Automated Training of ReaxFF Reactive Force Fields for Energetics of Enzymatic Reactions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F18%3A00102246" target="_blank" >RIV/00216224:14740/18:00102246 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1021/acs.jctc.7b00870" target="_blank" >http://dx.doi.org/10.1021/acs.jctc.7b00870</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1021/acs.jctc.7b00870" target="_blank" >10.1021/acs.jctc.7b00870</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automated Training of ReaxFF Reactive Force Fields for Energetics of Enzymatic Reactions

Popis výsledku v původním jazyce

Computational studies of the reaction mechanisms of various enzymes are nowadays based almost exclusively on hybrid QM/MM models. Unfortunately, the success of this approach strongly depends on the selection of the QM region, and computational cost is a crucial limiting factor. An interesting alternative is offered by empirical reactive molecular force fields, especially the ReaxFF potential developed by van Duin and co-workers. However, even though an initial parametrization of ReaxFF for biomolecules already exists, it does not provide the desired level of accuracy. We have conducted a thorough refitting of the ReaxFF force field to improve the description of reaction energetics. To minimize the human effort required, we propose a fully automated approach to generate an extensive training set comprised of thousands of different geometries and molecular fragments starting from a few model molecules. Electrostatic parameters were optimized with QM electrostatic potentials as the main target quantity, avoiding excessive dependence on the choice of reference atomic charges and improving robustness and transferability. The remaining force field parameters were optimized using the VD-CMA-ES variant of the CMA-ES optimization algorithm. This method is able to optimize hundreds of parameters simultaneously with unprecedented speed and reliability. The resulting force field was validated on a real enzymatic system, ppGalNAcT2 glycosyltransferase. The new force field offers excellent qualitative agreement with the reference QM/MM reaction energy profile, matches the relative energies of intermediate and product minima almost exactly, and reduces the overestimation of transition state energies by 27-48% compared with the previous parametrization.

Název v anglickém jazyce

Automated Training of ReaxFF Reactive Force Fields for Energetics of Enzymatic Reactions

Popis výsledku anglicky

Computational studies of the reaction mechanisms of various enzymes are nowadays based almost exclusively on hybrid QM/MM models. Unfortunately, the success of this approach strongly depends on the selection of the QM region, and computational cost is a crucial limiting factor. An interesting alternative is offered by empirical reactive molecular force fields, especially the ReaxFF potential developed by van Duin and co-workers. However, even though an initial parametrization of ReaxFF for biomolecules already exists, it does not provide the desired level of accuracy. We have conducted a thorough refitting of the ReaxFF force field to improve the description of reaction energetics. To minimize the human effort required, we propose a fully automated approach to generate an extensive training set comprised of thousands of different geometries and molecular fragments starting from a few model molecules. Electrostatic parameters were optimized with QM electrostatic potentials as the main target quantity, avoiding excessive dependence on the choice of reference atomic charges and improving robustness and transferability. The remaining force field parameters were optimized using the VD-CMA-ES variant of the CMA-ES optimization algorithm. This method is able to optimize hundreds of parameters simultaneously with unprecedented speed and reliability. The resulting force field was validated on a real enzymatic system, ppGalNAcT2 glycosyltransferase. The new force field offers excellent qualitative agreement with the reference QM/MM reaction energy profile, matches the relative energies of intermediate and product minima almost exactly, and reduces the overestimation of transition state energies by 27-48% compared with the previous parametrization.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10610 - Biophysics

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Chemical Theory and Computation

ISSN

1549-9618

e-ISSN

—

Svazek periodika

14

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

291-302

Kód UT WoS článku

000419998300026

EID výsledku v databázi Scopus

2-s2.0-85040347593