Local deformations of proteins through molecular simulations reveal allosteric couplings with implications for drug design

Allosteric regulation is an important property of proteins with many applications in drug design, yet is notoriously difficult to characterize for any general protein. Many proteins show very subtle conformational changes upon allosteric perturbations, with local changes that are not captured by global metrics such as Root Mean Squared Deviation. This poses a challenge for drug design, where subtle allosteric changes induced by drug binding are missed and the computed efficacy of drugs is mischaracterized. We show that the more natural language to describe conformational changes is a local metric based on an elastic strain formalism, that is able to capture local deformations induced by allosteric perturbations such as drug/peptide binding in Molecular Dynamics simulations. The shear strain tensor is calculated upon binding and reveals previously unknown allosteric sites and allosteric mechanisms. In particular, we find that through this formalism, we are able to explain the mechanisms of repurposed drugs against key proteins of the SARS-CoV-2 proteome, and uncover previously unknown binding sites that can be exploited in drug design. This methodology paves the way for the design of new allosteric drugs to tackle diseases that are hard to target through drugs that act at the functional site.