Property-based characterization of kinase-like ligand space for library design and virtual screening

Abstract

A property-based desirability scoring scheme has been developed for kinase-focused library design and ligand-based pre-screening of large compound sets. The property distributions of known kinase inhibitors from the ChEMBL Kinase Sarfari database were investigated and used for a desirability function-based score. The scoring scheme is easily interpretable as it accounts for six molecular properties: topological polar surface area and the number of rotatable bonds, hydrogen bond donors, aromatic rings, nitrogen atoms and oxygen atoms. The performance of the Kinase Desirability Score (KiDS) is evaluated on both public and proprietary experimental screening data.