Machine Learning for Fast, Quantum Mechanics-Based Approximation of Drug Lipophilicity.

ABSTRACT: Lipophilicity, as measured by the partition coefficient between octanol and water (log P), is a key parameter in early drug discovery research. However, measuring log P experimentally is difficult for specific compounds and log P ranges. The resulting lack of reliable experimental data impedes development of accurate in silico models for such compounds. In certain discovery projects at Novartis focused on such compounds, a quantum mechanics (QM)-based tool for log P estimation has emerged as a valuable supplement to experimental measurements and as a preferred alternative to existing empirical models. However, this QM-based approach incurs a substantial computational cost, limiting its applicability to small series and prohibiting quick, interactive ideation. Th

SUBMITTER: Isert C 

PROVIDER: S-EPMC9850743 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature