Along the allostery stream: Recent advances in computational methods for allosteric drug discovery

Abstract

Allostery is a universal, biological phenomenon in which orthosteric sites are finetuned by topologically distal allosteric sites triggered by perturbations, such as ligand binding, residue mutations, or post-translational modifications. Allosteric regulation is implicated in a variety of physiological and pathological conditions and is thus emerging as a novel avenue for drug discovery. Allosteric drugs have traditionally been discovered by serendipity through large-scale experimental screening. Recently, we have witnessed significant progress in biophysics, particularly in structural bioinformatics, which has facilitated the in-depth characterization of allosteric effects and the accurate detection of allosteric residues and exosites. These advances improve our understanding of allosterism and promote allosteric drug discovery, thereby revolutionizing the shift from the traditional serendipitous route used to discover allosteric drugs to the updated path centered on rational structure-based design. In this review, recent advances in computational methods applied to allosteric drug discovery are summarized. We comprehensively review these achievements along various levels of allosteric events, from the construction of allosteric databases to the identification and analysis of allosteric residues, signals, sites, and modulators. We expect to increase the awareness of the discovery of allosteric drugs using structure-based computational methods.

Molecular Dynamics Simulations Establish the Molecular Basis for the Broad Allostery Hotspot Distributions in the Tetracycline Repressor

“…52 As discussed in the previous work, 52 mutation of allostery hotspots led to noninducible (dead) phenotypes, whose inducibility could be rescued by additional mutations; however, different dead mutants could be rescued with different numbers of mutations (i.e., the hotspots featured varying degrees of "rescuabilities"). For biomedical applications, therefore, a potential implication is that successful design of allostery inhibition 7,8 needs to target allostery hotspots that are particularly difficult to rescue, as otherwise allostery can be readily restored with additional mutations, leading to abolishment of inhibition. Evidently, a future endeavor is to develop computational methodologies that help not only to identify allostery hotspots but also to evaluate their rescuabilities, which are likely related to the degree that the underlying free energy landscape is perturbed by the hotspot mutations.…”

Harnessing Reversed Allosteric Communication: A Novel Strategy for Allosteric Drug Discovery

“…In contrast, extensive and efficient computational approaches have enabled us to overcome the limitations of experimental approaches. Structure-based computational approaches, such as molecular dynamics (MD) simulations, − FPocket (a pocket detection program), and Allosite (a program that uses SVM to predict protein allosteric sites), can predict potential allosteric sites by coupling the conformational and temporal features of protein complexes. Sequence-based computational approaches, such as statistical coupling analysis, can identify residues that act as evolutionary, structural, and functional sectors in a protein by probing the homology of the sequence, , providing ingenious insights into the prediction of allosteric sites.…”

Atomic-scale insights into allosteric inhibition and evolutional rescue mechanism of Streptococcus thermophilus Cas9 by the anti-CRISPR protein AcrIIA6

“…Taken together, our findings help elucidate the driving force behind the emergence of AcrIIA6 during the coevolution of bacteria and phages as well as the detailed mechanism of allosteric inhibition of St1Cas9 RNP by the anti-CRISPR protein AcrIIA6 [95] , [96] , [97] , [98] . The results provide a dynamic picture of this mechanism.…”