Published November 8, 2019 | Version v1
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Using NMR relaxation data to improve the dynamics of methyl groups in AMBER and CHARMM force fields


Falk Hoffmann (Ruhr University Bochum) presented his work on improving torsional barriers associated with methyl group rotations in amino acid side-chains in AMBER and CHARMM force fields by using NMR relaxation rates. This study is available as a preprint on ChemrXiv. This talk is a part of OpenFF Webinars that took place on Sep 20, 2019.

Abstract: The internal dynamics of proteins occurring on time scales from picoseconds to nanoseconds can be sensitively probed by nuclear magnetic resonance (NMR) spin relaxation experiments, as well as by molecular dynamics (MD) simulations. This complementarity offers unique opportunities, provided that the two methods are compared at a suitable level. Recently, several groups have used MD simulations to compute the spectral density of backbone and side-chain molecular motions, and to predict NMR relaxation rates from these. Unfortunately, in the case of methyl groups in protein side-chains, inaccurate energy barriers to methyl rotation were responsible for a systematic discrepancy in the computed relaxation rates. In this talk I will present how we used NMR relaxation rates to identify disagreements between simulation and experiment for these energy barriers. The corresponding dihedral angle terms in AMBER and CHARMM force fields which are responsible for these energy barriers are subsequently improved and correspondence between experiment and simulation could be regained by emending the MD force field with accurate coupled cluster quantum chemical calculations. Improved methyl group rotation barriers were derived, such that the NMR relaxation data obtained from the MD simulations now also display very good agreement with experiment. Furthermore, I will show how these energy barriers influence the validity of the Lipari-Szabo model for protein side-chains which is used to extract generalized order parameters from NMR relaxation experiments and MD simulations.



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