Analysis of the uncharted, druglike property space by self-organizing maps.

ABSTRACT: Physicochemical properties are fundamental to predict the pharmacokinetic and pharmacodynamic behavior of drug candidates. Easily calculated descriptors such as molecular weight and logP have been found to correlate with the success rate of clinical trials. These properties have been previously shown to highlight a sweet-spot in the chemical space associated with favorable pharmacokinetics, which is superior against other regions during hit identification and optimization. In this study, we applied self-organizing maps (SOMs) trained on sixteen calculated properties of a subset of known drugs for the analysis of commercially available compound databases, as well as public biological and chemical databases frequently used for drug discovery. Interestingly, several regions of the property sp

SUBMITTER: Takacs G 

PROVIDER: S-EPMC9532340 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature