281  \n",
       "      1      3.581246  \n",
       "      2      3.624244  \n",
       "      3      3.640820  \n",
       "4     0      3.629298  \n",
       "      1      3.592058  \n",
       "      2      3.642253  \n",
       "      3      3.624172  \n",
       "5     0      3.624391  \n",
       "      1      3.614704  \n",
       "      2      3.608444  \n",
       "      3      3.659191  \n",
       "6     0      3.651458  \n",
       "      1      3.659564  \n",
       "      2      3.570419  \n",
       "      3      3.638641  \n",
       "7     0      3.631477  \n",
       "      1      3.618760  \n",
       "      2      3.656269  \n",
       "      3      3.582190  \n",
       "8     0      3.709208  \n",
       "      1      3.633819  \n",
       "      2      3.677449  \n",
       "      3      3.674417  \n",
       "9     0      3.709854  \n",
       "      1      3.693908  \n",
       "      2      3.623409  \n",
       "      3      3.731073  \n",
       "10    0      3.616123  \n",
       "      1      3.672518  \n",
       "      2      3.602152  \n",
       "      3      3.715579  \n",
       "11    0           NaN  \n",
       "      1           NaN  \n",
       "      2           NaN  \n",
       "      3           NaN  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bundle_dfs['11']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first domain spans residues 61-72, whereas the second 83-94, but what's is happening between them?\n",
    "\n",
    "Once we know domain boundaries and layers, we can force SamCC-Turbo to measure also the missing part (i.e, to measure the whole region as it is were a single coiled coil).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "bundle = bundleClass()\n",
    "\n",
    "# we use `defdata` to define the boundaries of this big domain\n",
    "defdata = [[range(61, 95), range(61, 95), range(61, 95), range(61, 95)], # residue ranges\n",
    "           ['A', 'B', 'C', 'D'], # PDB chains ordered as in the bundle\n",
    "           [False, False, False, False], # no anti-parallel helices\n",
    "           ['x', 'x', 'x', 'x']] # no hepatd register definition\n",
    "\n",
    "bundle.from_defdata(pdbpath, *defdata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now, we do measurements for the whole region:\n",
    "bundle.calc_bundleaxis() \n",
    "bundle.calc_radius() \n",
    "bundle.calc_periodicity() \n",
    "big_bundle_df = bundle.gendf() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='layer'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ... and plot the helical periodicity (averaged per layer):\n",
    "p_mean = big_bundle_df.p.mean(level=0)\n",
    "p_mean.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The helices of the two coiled-coil segments adopt a canonical periodicity of ~3.63 residues per turn. However, in the linker region, the helical periodicity increases to almost 5 residues per turn, a value characteristic for pi-helices. That's the reason why it was not detected by SOCKET (presumably due to the lack of knobs-into-holes interactions)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "helical periodicity of bundle #1 3.61 res/turn -> alpha helix\n",
      "helical periodicity of bundle #2 3.63 res/turn -> alpha helix\n",
      "\n",
      "helical periodicity of the linker 4.27 res/turn -> pi helix\n"
     ]
    }
   ],
   "source": [
    "print (f'helical periodicity of bundle #1 {p_mean[:17].mean().round(2)} res/turn -> alpha helix')\n",
    "print (f'helical periodicity of bundle #2 {p_mean[23:].mean().round(2)} res/turn -> alpha helix')\n",
    "print (f'\\nhelical periodicity of the linker {p_mean[17:23].mean().round(2)} res/turn -> pi helix')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take a look at the structure again to localize the pi-helical linker: <a href=\"https://www.rcsb.org/3d-view/3TSI\" target=\"_blank\">3D view at PDB</a>\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='layer'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's investigate the periodicity of the bundle (i.e., supercoiling of the helices):\n",
    "P_mean = big_bundle_df.P.mean(level=0)\n",
    "P_mean.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "periodicity of bundle #1 3.52 res/turn -> canonical 7/2 coiled coil\n",
      "periodicity of bundle #2 3.66 res/turn -> non-canonical 11/3 coiled coil\n"
     ]
    }
   ],
   "source": [
    "print (f'periodicity of bundle #1 {P_mean[:17].mean().round(2)} res/turn -> canonical 7/2 coiled coil')\n",
    "print (f'periodicity of bundle #2 {P_mean[23:].mean().round(2)} res/turn -> non-canonical 11/3 coiled coil')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The 3tsi structure comprises two coiled-coil regions of different periodicities. The first N-terminal domain is a canonical left-handed coiled-coil (7/2=3.5 periodicity), whereas in the second C-terminal, the helices are straight and display only subtle right-handed supercoiling (the difference between bundle periodicity, 3.64, and the periodicity of a regular alpha helix, 3.63, is very small)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below we will investigate the core packing of the first domain. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "with bundles[0] as b:\n",
    "    b.calc_crick() # calculates the Circk angle for each residue in the bundle\n",
    "    b.calc_crickdev(3.5, 7, optimal_ph1=19.5) # calculates the difference between the observed Crick angles \n",
    "    # (see above) and expected for an ideal bundle of a given periodicity. The `optimal_ph1` defines\n",
    "    # the reference rotation state of the helices (see also https://pubmed.ncbi.nlm.nih.gov/20139000/)\n",
    "    # defined based on many parallel tetrameric structures.\n",
    "    bundle_dfs[b.socket_cc_id] = b.gendf() # update data frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-26.0, 26.0)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This result indicates the core packing of the first domain is fairly canonical (so-called a-d packing)\n",
    "# (the difference between the observed orientation of the side-chain and one expected for an ideal bundle\n",
    "# is close to zero)\n",
    "ax=bundle_dfs['10'].crdev.mean(level=0).plot()\n",
    "ax.set_ylim(-26, 26)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# To be continued!\n",
    "If you have any questions or comments, do not hesitate to [contact us](mailto:s.dunin-horkawicz@cent.uw.edu.pl?subject=[SamCC-Turbo])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
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}