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.
- 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
The most recent version of PyShifts can be downloaded from our GitHub repository.
Requirements & Dependencies
- XQuartz (Mac user)
- PyMOL license
Installation & Configuration
git clone https://github.com/atfrank/PyShifts.git cd Pyshifts . setup.sh
Open PyMOL GUI
Install PyShifts in PyMOL
In PyMOL GUI, go to
Plugin Manager >
Install New Plugin > choose
PyShiftsPlugin.py from the directory that the PyShifts repository is located.
You can use the examples from the
test/ directory to test run PyShifts.
Load the object to be analyzed in PyMOL, e.g.
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
Legacy Plugins >
Perform Chemical Shift-Based Analysis
- Type the object name
PyMOL selection/objectentry > Run.
- Go to second tab
Error Analysisand input measured chemical shifts in
Chemical Shift File>
Compare Chemical Shifts.
- Click on
CS tableto save results.
- PyShifts (In revision): 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.
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.