The SARS-CoV-2 Spike protein needs to be in an open-state conformation to interact with ACE2 to initiate viral entry. We utilise coarse-grained normal mode analysis to model the dynamics of Spike and calculate transition probabilities between states for 17081 variants including experimentally observed variants. Our results correctly model an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state. We predict the same effect for several mutations on glycine residues (404, 416, 504, 252) as well as residues K417, D467 and N501, including the N501Y mutation recently observed within the B.1.1.7, 501.V2 and P1 strains. This is, to our knowledge, the first use of normal mode analysis to model conformational state transitions and the effect of mutations on such transitions. The specific mutations of Spike identified here may guide future studies to increase our understanding of SARS-CoV-2 infection mechanisms and guide public health in their surveillance efforts. Author summary The present work explores the molecular mechanisms underlying and potentially helping new strains of SARS-CoV-2 to gain an evolutionary advantage during the ongoing COVID-19 pandemics. We show how a computational method called normal mode analysis that treats protein dynamics in a simplified manner is capable to predict the higher propensity of the Spike protein to be in the open state in which it is capable to interact with the human ACE2 receptor and thus facilitate cell entry. Because the simulation of the simplified computational model is relatively less demanding on resources than alternative methods, we were able to simulate over 17000 mutations in the SARS-CoV-2 Spike protein to identify multiple mutations that if they were to appear as the virus continues to evolve, could confer an evolutionary advantage. As a matter of fact, our predictions foresaw the emergence of particular mutations such as N501Y that appeared in several variants of concern. Our results can inform public health regarding new variants and serves as a proof of concept for the application of normal mode analysis to study the effect of mutations on both, protein dynamics and conformational transitions in a high-throughput manner.
【초록키워드】 COVID-19, public health, SARS-CoV-2, ACE2, Mutation, spike, knowledge, SARS-COV-2 infection, variant, molecular mechanism, virus, viral entry, variants, Spike protein, Protein, Simulation, Viral, Surveillance, B.1.1.7, N501Y, SARS-CoV-2 spike protein, Pandemics, D614G, N501Y mutation, resource, Strains, predict, mechanism, flexibility, open, glycine, alternative methods, proof of concept, 501.V2, residue, cell entry, molecular mechanisms, new strain, treat, several variants, human ACE2 receptor, computational method, K417, matter, multiple mutations, normal mode analysis, proof, residues, specific mutations, transition probabilities, helping, decrease, identify, facilitate, less, conformational, increase in, specific mutation, the Spike, multiple mutation, calculate, several variant, the SARS-CoV-2, transition probability, 【제목키워드】 SARS-CoV-2, spike, variant, Infection, Protein, conformational,