PyShifts: A PyMOL Plugin for Chemical Shift-Based Analysis of Biomolecular Ensembles
Here, we present PyShiftsa PyMOL plugin for chemical shift-based analysis of biomolecular ensembles. With PyShifts, users can compare and visualize differences between experimentally measured and computationally predicted chemical shifts. When analyzing multiple conformations of a biomolecule with...
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Veröffentlicht in: | Journal of chemical information and modeling 2020-03, Vol.60 (3), p.1073-1078 |
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Sprache: | eng |
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Zusammenfassung: | Here, we present PyShiftsa PyMOL plugin for chemical shift-based analysis of biomolecular ensembles. With PyShifts, users can compare and visualize differences between experimentally measured and computationally predicted chemical shifts. When analyzing multiple conformations of a biomolecule with PyShifts, users can also sort a set of conformations based on chemical shift differences and identify the conformers that exhibit the best agreement between measured and predicted chemical shifts. Although we have integrated PyShifts with the chemical shift predictors LARMORD and LARMORCα, PyShifts can read in chemical shifts from any source, and so, users can employ PyShifts to analyze biomolecular structures using chemical shifts computed by any chemical shift predictor. We envision, therefore, that PyShifts (https://github.com/atfrank/PyShifts) will find utility as a general-purpose tool for exploring chemical shift–structure relationships in biomolecular ensembles. |
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ISSN: | 1549-9596 1549-960X |
DOI: | 10.1021/acs.jcim.9b01039 |