Rewiring enzyme regulation: allosteric drugs and predictive tools

Abstract

Allosteric modulation offers an increasingly attractive route for precise intervention in enzymatic pathways. This review outlines emerging strategies for the identification and exploitation of allosteric sites, emphasizing computational frameworks that integrate evolutionary, structural, and dynamic features with machine learning models. We discuss how perturbation-based simulations, network analyses, and deep mutational data are reshaping our understanding of allosteric regulation. In parallel, advances in experimental techniques have enabled validation of cryptic and functionally relevant pockets across diverse enzyme families. We further catalog FDA-approved allosteric modulators of enzymes, highlighting therapeutic designs that leverage distal regulation to enhance specificity and overcome resistance. Taken together, these developments reveal the growing utility of allostery in drug design and underscore its potential to expand the therapeutic target space beyond conventional binding sites.