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Journal of Computational Chemistry
Article . 2020 . Peer-reviewed
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Journal of Computational Chemistry
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On the many‐body nature of intramolecular forces in FFLUX and its implications

Authors: Anton Konovalov; Benjamin C.B. Symons; Paul L.A. Popelier;

On the many‐body nature of intramolecular forces in FFLUX and its implications

Abstract

AbstractFFLUX is a biomolecular force field under construction, based on Quantum Chemical Topology (QCT) and machine learning (kriging), with a minimalistic and physically motivated design. A detailed analysis of the forces within the kriging models as treated in FFLUX is presented, taking as a test example a liquid water model. The energies of topological atoms are modeled as 3Natoms‐6 dimensional potential energy surfaces, using atomic local frames to represent the internal degrees of freedom. As a result, the forces within the kriging models in FFLUX are inherently N‐body in nature where N refers to Natoms. This provides a fuller picture that is closer to a true quantum mechanical representation of interactions between atoms. The presented computational example quantitatively showcases the non‐negligible (as much as 9%) three‐body nature of bonded forces and angular forces in a water molecule. We discuss the practical impact on the pressure calculation with N‐body forces and periodic boundary conditions (PBC) in molecular dynamics, as opposed to classical force fields with two‐body forces. The equivalence between the PBC‐related correction terms in the general virial equation is shown mathematically.

Related Organizations
Keywords

Machine Learning, Models, Chemical, Water, Computer Simulation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Average
Top 10%
Green
hybrid