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Chen, Po-Chia ; Hologne, Maggy ; Walker, Olivier ; Hennig, Janosch:
Ab Initio Prediction of NMR Spin Relaxation Parameters from Molecular Dynamics Simulations.
In: Journal of Chemical Theory and Computation.
Bd. 14
(2018)
Heft 2
.
- S. 1009-1019.
ISSN 1549-9626
DOI: https://doi.org/10.1021/acs.jctc.7b00750
Abstract
1H–15N NMR spin relaxation and relaxation dispersion experiments can reveal the time scale and extent of protein motions across the ps–ms range, where the ps–ns dynamics revealed by fundamental quantities R1, R2, and heteronuclear NOE can be well-sampled by molecular dynamics simulations (MD). Although the principles of relaxation prediction from simulations are well-established, numerous NMR–MD comparisons have hitherto focused upon the aspect of order parameters S2 due to common artifacts in the prediction of transient dynamics. We therefore summarize here all necessary components and highlight existing and proposed solutions, such as the inclusion of quantum mechanical zero-point vibrational corrections and separate MD convergence of global and local motions in coarse-grained and all-atom force fields, respectively. For the accuracy of the MD prediction to be tested, two model proteins GB3 and Ubiquitin are used to validate five atomistic force fields against published NMR data supplemented by the coarse-grained force field MARTINI+EN. In Amber and CHARMM-type force fields, quantitative agreement was achieved for structured elements with minimum adjustment of global parameters. Deviations from experiment occur in flexible loops and termini, indicating differences in both the extent and time scale of backbone motions. The lack of systematic patterns and water model dependence suggests that modeling of the local environment limits prediction accuracy. Nevertheless, qualitative accuracy in a 2 μs CHARMM36m Stam2 VHS domain simulation demonstrates the potential of MD-based interpretation in combination with NMR-measured dynamics, increasing the utility of spin relaxation in integrative structural biology.