Regardless of the diversity of systems, allosteic signalling is found to be always caused by perturbations. This recurring trait of allostery serves as a foundation for developing different experimental efforts and theoretical models for the studies of allosteric mechanisms. Among computational approaches considered here particular emphasis is given to the structure-based statistical mechanical model of allostery (SBSMMA), which allows one to study the causality and energetics of allosteric communication. We argue that the reverse allosteric signaling on the basis of SBSMMA can be used for predicting latent allosteric sites and inducing a tunable allosteric response. Per-residue allosteric effects of mutations can also be explored and ‘latent drivers’ expanding the cancer mutational landscape can be predicted using SBSMMA. Most recent and important implementations of computational models in web-resources along with a brief outlook on future research directions are also discussed.
Current Opinion in Structural Biology, Vol. 56, June 2019, Pg 18-27, doi: 10.1016/j.sbi.2018.10.008