Fast and accurate prediction of partial charges using Atom-Path-Descriptor-based machine learning.
Journal:
Bioinformatics (Oxford, England)
PMID:
32525553
Abstract
MOTIVATION: Partial atomic charges are usually used to calculate the electrostatic component of energy in many molecular modeling applications, such as molecular docking, molecular dynamics simulations, free energy calculations and so forth. High-level quantum mechanics calculations may provide the most accurate way to estimate the partial charges for small molecules, but they are too time-consuming to be used to process a large number of molecules for high throughput virtual screening.