Strömich, L. | bioRxiv Science

bioRxiv2021

Prediction of allosteric sites and signalling: insights from benchmarking datasets

AO_SCPLOWBSTRACTC_SCPLOWAllostery is a pervasive mechanism which regulates the activity of proteins in living systems through binding of a molecule at a distant site from the orthosteric site of the protein. The universality of allosteric regulation complemented by the benefits of highly specific, potentially non-toxic and protein activity modulating allosteric drugs makes uncovering allosteric sites on proteins invaluable for drug discovery. However, there are few computational methods to effectively predict them. Bond-to-bond propensity analysis, a recently developed method, has successfully predicted allosteric sites for a diverse group of proteins with only the knowledge of the orthosteric sites and the corresponding ligands in 19 of 20 cases. The method is based on an energy-weighted atomistic protein graph and allows for computationally highly efficient analysis in atomistic detail. We here extended the analysis onto 432 structures of 146 proteins from two existing benchmarking datasets for allosteric proteins: ASBench and CASBench. We further refined the metrics to account for the cumulative effect of residues with high propensities and the crucial residues in a given site with two additional measures. The allosteric site is recovered for 95/113 proteins (99/118 structures) from ASBench and 32/33 proteins (304/314 structures) from CASBench, with the only a priori knowledge being the orthosteric site residues. Knowing the orthosteric ligands of the protein, the allosteric site is identified for 32/33 proteins (308/314 structures) from CASBench.

bioinformatics↗

bioRxiv2020

Allosteric hotspots in the main protease of SARS-CoV-2

AO_SCPLOWBSTRACTC_SCPLOWInhibiting the main protease of SARS-CoV-2 is of great interest in tackling the COVID-19 pandemic caused by the virus. Most efforts have been centred on inhibiting the binding site of the enzyme. However, considering allosteric sites, distant from the active or orthosteric site, broadens the search space for drug candidates and confers the advantages of allosteric drug targeting. Here, we report the allosteric communication pathways in the main protease dimer by using two novel fully atomistic graph theoretical methods: Bond-to-bond propensity analysis, which has been previously successful in identifying allosteric sites without a priori knowledge in benchmark data sets, and, Markov transient analysis, which has previously aided in finding novel drug targets in catalytic protein families. We further score the highest ranking sites against random sites in similar distances through statistical bootstrapping and identify four statistically significant putative allosteric sites as good candidates for alternative drug targeting.

bioinformatics↗