Steering Molecular Dynamics Simulations of Membrane-Associated Proteins with Neutron Reflection Results
Author(s) -
Bradley W. Treece,
Frank Heinrich,
Arvind Ramanathan,
Mathias Lösche
Publication year - 2020
Publication title -
journal of chemical theory and computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.001
H-Index - 185
eISSN - 1549-9626
pISSN - 1549-9618
DOI - 10.1021/acs.jctc.0c00136
Subject(s) - molecular dynamics , neutron reflectometry , reflectometry , reflection (computer programming) , work (physics) , biological system , neutron scattering , neutron , statistical physics , scattering , computer science , physics , chemical physics , materials science , computational physics , chemistry , computational chemistry , optics , small angle neutron scattering , thermodynamics , time domain , quantum mechanics , biology , computer vision , programming language
We present a novel method to incorporate structural results from surface-sensitive scattering, such as X-ray or neutron reflectometry, into molecular dynamics simulations. While reflectometry techniques generally provide a means to determine the molecular-scale structures of organized interfacial films, they were recently shown to offer the capability to characterize the structures of protein-membrane complexes supported by a solid substrate. One-dimensional information inherent in the experimental results is used in the form of component volume occupancy (CVO) profiles, which describe the distribution of molecular components within an interfacial architecture, to construct real-space constraints in the form of a biasing potential for the simulation that vanishes when the simulated and experimental profiles agree. This approach improves the correspondence between simulation and experiment, as shown in the re-evaluation of an neutron-reflection-derived structure which was approximated by an independent molecular dynamics simulation in earlier work, and it also leads to faster equilibration of ensemble structures. We further show that time averaging the CVO profile that develops in the simulation while biasing with this approach permits fluctuations about the average that are necessary for conformational exploration of the system. This method is particularly valuable for studies of proteins at interfaces that contain disordered regions since the conformation of such regions is difficult to judge from the analysis of one-dimensional experimental profiles and may take prohibitively long to equilibrate in simulations.
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