A Machine Learning Force Field for Bio-Macromolecular Modeling Based on Quantum Chemistry-Calculated Interaction Energy Datasets

A Machine Learning Force Field for Bio-Macromolecular Modeling Based on Quantum Chemistry-Calculated Interaction Energy Datasets

Accurate energy data from noncovalent interactions are essential for constructing force fields for molecular dynamics simulations of bio-macromolecular systems. There are two important practical issues in the construction of a reliable force field with the hope of balancing the desired chemical accu...

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Bibliographic Details
Main Authors: Zhen-Xuan Fan, Sheng D. Chao
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Bioengineering
Subjects:
noncovalent interactions
machine learning force fields
symmetry-adapted perturbation theory
ab initio energy datasets
artificial intelligence
Online Access:https://www.mdpi.com/2306-5354/11/1/51

Internet

https://www.mdpi.com/2306-5354/11/1/51

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