Reference : Quantum machine learning corrects classical forcefields: Stretching DNA base pairs in...
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Physics
Physics and Materials Science
http://hdl.handle.net/10993/51973
Quantum machine learning corrects classical forcefields: Stretching DNA base pairs in explicit solvent
English
Berryman, Josh mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS) >]
Taghavi, Amirhossein mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Physics and Materials Science Research Unit >]
Mazur, Florian mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Physics and Materials Science Research Unit > ; Université de Lorraine > Laboratoire de Physique et Chimie Théoriques]
Tkatchenko, Alexandre mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS) >]
9-Aug-2022
Journal of Chemical Physics
157
6
Yes
International
[en] machine learning ; simulation ; DNA
[en] In order to improve the accuracy of molecular dynamics simulations, classical forcefields are supplemented with a kernel-based machine learning method trained on quantum-mechanical fragment energies. As an example application, a potential-energy surface is generalized for a small DNA duplex, taking into account explicit solvation and long-range electron exchange–correlation effects. A long-standing problem in molecular science is that experimental studies of the structural and thermodynamic behavior of DNA under tension are not well confirmed by simulation; study of the potential energy vs extension taking into account a novel correction shows that leading classical DNA models have excessive stiffness with respect to stretching. This discrepancy is found to be common across multiple forcefields. The quantum correction is in qualitative agreement with the experimental thermodynamics for larger DNA double helices, providing a candidate explanation for the general and long-standing discrepancy between single molecule stretching experiments and classical calculations of DNA stretching. The new dataset of quantum calculations should facilitate multiple types of nucleic acid simulation, and the associated Kernel Modified Molecular Dynamics method (KMMD) is applicable to biomolecular simulations in general. KMMD is made available as part of the AMBER22 simulation software.
University of Luxembourg: High Performance Computing - ULHPC
Fonds National de la Recherche - FnR
BroadApp
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/51973
10.1063/5.0094727
https://aip.scitation.org/doi/full/10.1063/5.0094727#_i22
Associated dara is available from the NOMAD searchable online repository.
FnR ; FNR14769845 > Alexandre Tkatchenko > BroadApp > Broadly Applicable Methods For Van Der Waals Interactions In Molecules And Materials > 01/09/2021 > 31/08/2024 > 2020

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