{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "*This notebook contains material from [PyRosetta](https://RosettaCommons.github.io/PyRosetta.notebooks);\n", "content is available [on Github](https://github.com/RosettaCommons/PyRosetta.notebooks.git).*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [Global Ligand Docking using `XMLObjects` Using the `ref2015.wts` Scorefunction](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/08.01-Ligand-Docking-XMLObjects.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Loop Modeling](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/09.00-Loop-Modeling.ipynb) >

\"Open" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# `GALigandDock` Protocol with `pyrosetta.distributed` Using the `beta_cart.wts` Scorefunction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*Warning*: This notebook uses `pyrosetta.distributed.viewer` code, which runs in `jupyter notebook` and might not run if you're using `jupyterlab`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*Note:* This Jupyter notebook requires the PyRosetta distributed layer. Please make sure to activate the `PyRosetta.notebooks` conda environment before running this notebook. The kernel is set to use this environment. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import logging\n", "logging.basicConfig(level=logging.INFO)\n", "import matplotlib\n", "%matplotlib inline\n", "import os\n", "import pandas as pd\n", "import pyrosetta\n", "import pyrosetta.distributed\n", "import pyrosetta.distributed.io as io\n", "import pyrosetta.distributed.viewer as viewer\n", "import pyrosetta.distributed.packed_pose as packed_pose\n", "import pyrosetta.distributed.tasks.rosetta_scripts as rosetta_scripts\n", "import seaborn\n", "seaborn.set()\n", "import sys\n", "\n", "!pip install pyrosettacolabsetup\n", "import pyrosettacolabsetup; pyrosettacolabsetup.install_pyrosetta()\n", "import pyrosetta\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load the `TPA.am1-bcc.gp.params` file when using the `-beta_cart` flag, which has `gen_potential` atom typing and AM1-BCC partial charges:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:pyrosetta.distributed:maybe_init performing pyrosetta initialization: {'extra_options': '-ignore_unrecognized_res 1 -extra_res_fa inputs/TPA.am1-bcc.gp.params -beta_cart -out:level 200', 'silent': True}\n", "INFO:pyrosetta.rosetta:Found rosetta database at: /mnt/home/klimaj/git/Rosetta/main/source/src/python/PyRosetta/src/pyrosetta/database; using it....\n", "INFO:pyrosetta.rosetta:PyRosetta-4 2019 [Rosetta PyRosetta4.conda.linux.CentOS.python36.Release 2019.39+release.93456a567a8125cafdf7f8cb44400bc20b570d81 2019-09-26T14:24:44] retrieved from: http://www.pyrosetta.org\n", "(C) Copyright Rosetta Commons Member Institutions. Created in JHU by Sergey Lyskov and PyRosetta Team.\n", "INFO:rosetta:core.init.score_function_corrections: {0} [ WARNING ] Flag -beta_nov16 is set but -weights are also specified. Not changing input weights file!\n", "INFO:rosetta:core.io.pose_from_sfr.PoseFromSFRBuilder: {0} [ WARNING ] TPA337 has an unfavorable ring conformation; the coordinates for this input structure may have been poorly assigned.\n" ] } ], "source": [ "pdb_filename = \"inputs/test_lig.pdb\"\n", "ligand_params = \"inputs/TPA.am1-bcc.gp.params\"\n", "flags = f\"\"\"\n", "-ignore_unrecognized_res 1\n", "-extra_res_fa {ligand_params}\n", "-beta_cart\n", "-out:level 200\n", "\"\"\"\n", "pyrosetta.distributed.init(flags)\n", "pose_obj = io.pose_from_file(filename=pdb_filename)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we change the scorefunction in our RosettaScripts script to `beta_cart.wts`, the weights of which were optimized on protein-ligand complexes using ligands with AM1-BCC partial charges generated with Amber's `antechamber`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`GALigandDock` within RosettaScripts normally outputs multiple `.pdb` files to disk if run by the command line. However, when using the `MultioutputRosettaScriptsTask` function in `pyrosetta.distributed`, the outputs will be captured in memory within this Jupyter session!" