Explicit models of motions to analyze NMR relaxation data in proteins

TL;DR

This paper introduces explicit models of molecular motions for analyzing NMR relaxation data in proteins, especially methyl groups, demonstrating their robustness over traditional Model Free approaches in the presence of rotamer jumps.

Contribution

It presents a method to build explicit motion models from molecular dynamics simulations for better NMR relaxation data analysis in proteins.

Findings

Explicit models outperform Model Free in the presence of rotamer jumps.

Models are particularly suited for methyl-bearing side-chains.

Synthetic data shows increased robustness of explicit models.

Abstract

Nuclear Magnetic Resonance (NMR) is a tool of choice to characterize molecular motions. In biological macromolecules, pico- to nano-second motions, in particular, can be probed by nuclear spin relaxation rates which depend on the time fluctuations of the orientations of spin interaction frames. For the past 40 years, relaxation rates have been successfully analyzed using the Model Free (MF) approach which makes no assumption on the nature of motions and reports on the effective amplitude and time-scale of the motions. However, obtaining a mechanistic picture of motions from this type of analysis is difficult at best, unless complemented with molecular dynamics (MD) simulations. In spite of their limited accuracy, such simulations can be used to obtain the information necessary to build explicit models of motions designed to analyze NMR relaxation data. Here, we present how to build such models, suited in particular to describe motions of methyl-bearing protein side-chains and compare them with the MF approach. We show on synthetic data that explicit models of motions are more robust in the presence of rotamer jumps which dominate the relaxation in methyl groups of protein side-chains. We expect this work to motivate the use of explicit models of motion to analyze MD and NMR data.