Reversing allosteric communication: From detecting allosteric sites to inducing and tuning targeted allosteric response

Published date : 18 Jun 2018

The omnipresence of allosteric regulation together with the fundamental role of structural dynamics in this phenomenon have initiated a great interest to the detection of regulatory exosites and design of corresponding effectors. However, despite a general consensus on the key role of dynamics most of the earlier efforts on the prediction of allosteric sites are heavily crippled by the static nature of the underlying methods, which are either structure-based approaches seeking for deep surface pockets typical for “traditional” orthosteric drugs or sequence-based techniques exploiting the conservation of protein sequences. Because of the critical role of global protein dynamics in allosteric signaling, we investigate the hypothesis of reversibility in allosteric communication, according to which allosteric sites can be detected via the perturbation of the functional sites. The reversibility is tested here using our structure-based perturbation model of allostery, which allows one to analyze the causality and energetics of allosteric communication. We validate the “reverse perturbation” hypothesis and its predictive power on a set of classical allosteric proteins, then, on the independent extended benchmark set. We also show that, in addition to known allosteric sites, the perturbation of the functional sites unravels rather extended protein regions, which can host latent regulatory exosites. These protein parts that are dynamically coupled with functional sites can also be used for inducing and tuning allosteric communication, and an exhaustive exploration of the per-residue contributions to allosteric effects can eventually lead to the optimal modulation of protein activity. The site-effector interactions necessary for a specific mode and level of allosteric communication can be fine-tuned by adjusting the site’s structure to an available effector molecule and by the design or selection of an appropriate ligand.

Journal Paper
PLoS Computational Biology, 18 Jun 2018, doi:10.1371/journal.pcbi.1006228
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