Fitting Side-Chain NMR Relaxation Data Using Molecular Simulations
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Dokumenter
- Fulltext
Forlagets udgivne version, 3,23 MB, PDF-dokument
Proteins display a wealth of dynamical motions that can be probed using both experiments and simulations. We present an approach to integrate side-chain NMR relaxation measurements with molecular dynamics simulations to study the structure and dynamics of these motions. The approach, which we term ABSURDer (average block selection using relaxation data with entropy restraints), can be used to find a set of trajectories that are in agreement with relaxation measurements. We apply the method to deuterium relaxation measurements in T4 lysozyme and show how it can be used to integrate the accuracy of the NMR measurements with the molecular models of protein dynamics afforded by the simulations. We show how fitting of dynamic quantities leads to improved agreement with static properties and highlight areas needed for further improvements of the approach.
Originalsprog | Engelsk |
---|---|
Tidsskrift | Journal of Chemical Theory and Computation |
Vol/bind | 17 |
Udgave nummer | 8 |
Sider (fra-til) | 5262-5275 |
Antal sider | 14 |
ISSN | 1549-9618 |
DOI | |
Status | Udgivet - 2021 |
Bibliografisk note
Funding Information:
We are grateful to Profs. Lars V. Schäfer and Frans A.A. Mulder for discussions, help, and comments on the manuscript. We acknowledge support by a grant from the Lundbeck Foundation to the BRAINSTRUC structural biology initiative (155-2015-2666, to K.L.-L.), the NordForsk Nordic Neutron Science Programme (to K.L.-L.), the Carlsberg Foundation (CF17-0491, to Y.G.), and the Novo Nordisk Foundation (NNF15OC0016360, to K.T. and K.L.-L.). We acknowledge access to computational resources from the ROBUST Resource for Biomolecular Simulations (supported by the Novo Nordisk Foundation grant no. NF18OC0032608) and the Biocomputing Core Facility at the Department of Biology, University of Copenhagen.
Publisher Copyright:
© 2021 American Chemical Society.
ID: 276166008