Quantum-based machine learning and AI models to generate force field parameters for drug-like small molecules.

ABSTRACT: Force fields for drug-like small molecules play an essential role in molecular dynamics simulations and binding free energy calculations. In particular, the accurate generation of partial charges on small molecules is critical to understanding the interactions between proteins and drug-like molecules. However, it is a time-consuming process. Thus, we generated a force field for small molecules and employed a machine learning (ML) model to rapidly predict partial charges on molecules in less than a minute of time. We performed density functional theory (DFT) calculation for 31770 small molecules that covered the chemical space of drug-like molecules. The partial charges for the atoms in a molecule were predicted using an ML model trained on DFT-based atomic charges. The predicted values wer

SUBMITTER: Mudedla SK 

PROVIDER: S-EPMC9592901 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature