Exposons exploit cooperative changes in solvent exposure to detect cryptic allosteric sites and other functionally-relevant conformational transitions

Conformational changes can dramatically alter a protein9s function by changing the surfaces that are accessible to interact with binding partners. However, it is often difficult to hone in on the most relevant conformational changes from the cartesian coordinates of atoms on the protein9s surface. Instead, we describe a protein9s surface in terms of groups of residues that undergo cooperative changes in their solvent exposure. We term these groups exposons. We demonstrate that Markov state models (MSMs) elegantly identify the conformational transitions that give rise to an exposon, enabling users to rapidly find the most interesting conformational changes in their system. For example, this approach readily identifies previously-known cryptic allosteric sites and other functionally-relevant conformational transitions. Moreover, it predicts a cryptic allosteric site in an important target for combating antibiotic resistance that lacks known cryptic pockets. Experimental tests confirm that targeting this site reduces catalytic efficiency 15-fold.