{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "*This notebook contains material from [PyRosetta](https://RosettaCommons.github.io/PyRosetta);\n", "content is available [on Github](https://github.com/RosettaCommons/PyRosetta.notebooks.git).*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [*De Novo* Protein Design with PyRosetta](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/06.07-Introduction-to-DeNovo-protein-design.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Fast Fourier Transform Based Docking via ZDOCK](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/07.01-Fast-Fourier-Transform-Based-Docking-via-ZDOCK.ipynb) >

\"Open" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Docking\n", "\n", "\n", "Protein–protein docking is the prediction of a complex structure starting from its monomer components. The search space can be extremely large, so large amounts of computational resources are typically required. In this workshop, we will explore several of the techniques briefly; keep in mind that for real applications, many more decoys will need to be tested.\n", "\n", "\n", "### Suggested Readings\n", "\n", "\n", "- J. J. Gray et al., “Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations,” *J. Mol. Biol.* 331, 281-299 (2003).\n", "\n", "\n", "- S. Chaudhury & J. J. Gray, “Conformer selection and induced fit in flexible backbone protein-protein docking using computational and NMR ensembles,” *J. Mol. Biol.* 381, 1068-1087 (2008).\n", "\n", "\n", "\n", "### Appendix D: \n", "Running PyRosetta on a Cluster includes more helpful information about using the `PyJobDistributor` to distribute jobs over multiple computers." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [*De Novo* Protein Design with PyRosetta](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/06.07-Introduction-to-DeNovo-protein-design.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Fast Fourier Transform Based Docking via ZDOCK](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/07.01-Fast-Fourier-Transform-Based-Docking-via-ZDOCK.ipynb) >

\"Open" ] } ], "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": "3.6.0" }, "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 }