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO:rosetta:core.io.pose_from_sfr.PoseFromSFRBuilder: {0} [ WARNING ] TPA337 has an unfavorable ring conformation; the coordinates for this input structure may have been poorly assigned.\n" ] } ], "source": [ "xml = f\"\"\"\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "\"\"\"\n", "xml_obj = rosetta_scripts.MultioutputRosettaScriptsTask(xml)\n", "xml_obj.setup()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`MultioutputRosettaScriptsTask` is a python generator object. Therefore, we need to call `list()` or `set()` on it to run it.\n", "\n", "*Warning*, the following cell runs for ~45 minutes CPU time." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "if not os.getenv(\"DEBUG\"):\n", " %time results = list(xml_obj(pose_obj))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Inspect the scores for the `GALigandDock` trajectories:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "

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50 rows × 30 columns

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" ], "text/plain": [ " cart_bonded dslf_fa13 fa_atr fa_dun_dev fa_dun_rot fa_dun_semi \\\n", "0 1123.712502 0.0 -2151.762324 2073.947599 351.670653 526.462836 \n", "1 1126.994362 0.0 -2153.494398 2074.354803 350.045712 527.638427 \n", "2 1122.218749 0.0 -2152.061341 2074.616276 352.358914 528.828818 \n", "3 1124.089966 0.0 -2152.510428 2074.255528 352.854664 526.668672 \n", "4 1127.329477 0.0 -2144.634818 2074.065162 353.115713 528.590003 \n", "5 1119.868142 0.0 -2135.739776 2073.996665 353.098796 528.725083 \n", "6 1119.054847 0.0 -2128.180817 2074.125675 354.267620 527.658626 \n", "7 1118.147392 0.0 -2120.681500 2073.846102 354.157516 527.871629 \n", "8 1117.748559 0.0 -2123.042805 2074.240598 354.436350 528.611581 \n", "9 1122.056963 0.0 -2148.039319 2074.745640 352.344596 529.868373 \n", "10 1117.741151 0.0 -2121.369976 2074.302515 354.174154 527.791725 \n", "11 1119.795446 0.0 -2117.973995 2074.530476 354.559199 527.338329 \n", "12 1118.312826 0.0 -2114.047445 2073.902282 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2074.762505 353.521146 527.725522 \n", "27 1117.264440 0.0 -2117.967615 2073.920889 352.837101 527.984058 \n", "28 1117.192046 0.0 -2116.088396 2074.109505 354.226898 527.758834 \n", "29 1115.740407 0.0 -2121.220723 2073.950516 354.180802 527.823457 \n", "30 1118.176537 0.0 -2118.976859 2074.091208 354.235640 527.771483 \n", "31 1117.720868 0.0 -2117.913073 2073.964761 354.143081 527.906426 \n", "32 1120.610165 0.0 -2120.058676 2074.137857 354.221243 526.489176 \n", "33 1116.528835 0.0 -2114.868437 2073.857444 354.169507 527.771740 \n", "34 1118.887136 0.0 -2119.543055 2074.126521 353.328521 528.791448 \n", "35 1117.173583 0.0 -2116.769462 2074.056933 354.164934 527.351801 \n", "36 1118.897286 0.0 -2123.904734 2073.872455 354.384303 527.646746 \n", "37 1126.205813 0.0 -2152.142984 2074.917354 353.307715 528.107170 \n", "38 1116.328492 0.0 -2117.094750 2073.901394 354.204171 527.850793 \n", "39 1118.472471 0.0 -2118.173586 2073.906513 354.093842 527.694559 \n", "40 1122.074279 0.0 -2120.153906 2074.046413 354.141093 527.769415 \n", "41 1120.563660 0.0 -2122.478336 2074.408840 354.076905 527.893912 \n", "42 1122.183065 0.0 -2134.140192 2074.061703 354.273227 