Structural Evolution of Delta (B.1.617.2) and Omicron (BA.1) Spike Glycoproteins

Cooperative and structural relationships of the trimeric Spike with infectivity and antibody escape of the strains Delta (B.1.617.2) and Omicron (BA.2, BA.5, and BQ.1)

Herein, we conducted simulations of trimeric Spike from several SARS-CoV-2 variants of concern (Delta and Omicron sub-variants BA.2, BA.5, and BQ.1) and investigated the mechanisms by which specific mutations confer resistance to neutralizing antibodies. We observed that the mutations primarily affect the cooperation between protein domains within and between protomers. The substitutions K417N and L452R expand hydrogen bonding interactions, reducing their interaction with neutralizing antibodies. By interacting with nearby residues, the K444T and N460K mutations in the SpikeBQ.1 variant potentially reduces solvent exposure, thereby promoting resistance to antibodies. We also examined the impact of D614G, P681R, and P681H substitutions on Spike protein structure that may be related to infectivity. The D614G substitution influences communication between a glycine residue and neighboring domains, affecting the transition between up- and -down RBD states. The P681R mutation, found in the Delta variant, enhances correlations between protein subunits, while the P681H mutation in Omicron sub-variants weakens long-range interactions that may be associated with reduced fusogenicity. Using a multiple linear regression model, we established a connection between inter-protomer communication and loss of sensitivity to neutralizing antibodies. Our findings underscore the importance of structural communication between protein domains and provide insights into potential mechanisms of immune evasion by SARS-CoV-2. Overall, this study deepens our understanding of how specific mutations impact SARS-CoV-2 infectivity and shed light on how the virus evades the immune system.

Effects of N-glycan modifications on spike expression, virus infectivity, and neutralization sensitivity in ancestral compared to Omicron SARS-CoV-2 variants

The SARS-CoV-2 spike glycoprotein has 22 potential N-linked glycosylation sites per monomer that are highly conserved among diverse variants, but how individual glycans affect virus entry and neutralization of Omicron variants has not been extensively characterized. Here we compared the effects of specific glycan deletions or modifications in the Omicron BA.1 and D614G spikes on spike expression, processing, and incorporation into pseudoviruses, as well as on virus infectivity and neutralization by therapeutic antibodies. We found that loss of potential glycans at spike residues N717 and N801 each conferred a loss of pseudovirus infectivity for Omicron but not for D614G or Delta variants. This decrease in infectivity correlated with decreased spike processing and incorporation into Omicron pseudoviruses. Oligomannose-enriched Omicron pseudoviruses generated in GnTI- cells or in the presence of kifunensine were non-infectious, whereas D614G or Delta pseudoviruses generated under similar conditions remained infectious. Similarly, growth of live (authentic) SARS-CoV-2 in the presence of kifunensine resulted in a greater reduction of titers for the BA.1.1 variant than Delta or D614G variants relative to their respective, untreated controls. Finally, we found that loss of some N-glycans, including N343 and N234, increased the maximum percent neutralization by the class 3 S309 monoclonal antibody against D614G but not BA.1 variants, while these glycan deletions altered the neutralization potency of the class 1 COV2-2196 and Etesevimab monoclonal antibodies without affecting maximum percent neutralization. The maximum neutralization by some antibodies also varied with the glycan composition, with oligomannose-enriched pseudoviruses conferring the highest percent neutralization. These results highlight differences in the interactions between glycans and residues among SARS-CoV-2 variants that can affect spike expression, virus infectivity, and susceptibility of variants to antibody neutralization.

Treatment-Emergent Cilgavimab Resistance Was Uncommon in Vaccinated Omicron BA.4/5 Outpatients

Mutations in the SARS-CoV-2 Spike glycoprotein can affect monoclonal antibody efficacy. Recent findings report the occurrence of resistant mutations in immunocompromised patients after tixagevimab/cilgavimab treatment. More recently, the Food and Drug Agency revoked the authorization for tixagevimab/cilgavimab, while this monoclonal antibody cocktail is currently recommended by the European Medical Agency. We retrospectively reviewed 22 immunocompetent patients at high risk for disease progression who received intramuscular tixagevimab/cilgavimab as early COVID-19 treatment and presented a prolonged high viral load. Complete SARS-CoV-2 genome sequences were obtained for a deep investigation of mutation frequencies in Spike protein before and during treatment. At seven days, only one patient showed evidence of treatment-emergent cilgavimab resistance. Quasispecies analysis revealed two different deletions on the Spike protein (S:del138-144 or S:del141-145) in combination with the resistance S:K444N mutation. The structural and dynamic impact of the two quasispecies was characterized by using molecular dynamics simulations, showing the conservation of the principal functional movements in the mutated systems and their capabilities to alter the structure and dynamics of the RBD, responsible for the interaction with the ACE2 human receptor. Our study underlines the importance of prompting an early virological investigation to prevent drug resistance or clinical failures in immunocompetent patients.

MD-Ligand-Receptor: A High-Performance Computing Tool for Characterizing Ligand-Receptor Binding Interactions in Molecular Dynamics Trajectories

Molecular dynamics simulation is a widely employed computational technique for studying the dynamic behavior of molecular systems over time. By simulating macromolecular biological systems consisting of a drug, a receptor and a solvated environment with thousands of water molecules, MD allows for realistic ligand-receptor binding interactions (lrbi) to be studied. In this study, we present MD-ligand-receptor (MDLR), a state-of-the-art software designed to explore the intricate interactions between ligands and receptors over time using molecular dynamics trajectories. Unlike traditional static analysis tools, MDLR goes beyond simply taking a snapshot of ligand-receptor binding interactions (lrbi), uncovering long-lasting molecular interactions and predicting the time-dependent inhibitory activity of specific drugs. With MDLR, researchers can gain insights into the dynamic behavior of complex ligand-receptor systems. Our pipeline is optimized for high-performance computing, capable of efficiently processing vast molecular dynamics trajectories on multicore Linux servers or even multinode HPC clusters. In the latter case, MDLR allows the user to analyze large trajectories in a very short time. To facilitate the exploration and visualization of lrbi, we provide an intuitive Python notebook (Jupyter), which allows users to examine and interpret the results through various graphical representations.

The Spike Mutants Website: A Worldwide Used Resource against SARS-CoV-2

A large number of SARS-CoV-2 mutations in a short period of time has driven scientific research related to vaccines, new drugs, and antibodies to combat the new variants of the virus. Herein, we present a web portal containing the structural information, the tridimensional coordinates, and the molecular dynamics trajectories of the SARS-CoV-2 spike protein and its main variants. The Spike Mutants website can serve as a rapid online tool for investigating the impact of novel mutations on virus fitness. Taking into account the high variability of SARS-CoV-2, this application can help the scientific community when prioritizing molecules for experimental assays, thus, accelerating the identification of promising drug candidates for COVID-19 treatment. Below we describe the main features of the platform and illustrate the possible applications for speeding up the drug discovery process and hypothesize new effective strategies to overcome the recurrent mutations in SARS-CoV-2 genome.