{ "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", "< [Low-Res Scoring and Fragments](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/04.02-Low-Res-Scoring-and-Fragments.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [High-Resolution Movers](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/05.01-High-Res-Movers.ipynb) >

\"Open" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Structure Refinement" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "One of the most basic operations in protein structure and design algorithms is manipulation of the protein conformation. In Rosetta, these manipulations are organized into movers. A `Mover` object simply changes the conformation of a given pose. It can be simple, like a single φ or ψ angle change, or complex, like an entire refinement protocol.\n", "\n", "## Suggested Reading\n", "- P. Bradley, K. M. S. Misura & D. Baker, “Toward high-resolution de novo structure prediction for small proteins,” Science 309, 1868-1871 (2005), including Supplementary Material.\n", "- Z. Li & H. A. Scheraga, “Monte Carlo-minimization approach to the multiple-minima problem in protein folding,” Proc. Natl. Acad. Sci. USA 84, 6611-6615 (1987).\n", "\n", "## PyRosetta Workshop 5 Link\n", "https://graylab.jhu.edu/pyrosetta/downloads/documentation/pyrosetta4_online_format/PyRosetta4_Workshop5_StructureRefinement.pdf\n", "\n", "## Appendix A Link\n", "https://graylab.jhu.edu/pyrosetta/downloads/documentation/pyrosetta4_online_format/PyRosetta4_Workshops_Appendix_A.pdf" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Chapter contributors:**\n", "\n", "- Kathy Le (Johns Hopkins University); this chapter was 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", "< [Low-Res Scoring and Fragments](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/04.02-Low-Res-Scoring-and-Fragments.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [High-Resolution Movers](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/05.01-High-Res-Movers.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 }