527.587301 \n", "43 1121.896046 0.0 -2122.725356 2073.888454 354.339331 528.732720 \n", "44 1120.136109 0.0 -2129.790646 2074.069462 354.917341 527.542480 \n", "45 1119.679063 0.0 -2134.665902 2073.996940 355.192983 527.415419 \n", "46 1118.074433 0.0 -2113.160467 2074.074668 353.120830 526.287474 \n", "47 1117.514275 0.0 -2115.978997 2074.329427 353.768894 526.949539 \n", "48 1116.978234 0.0 -2125.072550 2074.670339 353.297882 528.306793 \n", "49 1122.186473 0.0 -2141.044482 2074.397811 354.212538 527.553732 \n", "\n", " fa_elec fa_intra_atr_xover4 fa_intra_elec fa_intra_rep_xover4 \\\n", "0 -608.942522 -152.925958 -91.709467 484.474982 \n", "1 -598.326113 -155.611156 -95.374631 487.259466 \n", "2 -592.915774 -152.872453 -94.779139 484.857347 \n", "3 -594.728864 -154.667979 -91.274751 484.674904 \n", "4 -591.697767 -157.057321 -99.639525 488.113252 \n", "5 -585.912100 -153.333212 -95.675236 484.059834 \n", "6 -600.190559 -152.753968 -93.492140 484.075625 \n", "7 -589.804841 -153.593008 -94.975244 485.339630 \n", "8 -590.876958 -153.665083 -94.331011 485.674473 \n", "9 -594.182910 -153.210177 -92.399237 484.908058 \n", "10 -590.241078 -153.597633 -95.827353 484.667353 \n", "11 -589.618991 -152.679052 -94.486570 483.735919 \n", "12 -582.787032 -155.366733 -95.968917 484.953600 \n", "13 -590.049904 -153.449984 -93.513722 484.159308 \n", "14 -592.217546 -152.449089 -94.956140 484.107818 \n", "15 -589.463209 -154.153409 -96.869409 485.552224 \n", "16 -588.314086 -153.611090 -95.320298 485.147909 \n", "17 -582.793771 -152.797945 -94.676084 484.698239 \n", "18 -588.721658 -153.256935 -95.684619 484.856754 \n", "19 -598.362623 -153.919304 -92.398482 483.048769 \n", "20 -600.943325 -153.540042 -92.812196 485.343720 \n", "21 -586.305973 -154.254092 -91.845749 485.066702 \n", "22 -587.750200 -153.653116 -95.974025 484.157755 \n", "23 -588.315750 -153.221795 -92.867507 483.416645 \n", "24 -598.458861 -152.784966 -94.281443 484.558852 \n", "25 -583.333339 -153.362764 -94.510391 484.397750 \n", "26 -583.715146 -153.625307 -92.616395 484.624171 \n", "27 -583.429823 -153.081684 -96.927710 484.420431 \n", "28 -587.301089 -153.499639 -94.926420 484.217262 \n", "29 -584.729707 -153.132527 -92.970132 484.788703 \n", "30 -591.733103 -153.193661 -94.015077 484.421670 \n", "31 -589.163726 -152.904905 -94.489469 484.573393 \n", "32 -589.280668 -153.848764 -91.706236 484.522268 \n", "33 -587.077078 -153.825286 -93.215278 484.916617 \n", "34 -584.198246 -153.874909 -96.050302 484.634286 \n", "35 -584.333500 -153.785952 -92.757097 483.602991 \n", "36 -590.495957 -154.263097 -95.314800 484.645354 \n", "37 -582.578905 -154.116226 -95.336262 487.068420 \n", "38 -590.565227 -152.014204 -94.162300 483.845064 \n", "39 -579.597896 -153.772378 -94.421606 484.157218 \n", "40 -586.209890 -155.410559 -94.022582 485.814683 \n", "41 -589.536028 -153.098357 -94.206318 484.609542 \n", "42 -594.595432 -153.088345 -94.107961 483.686954 \n", "43 -582.161860 -153.748085 -93.864669 485.063471 \n", "44 -586.778335 -153.076268 -95.400060 484.850197 \n", "45 -593.001728 -153.120848 -94.091495 484.763015 \n", "46 -586.075877 -153.679664 -93.415569 483.843130 \n", "47 -575.206892 -153.425757 -96.710046 486.046957 \n", "48 -587.755445 -152.715260 -95.858052 483.961905 \n", "49 -589.354853 -154.016633 -94.162834 485.014271 \n", "\n", " ... lk_ball lk_ball_bridge lk_ball_bridge_uncpl \\\n", "0 ... 914.974515 8.028863 56.938398 \n", "1 ... 912.676585 8.185741 57.137773 \n", "2 ... 911.937969 8.482099 59.081443 \n", "3 ... 911.669956 8.161121 56.862517 \n", "4 ... 911.687657 8.390250 59.421205 \n", "5 ... 904.758285 8.352889 59.583429 \n", "6 ... 910.301829 8.267338 58.256741 \n", "7 ... 901.078625 8.301181 57.906715 \n", "8 ... 