Molecular topology and other promiscuity determinants as predictors of therapeutic Class? A theoretical framework to guide drug repositioning?

JUAN F. MORALES; LUCAS N. ALBERCA; MAURICIO E. DI IANNI; SARA CHUGURANSKY; ALAN TALEVI; MARÍA E. RUIZ

Current Topics in Medicinal Chemistry

BENTHAM SCIENCE PUBL LTD

Lugar: Oak Park; Año: 2018 vol. 18 p. 1110 - 1122

1568-0266

Much interest has been paid in the last decade on molecular predictors of promiscuity, including molecular weight, log P, molecular complexity, acidity constant and molecular topology, with correlations between promiscuity and those descriptors seemingly being context-dependent. It has been observed that certain therapeutic categories (e.g. mood disorders therapies) display a tendency to include multi-target agents (i.e. selective non-selectivity). Numerous QSAR models based on topological descriptors suggest that the topology of a given drug could be used to infer its therapeutic applications. Here, we have used descriptors statistics to explore the distribution of molecular topology descriptors and other promiscuity predictors across different therapeutic categories. Interestingly, a 3-cluster clustering scheme based on molecular descriptors linked to promiscuity seem to explain up to 82.9% of approved cases of drug repurposing listed by repoDB (excluding trivial cases). Therapeutic categories seem to display distinctive molecular patterns, which could be used as a basis for drug screening and drug design campaigns, and to unveil drug repurposing opportunities between particular therapeutic categories.