Landscape-Based Mutational Sensitivity Cartography and Network Community Analysis of the SARS-CoV-2 Spike Protein Structures: Quantifying Functional Effects of the Circulating Variants

Abstract

Structural and biochemical studies SARS-CoV-2 spike mutants with the enhanced infectivity have attracted significant attention and offered several mechanisms to explain the experimental data. In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined atomistic simulations, deep mutational scanning and sensitivity mapping together with the network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Conformational dynamics and analysis of collective motions in the SARS-CoV-2 spike proteins demonstrated that the D614 position anchors a key regulatory cluster that dictates functional transitions between open and closed states. Using mutational scanning and sensitivity analysis of the spike residues, we identified the evolution of stability hotspots in the SARS-CoV-2 spike structures of the mutant trimers. The results offer support to the reduced shedding mechanism of as a driver of the increased infectivity triggered by the D614G mutation. By employing the landscape-based network community analysis of the SARS-CoV-2 spike proteins, our results revealed that the D614G mutation can promote the increased number of stable communities in the open form by enhancing the stability of the inter-domain interactions. This study provides atomistic view of the interactions and stability hotspots in the SARS-CoV-2 spike proteins, offering a useful insight into the molecular mechanisms of the D614G mutation that can exert its functional effects through allosterically induced changes on stability of the residue interaction networks.