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Simultaneous refinement of molecular dynamics ensembles and forward models using experimental data.

Authors :
Fröhlking, Thorben
Bernetti, Mattia
Bussi, Giovanni
Source :
Journal of Chemical Physics. 6/7/2023, Vol. 158 Issue 21, p1-13. 13p.
Publication Year :
2023

Abstract

A novel method combining the maximum entropy principle, the Bayesian-inference of ensembles approach, and the optimization of empirical forward models is presented. Here, we focus on the Karplus parameters for RNA systems, which relate the dihedral angles of γ, β, and the dihedrals in the sugar ring to the corresponding 3J-coupling signal between coupling protons. Extensive molecular simulations are performed on a set of RNA tetramers and hexamers and combined with available nucleic-magnetic-resonance data. Within the new framework, the sampled structural dynamics can be reweighted to match experimental data while the error arising from inaccuracies in the forward models can be corrected simultaneously and consequently does not leak into the reweighted ensemble. Carefully crafted cross-validation procedure and regularization terms enable obtaining transferable Karplus parameters. Our approach identifies the optimal regularization strength and new sets of Karplus parameters balancing good agreement between simulations and experiments with minimal changes to the original ensemble. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00219606
Volume :
158
Issue :
21
Database :
Academic Search Index
Journal :
Journal of Chemical Physics
Publication Type :
Academic Journal
Accession number :
164179359
Full Text :
https://doi.org/10.1063/5.0151163