902.906292 8.220858 58.551026 \n", "9 ... 914.566198 7.920984 55.527792 \n", "10 ... 902.542067 8.345890 58.585494 \n", "11 ... 900.964799 8.310695 59.028378 \n", "12 ... 897.209214 8.592110 60.281273 \n", "13 ... 901.034141 8.282241 58.387106 \n", "14 ... 904.939033 8.292054 58.087667 \n", "15 ... 900.635260 8.353362 58.863490 \n", "16 ... 900.851984 8.401965 58.705711 \n", "17 ... 899.264890 8.385106 58.834187 \n", "18 ... 902.384370 8.368650 58.995883 \n", "19 ... 908.434224 8.123019 56.443615 \n", "20 ... 908.716709 8.092196 56.262864 \n", "21 ... 899.245585 8.394896 59.021236 \n", "22 ... 900.967950 8.426505 59.073716 \n", "23 ... 899.084521 8.246251 57.568979 \n", "24 ... 907.877157 8.220266 57.625948 \n", "25 ... 899.917327 8.269664 58.201673 \n", "26 ... 899.566101 8.234914 57.339780 \n", "27 ... 900.899472 8.364630 59.048445 \n", "28 ... 900.514420 8.324491 58.216448 \n", "29 ... 901.835244 8.304383 58.752266 \n", "30 ... 905.297959 8.225279 57.791513 \n", "31 ... 901.256252 8.229592 56.822766 \n", "32 ... 902.329492 8.334486 58.820247 \n", "33 ... 899.883852 8.286588 57.875725 \n", "34 ... 899.690522 8.214202 57.495022 \n", "35 ... 899.034577 8.332849 58.410754 \n", "36 ... 906.082402 8.268748 56.961587 \n", "37 ... 909.171597 8.781040 62.662417 \n", "38 ... 903.492147 8.190625 56.990750 \n", "39 ... 899.414054 8.320370 58.245026 \n", "40 ... 901.952444 8.477702 58.843519 \n", "41 ... 905.121053 8.361940 59.220623 \n", "42 ... 910.903751 8.118174 56.584244 \n", "43 ... 900.362161 8.190309 56.311753 \n", "44 ... 906.779590 8.362696 57.329232 \n", "45 ... 910.660655 8.068935 56.222138 \n", "46 ... 900.288128 8.436855 59.436842 \n", "47 ... 896.743939 8.183895 56.891607 \n", "48 ... 905.459894 8.162587 56.287570 \n", "49 ... 911.224885 8.216895 57.795436 \n", "\n", " lk_ball_iso omega p_aa_pp \\\n", "0 2237.073939 3.205810 -84.787860 \n", "1 2236.078391 2.616802 -84.905751 \n", "2 2234.873025 2.785344 -84.712778 \n", "3 2235.493136 2.689288 -84.570622 \n", "4 2230.112093 3.098268 -84.642988 \n", "5 2222.677958 2.782730 -84.397516 \n", "6 2225.289996 2.463544 -83.967544 \n", "7 2210.271834 2.188813 -84.127671 \n", "8 2216.794578 2.357257 -84.155674 \n", "9 2237.359424 2.137919 -84.688511 \n", "10 2213.451888 2.415969 -83.917844 \n", "11 2209.505589 2.363121 -83.626671 \n", "12 2205.347438 2.395891 -83.962223 \n", "13 2209.445302 2.383612 -83.789749 \n", "14 2215.458503 2.156304 -83.943825 \n", "15 2208.448162 2.554803 -84.106625 \n", "16 2208.861342 2.298621 -83.990494 \n", "17 2207.193408 2.493420 -84.059707 \n", "18 2213.820288 2.424769 -83.954573 \n", "19 2226.746092 2.195113 -84.087127 \n", "20 2225.237135 1.934896 -84.138227 \n", "21 2208.290013 2.226094 -83.855202 \n", "22 2211.663744 2.362630 -83.991207 \n", "23 2207.411666 2.362959 -83.992033 \n", "24 2221.312457 2.273240 -84.084665 \n", "25 2209.080229 2.580138 -83.971134 \n", "26 2205.439602 2.335625 -83.754730 \n", "27 2209.367978 2.274618 -83.939094 \n", "28 2209.462522 2.235938 -84.040372 \n", "29 2213.783240 2.400138 -84.022702 \n", "30 2214.322574 2.560843 -83.994720 \n", "31 2210.611495 2.201650 -84.126880 \n", "32 2210.819610 2.267812 -84.308570 \n", "33 2207.725086 2.314438 -84.073244 \n", "34 2208.838554 2.626603 -84.212765 \n", "35 2206.737206 2.301316 -83.816302 \n", "36 2218.768584 2.820835 -84.201293 \n", "37 2237.343204 3.504083 -84.192562 \n", "38 2212.085955 2.336527 -84.112099 \n", "39 2209.080366 2.185829 -84.037889 \n", "40 2213.276321 2.649365 -83.926852 \n", "41 2216.119579 2.268016 -83.997958 \n", "42 2230.277951 2.311996 -84.196198 \n", "43 2211.958350 2.368035 -84.045210 \n", "44 2225.100940 3.163210 -84.006384 \n", "45 2229.244793 2.515460 -84.164875 \n", "46 2207.194812 