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Combined QM/MM, machine learning path integral approach to compute free energy profiles and kinetic isotope effects in RNA cleavage reactions
Accepted manuscript   Open access   Peer reviewed

Combined QM/MM, machine learning path integral approach to compute free energy profiles and kinetic isotope effects in RNA cleavage reactions

Timothy J. Giese, Jinzhe Zeng, Şölen Ekesan and Darrin M. York
Journal of Chemical Theory and Computation, Vol.18(7), pp.4304-4317
07/12/2022
DOI:
https://doi.org/10.7282/00000330
PMCID: PMC9283286
PMID: 35709391

Abstract

Chemistry Chemistry, Physical Physics, Atomic, Molecular & Chemical Science & Technology Free energy QM/MM Reaction mechanisms Transition states Computer Simulation or Modeling Physical Sciences Physics
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Accepted Manuscript (AM)This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Chemical Theory and Computation, copyright © 2022 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jctc.2c00151 Open Access
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https://doi.org/10.1021/acs.jctc.2c00151View
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