Literature DB >> 27415976

reaxFF Reactive Force Field for Disulfide Mechanochemistry, Fitted to Multireference ab Initio Data.

Julian Müller1, Bernd Hartke1.   

Abstract

Mechanochemistry, in particular in the form of single-molecule atomic force microscopy experiments, is difficult to model theoretically, for two reasons: Covalent bond breaking is not captured accurately by single-determinant, single-reference quantum chemistry methods, and experimental times of milliseconds or longer are hard to simulate with any approach. Reactive force fields have the potential to alleviate both problems, as demonstrated in this work: Using nondeterministic global parameter optimization by evolutionary algorithms, we have fitted a reaxFF force field to high-level multireference ab initio data for disulfides. The resulting force field can be used to reliably model large, multifunctional mechanochemistry units with disulfide bonds as designed breaking points. Explorative calculations show that a significant part of the time scale gap between AFM experiments and dynamical simulations can be bridged with this approach.

Entities:  

Year:  2016        PMID: 27415976     DOI: 10.1021/acs.jctc.6b00461

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  4 in total

Review 1.  Aqueous ionic liquids influence the disulfide bond isoform equilibrium in conotoxin AuIB: a consequence of the Hofmeister effect?

Authors:  Karuna Anna Sajeevan; Durba Roy
Journal:  Biophys Rev       Date:  2018-01-02

2.  Quantum mechanical force fields for condensed phase molecular simulations.

Authors:  Timothy J Giese; Darrin M York
Journal:  J Phys Condens Matter       Date:  2017-08-17       Impact factor: 2.333

3.  Mixing ReaxFF parameters for transition metal oxides using force-matching method.

Authors:  Adam Włodarczyk; Mariusz Uchroński; Agata Podsiadły-Paszkowska; Joanna Irek; Bartłomiej M Szyja
Journal:  J Mol Model       Date:  2021-12-14       Impact factor: 1.810

4.  GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations.

Authors:  Michael Freitas Gustavo; Toon Verstraelen
Journal:  J Cheminform       Date:  2022-02-16       Impact factor: 5.514

  4 in total

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