Impact of M and E protein mutations in SARS-CoV-2 Omicron variants on reduced antibody binding and increased...

First identified in late 2021, the Omicron variant of SARS-CoV-2 accumulated substantially more mutations than previously circulating variants. This study investigated the genomic characteristics and structural consequences of mutations in the membrane (M) and envelope (E) proteins of dominant Omicron lineages circulating in southern Iran between March 2021 and March 2023.

A total of 528 clinical samples were analyzed using next-generation sequencing (NGS), Nextclade lineage assignment, and complementary bioinformatics approaches. The structural effects of selected mutations were further evaluated using protein-protein docking, PDBe PISA interface analysis, MM/GBSA binding free energy calculations, and 100-ns molecular dynamics simulations.

Between 2021 and 2023, BA.5.2 accounted for 32.4% of sequenced isolates, whereas XBB.1.9.1 became the predominant lineage during the later phase of the study (14.2%). Structural analysis demonstrated that the interaction interface between the M protein dimer and the Fab fragment remained largely conserved across all investigated variants. However, MM/GBSA calculations revealed mutation-dependent differences in binding energetics, with the BA.5 (Q19E, A38S, A63T) variant exhibiting the least favorable binding free energy despite preservation of the overall interaction interface. Molecular dynamics simulations further showed that the investigated E protein variants maintained compact conformations with reduced conformational fluctuations relative to the wild-type protein throughout the simulation.

Combined genomic surveillance and structural analyses demonstrated that the investigated Omicron-associated mutations largely preserved the overall architecture of the M protein-Fab interaction interface while modulating residue-level energetic contributions and the conformational dynamics of the E protein. These findings indicate that the investigated mutations primarily affect interaction energetics and protein dynamics rather than inducing major structural rearrangements. The integrated computational framework presented in this study provides a useful approach for evaluating the structural consequences of newly emerging SARS-CoV-2 variants and prioritizing mutations for future experimental validation.