Along the allostery stream: Recent advances in computational methods for allosteric drug discovery

Abstract Allostery is a universal, biological phenomenon in which orthosteric sites are fine‐tuned by topologically distal allosteric sites triggered by perturbations, such as ligand binding, residue mutations, or post‐translational modifications. Allosteric regulation is implicated in a variety of physiological and pathological conditions and is thus emerging as a novel avenue for drug discovery. Allosteric drugs have traditionally been discovered by serendipity through large‐scale experimental screening. Recently, we have witnessed significant progress in biophysics, particularly in structural bioinformatics, which has facilitated the in‐depth characterization of allosteric effects and the accurate detection of allosteric residues and exosites. These advances improve our understanding of allosterism and promote allosteric drug discovery, thereby revolutionizing the shift from the traditional serendipitous route used to discover allosteric drugs to the updated path centered on rational structure‐based design. In this review, recent advances in computational methods applied to allosteric drug discovery are summarized. We comprehensively review these achievements along various levels of allosteric events, from the construction of allosteric databases to the identification and analysis of allosteric residues, signals, sites, and modulators. We expect to increase the awareness of the discovery of allosteric drugs using structure‐based computational methods. This article is categorized under: Structure and Mechanism > Computational Biochemistry and Biophysics