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Your search keyword '"force field"' showing total 2 results
2 results on '"force field"'

1. FFLUX: Transferability of polarizable machine-learned electrostatics in peptide chains.

Author

Fletcher, Timothy L. and Popelier, Paul L. A.

Subjects
*MACHINE learning, *ELECTROSTATICS, *PEPTIDES, *MOLECULAR force constants, *KRIGING
Abstract

The fully polarizable, multipolar, and atomistic force field protein FFLUX is being built from machine learning (i.e., kriging) models, each of which predicts an atomic property. Each atom of a given protein geometry needs to be assigned such a kriging model. Such a knowledgeable atom needs to be informed about a sufficiently large environment around it. The resulting complexity can be tackled by collecting the 20 natural amino acids into a few groups. Using substituted deca-alanines, we present the proof-of-concept that a given atom's charge can be modeled by a few kriging models only. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Published
2017
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2. Toward the Prediction of Multi-Spin State Charges of a Heme Model by Random Forest Regression

Author

Qing Li, Wei Zhao, Xian-Hui Huang, Jun Gao, and Lihua Bie

Subjects
Spin states, Charge model, ESP charge, 02 engineering and technology, 010402 general chemistry, 01 natural sciences, Force field (chemistry), lcsh:Chemistry, Molecular dynamics, spin crossover, Spin crossover, Atomic charge, Statistical physics, Original Research, Physics, force field, General Chemistry, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Random forest, Dynamic simulation, Chemistry, heme model, machine learning, lcsh:QD1-999, 0210 nano-technology
Abstract

The random forest regression (RFR) model was introduced to predict the multiple spin state charges of a heme model, which is important for the molecular dynamic simulation of the spin crossover phenomenon. In this work, a multiple spin state structure data set with 39,368 structures of the simplified heme–oxygen binding model was built from the non-adiabatic dynamic simulation trajectories. The ESP charges of each atom were calculated and used as the real-valued response. The conformational adapted charge model (CAC) of three spin states was constructed by an RFR model using symmetry functions. The results show that our RFR model can effectively predict the on the fly atomic charges with the varying conformations as well as the atomic charge of different spin states in the same conformation, thus achieving the balance of accuracy and efficiency. The average mean absolute error of the predicted charges of each spin state is

Published
2020

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