Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications.

ABSTRACT: Molecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most established and versatile concepts in drug discovery. Improvement of this molecular description is highly desirable for in silico drug discovery and medicinal chemistry applications. In this work, we revised a well-established molecular mechanics' force field and applied a hybrid quantum mechanics and machine learning approach to parametrize the hydrogen-bonding (HB) potentials of small molecules, improving this aspect of the molecular description. Approximately 66,000 molecules were chosen from available drug databases and subjected to density functional theory calculations (DFT). For each atom, the molecular electrostatic potential (EP) was extract

SUBMITTER: Tortorella S 

PROVIDER: S-EPMC9291213 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature