{ "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", "< [Refinement Protocol](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/05.02-Refinement-Protocol.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Side Chain Conformations and Dunbrack Energies](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/06.01-Side-Chain-Conformations-and-Dunbrack-Energies.ipynb) >

\"Open" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Packing & Design\n", "\n", "Rosetta uses a Monte Carlo optimization routine to pack side chains using a library of conformations, or rotamers. This operation can be used for side-chain packing for operations like refinement or for designing optimal sequences. This workshop will examine both capabilities.\n", "\n", "We will also cover many more ways to do protein design within Rosetta including parametric, denovo, and hydrogen-bond based design. All of these can be useful tools for protein engineering. \n", "\n", "### Suggested readings\n", "1. J. Desmet et al., “The dead-end elimination theorem and its use in protein side-chain positioning,” *Nature* 356, 539-543 (1992).\n", "2. B. Kuhlman & D. Baker, “Native protein structures are close to optimal for their structures,” *PNAS* 97, 10383, 2000.\n", "3. Denovo paper\n", "4. HbNet\n", "5. Andrew's packing paper\n", "6. Denovo design\n", "7. Parametric design paper" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Chapter contributors:**\n", "\n", "- Jared Adolf-Bryfogle (Scripps; Institute for Protein Innovation)\n", "- Jason C. Klima (University of Washington; Lyell Immunopharma)\n", "- Jack Maguire (University of North Carolina)\n", "- Kathy Le (Johns Hopkins University); parts of this chapter were adapted from the [PyRosetta book](https://www.amazon.com/PyRosetta-Interactive-Platform-Structure-Prediction-ebook/dp/B01N21DRY8) (J. J. Gray, S. Chaudhury, S. Lyskov, J. Labonte)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [Refinement Protocol](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/05.02-Refinement-Protocol.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Side Chain Conformations and Dunbrack Energies](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/06.01-Side-Chain-Conformations-and-Dunbrack-Energies.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": "3.6.1" }, "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 }