2.567297 -83.991158 \n", "47 2205.048713 2.446659 -83.981252 \n", "48 2220.501922 2.741407 -84.342385 \n", "49 2234.960243 2.454796 -84.284048 \n", "\n", " pickled_pose rama_prepro ref \\\n", "0 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 338.665837 -83.04488 \n", "1 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 338.066308 -83.04488 \n", "2 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 338.017765 -83.04488 \n", "3 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 338.948903 -83.04488 \n", "4 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 339.732965 -83.04488 \n", "5 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 339.262489 -83.04488 \n", "6 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.339600 -83.04488 \n", "7 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.763695 -83.04488 \n", "8 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 339.664206 -83.04488 \n", "9 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 339.407441 -83.04488 \n", "10 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.436524 -83.04488 \n", "11 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 341.958594 -83.04488 \n", "12 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.457713 -83.04488 \n", "13 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.885252 -83.04488 \n", "14 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.712217 -83.04488 \n", "15 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.456327 -83.04488 \n", "16 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.444064 -83.04488 \n", "17 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.345752 -83.04488 \n", "18 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.770906 -83.04488 \n", "19 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.751774 -83.04488 \n", "20 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.643492 -83.04488 \n", "21 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.857928 -83.04488 \n", "22 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.408618 -83.04488 \n", "23 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.335161 -83.04488 \n", "24 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.841184 -83.04488 \n", "25 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.407423 -83.04488 \n", "26 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 341.944039 -83.04488 \n", "27 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.668094 -83.04488 \n", "28 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.500974 -83.04488 \n", "29 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.452932 -83.04488 \n", "30 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.584211 -83.04488 \n", "31 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.613090 -83.04488 \n", "32 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.590574 -83.04488 \n", "33 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.429989 -83.04488 \n", "34 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 339.517557 -83.04488 \n", "35 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.539722 -83.04488 \n", "36 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.705109 -83.04488 \n", "37 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 337.419080 -83.04488 \n", "38 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.552713 -83.04488 \n", "39 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.548692 -83.04488 \n", "40 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.441443 -83.04488 \n", "41 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.609626 -83.04488 \n", "42 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 341.194660 -83.04488 \n", "43 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 339.576207 -83.04488 \n", "44 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.155735 -83.04488 \n", "45 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.078616 -83.04488 \n", "46 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 340.728354 -83.04488 \n", "47 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 341.310476 -83.04488 \n", "48 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 338.792190 -83.04488 \n", "49 gANjcHlyb3NldHRhLnJvc2V0dGEuY29yZS5wb3NlClBvc2... 