Specificity in the druggable kinome: Molecular basis and its applications

Rational design of kinase inhibitors remains a challenge partly because there is no clear delineation of the molecular features that direct the pharmacological impact towards clinically relevant targets. In this thesis, we focus on a structural marker and construct a kinase classifier that enables the accurate prediction of pharmacological differences. Our indicator is a microenvironmental descriptor that quantifies the propensity for water exclusion around preformed polar pairs. The results suggest that targeting polar dehydration patterns heralds a new generation of drugs that enable a tighter control of specificity than designs aimed at promoting ligand-kinase pairwise interactions. As an application of the structural marker, we introduce a computational screening approach which provides a tool for extensive screening that uses experimentally obtained small-scale profiles as input data and makes predictions for a larger kinase set. These predictions result from a propagation of the reduced profile, exploiting a structural comparison of kinases based on a feature-similarity matrix. The comparison focuses on a molecular marker for specificity and promiscuity of kinase inhibitors. Our approach enables the computational high-throughput screening of entire libraries of compounds to search for suitable leads, mapping their inhibitory impact on a sizable sample of the human kinome. Yet another application of the structural marker is advocated by illustrating its cleaning efficacy. In this regard, we reassess the possibility to turn multi-target drugs into real clinical opportunities through judicious redesign. A general cleaning strategy, which adopts the structural marker as redesigning instruction, is proposed and exemplified by a workable approach