Medina‐Franco, José L.

Abstract Preclinical Research The increasing awareness that drugs may have the clinical effect through the interaction with multiple targets is encouraging the screening of investigational compounds across multiple biological endpoints. As the number and complexity of chemogenomics data sets increase, more computational approaches are being developed for the efficient analysis of structure–multiple activity relationships. In silico methods cover a wide range of applications including visual, qualitative, and quantitative approaches to describe in detail multiple ligand–protein relationships, find associations between targets and, whenever possible, to predict the bioactivity profile of small molecules. Here, we present a commentary of representative computational methods and their applications to characterize structure–multiple activity relationships and conduct the rational design of polypharmacology for the advancement of drug discovery.

Inhibitors of human DNA methyltransferases (DNMT) are of increasing interest to develop novel epi-drugs for the treatment of cancer and other diseases. As the number of compounds with reported DNMT inhibition is increasing, molecular docking is shedding light to elucidate their mechanism of action and further interpret structure–activity relationships. Herein, we present a structure-based rationalization of the activity of SW155246, a distinct sulfonamide compound recently reported as an inhibitor of human DNMT1 obtained from high-throughput screening. We used flexible and induce-fit docking to develop a binding model of SW155246 with a crystallographic structure of human DNMT1. Results were in excellent agreement with experimental information providing a three-dimensional structural interpretation of ‘activity cliffs’, e.g., analogues of SW155246 with a high structural similarity to the sulfonamide compound, but with no activity in the enzymatic assay.