PyShifts: Difference between revisions

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We developed a PyMOL plugin, '''PyShifts''', a user friendly tool to analyze biomolecular structures using NMR-derived chemical shifts. PyShifts is highly interactive and allows the user to execute single model as well as multi-model structural analyses. Using PyShifts, users can sort structures, cluster structures, and assign conformational weights to each structure, which, collectively, facilitates a multi-faceted analysis of biomolecular ensembles.
We developed a PyMOL plugin, '''PyShifts''', a user friendly tool to analyze biomolecular structures using NMR-derived chemical shifts. PyShifts is highly interactive and allows the user to execute single model as well as multi-model structural analyses. Using PyShifts, users can sort structures, cluster structures, and assign conformational weights to each structure, which, collectively, facilitates a multi-faceted analysis of biomolecular ensembles.
== PyShifts Features ==
== PyShifts Features ==
* Chemical shifts-based error/difference analysis
* Single-model Analysis
* Visualize chemical shifts error
* Facilitates structure-based re-referencing of chemical shifts
* Multi-model Analysis
* Multi-model Analysis
** Assign conformational weights
** Sort structures based on chemical shift error
** Assign conformational weights (using Bayesian Maximum Entropy)
** Chemical shift-based clustering
** Chemical shift-based clustering
** Sort structures
 
== Download ==
== Download ==
The most recent version of PyShifts can be downloaded from our [https://github.com/atfrank/PyShifts GitHub repository].
The most recent version of PyShifts can be downloaded from our [https://github.com/atfrank/PyShifts GitHub repository].

Revision as of 23:03, 15 January 2020

Description

Determining the structure of biomolecules is an important step in understanding how they execute specific cellular functions. NMR spectroscopy provides a number of observables, for example, NMR-derived chemical shifts, that contain valuable information about the conformational state(s) that are accessible to a given biomolecule. Accordingly, chemical shifts are now routinely used to model the secondary and tertiary structure of proteins. We developed a PyMOL plugin, PyShifts, a user friendly tool to analyze biomolecular structures using NMR-derived chemical shifts. PyShifts is highly interactive and allows the user to execute single model as well as multi-model structural analyses. Using PyShifts, users can sort structures, cluster structures, and assign conformational weights to each structure, which, collectively, facilitates a multi-faceted analysis of biomolecular ensembles.

PyShifts Features

  • Single-model Analysis
  • Visualize chemical shifts error
  • Facilitates structure-based re-referencing of chemical shifts
  • Multi-model Analysis
    • Sort structures based on chemical shift error
    • Assign conformational weights (using Bayesian Maximum Entropy)
    • Chemical shift-based clustering

Download

The most recent version of PyShifts can be downloaded from our GitHub repository.

Requirements & Dependencies

Installation & Configuration

Install Dependencies

git clone https://github.com/atfrank/PyShifts.git
cd Pyshifts
. setup.sh

Open PyMOL GUI

pymol

Install PyShifts in PyMOL

In PyMOL GUI, go to Plugin > Plugin Manager > Install New Plugin > choose PyShiftsPlugin.py from the directory that the PyShifts repository is located.

Usage

You can use the examples from the test/ directory to test run PyShifts.

Load Object

Load the object to be analyzed in PyMOL, e.g. 2KOC_test.pdb from test directory by typing load test/2KOC_test.pdb in pymol command line or dragging the file into PyMOL window.

Open PyShifts GUI

Open PyShifts GUI from Plugin > Legacy Plugins > PyShifts.

Perform Chemical Shift-Based Analysis

  • Type the object name 2KOC_test in PyMOL selection/object entry > Run.
  • Go to second tab Error Analysis and input measured chemical shifts in Chemical Shift File > Compare Chemical Shifts.
  • Click on Error table or CS table to save results.

References

  • PyShifts (submitted): Jingru Xie, Kexin Zhang and Aaron T. Frank. "Pyshifts: A PyMOL Plugin for Chemical Shift-Based Analysis of Biomolecular Ensembles".
  • LarmorD: Frank, Aaron T., Sean M. Law, and Charles L. Brooks III. "A simple and fast approach for predicting 1H and 13C chemical shifts: toward chemical shift-guided simulations of RNA." The Journal of Physical Chemistry B 118.42 (2014): 12168-12175.
  • LarmorCa: Frank, Aaron T., et al. "Predicting Protein Backbone Chemical Shifts From Cα Coordinates: Extracting High Resolution Experimental Observables from Low Resolution Models." Journal of chemical theory and computation 11.1 (2014): 325-331.

Copyright Notice

The PyMOL Plugin source code in this file is copyrighted, but you can freely use and copy it as long as you don't change or remove any of the copyright notices. This PyMOL Plugin is Copyright (C) 2016 by Jingru Xie , Kexin Zhang and Aaron T. Frank All Rights Reserved

Permission to use, copy, modify, distribute, and distribute modified versions of this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies and that both the copyright notice and this permission notice appear in supporting documentation, and that the name(s) of the author(s) not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission.

THE AUTHOR(S) DISCLAIM ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR(S) BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.