341.233187 -83.04488 \n", "\n", " total_score \n", "0 2146.657901 \n", "1 2154.465790 \n", "2 2160.068530 \n", "3 2168.046714 \n", "4 2171.305626 \n", "5 2174.354305 \n", "6 2175.892215 \n", "7 2176.467254 \n", "8 2176.841510 \n", "9 2176.972496 \n", "10 2177.730121 \n", "11 2178.204123 \n", "12 2178.866416 \n", "13 2179.058794 \n", "14 2180.117049 \n", "15 2180.583104 \n", "16 2180.631216 \n", "17 2180.725153 \n", "18 2180.847581 \n", "19 2180.751217 \n", "20 2180.879864 \n", "21 2181.324150 \n", "22 2181.401864 \n", "23 2181.440088 \n", "24 2181.525400 \n", "25 2181.759201 \n", "26 2181.829008 \n", "27 2181.989318 \n", "28 2181.941843 \n", "29 2181.977075 \n", "30 2182.044673 \n", "31 2182.105762 \n", "32 2182.142107 \n", "33 2182.435992 \n", "34 2182.829516 \n", "35 2182.715754 \n", "36 2183.402096 \n", "37 2182.847308 \n", "38 2183.796557 \n", "39 2183.988985 \n", "40 2184.389649 \n", "41 2184.355960 \n", "42 2184.470170 \n", "43 2185.656786 \n", "44 2186.132616 \n", "45 2185.720084 \n", "46 2186.292344 \n", "47 2186.556645 \n", "48 2186.276192 \n", "49 2189.951239 \n", "\n", "[50 rows x 30 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "if not os.getenv(\"DEBUG\"):\n", " df = pd.DataFrame.from_records(packed_pose.to_dict(results))\n", " df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Now that we have performed `GALigandDock`, we can plot the ligand binding energy landscape:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "if not os.getenv(\"DEBUG\"):\n", " matplotlib.rcParams[\"figure.figsize\"] = [12.0, 8.0]\n", " seaborn.scatterplot(x=\"lig_rms\", y=\"total_score\", data=df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's look at the ligand dock with the lowest `total_score` score!" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "application/3dmoljs_load.v0": "
\n

You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n jupyter labextension install jupyterlab_3dmol

\n
\n", "text/html": [ "
\n", "

You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n", " jupyter labextension install jupyterlab_3dmol

\n", "
\n", "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "if not os.getenv(\"DEBUG\"):\n", " ppose_lowest_total_score = results[df.sort_values(by=\"total_score\").index[0]]\n", " view = viewer.init(ppose_lowest_total_score)\n", " view.add(viewer.setStyle())\n", " view.add(viewer.setStyle(command=({\"hetflag\": True}, {\"stick\": {\"colorscheme\": \"brownCarbon\", \"radius\": 0.2}})))\n", " view.add(viewer.setSurface(residue_selector=pyrosetta.rosetta.core.select.residue_selector.ChainSelector(\"E\"), opacity=0.7, color='white'))\n", " view.add(viewer.setHydrogenBonds())\n", " view()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [Global Ligand Docking using `XMLObjects` Using the `ref2015.wts` Scorefunction](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/08.01-Ligand-Docking-XMLObjects.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Loop Modeling](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/09.00-Loop-Modeling.ipynb) >

\"Open" ] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:PyRosetta.notebooks] *", "language": "python", "name": "conda-env-PyRosetta.notebooks-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }