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Modeling of Hidden Structures Using Sparse Chemical Shift Data from NMR Relaxation Dispersion.

Authors :
Fenwick RB
Oyen D
van den Bedem H
Dyson HJ
Wright PE
Source :
Biophysical journal [Biophys J] 2021 Jan 19; Vol. 120 (2), pp. 296-305. Date of Electronic Publication: 2020 Dec 08.
Publication Year :
2021

Abstract

NMR relaxation dispersion measurements report on conformational changes occurring on the μs-ms timescale. Chemical shift information derived from relaxation dispersion can be used to generate structural models of weakly populated alternative conformational states. Current methods to obtain such models rely on determining the signs of chemical shift changes between the conformational states, which are difficult to obtain in many situations. Here, we use a "sample and select" method to generate relevant structural models of alternative conformations of the C-terminal-associated region of Escherichia coli dihydrofolate reductase (DHFR), using only unsigned chemical shift changes for backbone amides and carbonyls ( <superscript>1</superscript> H, <superscript>15</superscript> N, and <superscript>13</superscript> C'). We find that CS-Rosetta sampling with unsigned chemical shift changes generates a diversity of structures that are sufficient to characterize a minor conformational state of the C-terminal region of DHFR. The excited state differs from the ground state by a change in secondary structure, consistent with previous predictions from chemical shift hypersurfaces and validated by the x-ray structure of a partially humanized mutant of E. coli DHFR (N23PP/G51PEKN). The results demonstrate that the combination of fragment modeling with sparse chemical shift data can determine the structure of an alternative conformation of DHFR sampled on the μs-ms timescale. Such methods will be useful for characterizing alternative states, which can potentially be used for in silico drug screening, as well as contributing to understanding the role of minor states in biology and molecular evolution.<br /> (Copyright © 2020 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1542-0086
Volume :
120
Issue :
2
Database :
MEDLINE
Journal :
Biophysical journal
Publication Type :
Academic Journal
Accession number :
33301748
Full Text :
https://doi.org/10.1016/j.bpj.2020.11.2267