An Integrated Understanding of the Evolutionary and Structural Features of the SARS-CoV-2 Spike Receptor Binding Domain (RBD)

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Covid-19, Sars-cov-2, Receptor Binding Domain, Sequence Space Analysis, Co-evolution, Deep Mutation Scan, Molecular Dynamic Simulation, Structure Network Analysis, Fuzzy C-means Clustering, Druggability, Machine Learning

Digital Object Identifier (DOI)

International Journal of Biological Macromolecules


Conventional drug development strategies typically use pocket in protein structures as drug-target sites. They overlook the plausible effects of protein evolvability and resistant mutations on protein structure which in turn may impair protein-drug interaction. In this study, we used an integrated evolution and structure guided strategy to develop potential evolutionary-escape resistant therapeutics using receptor binding domain (RBD) of SARS-CoV-2 spike-protein/S-protein as a model. Deploying an ensemble of sequence space exploratory tools including co-evolutionary analysis and deep mutational scans we provide a quantitative insight into the evolutionarily constrained subspace of the RBD sequence-space. Guided by molecular simulation and structure network analysis we highlight regions inside the RBD, which are critical for providing structural integrity and conformational flexibility. Using fuzzy C-means clustering we combined evolutionary and structural features of RBD and identified a critical region. Subsequently, we used computational drug screening using a library of 1615 small molecules and identified one lead molecule, which is expected to target the identified region, critical for evolvability and structural stability of RBD. This integrated evolution-structure guided strategy to develop evolutionary-escape resistant lead molecules have potential general applications beyond SARS-CoV-2.

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Citation / Publisher Attribution

International Journal of Biological Macromolecules, v. 217, p. 492-505