Impact of M and E protein mutations in SARS-CoV-2 Omicron variants on reduced antibody binding and increased structural stability: a bioinformatics study (2021-2023).

Structural and functional dissection of neutralisation differences among SARS-CoV-2 variants using antigenicity prediction and CR3022 binding analysis

A combined experimental and computational characterization of SARS-CoV-2 variant-specific neutralisation across infection, vaccination and hybrid immunity-driven cohorts is provided, offering a hypothesis-generating framework to contextualize observed differences in antibody responses and epitope recognition across variants.

Emergence of Lineage E.4 and Structural Plasticity of A28L Protein in Mpox Virus: Characterization of LCR7 Length Polymorphisms Across Lineages — Shenzhen City, Guangdong Province, China, 2023–2025

Structural variation in A28L provides additional insight into MPXV evolution beyond conventional single-nucleotide analyses, and continued surveillance of these genomic features may improve monitoring of viral transmission and the emergence of new variants.

The emergence of putative epistatic mutations and iSNVs in SARS-CoV-2 XBB.1.16 variants linked with alteration in immunogenic determinants

Higher order protein structural predictions suggested that the putative epistatic interactions among E180V, G184V, and G252V, D253G may be associated with S protein folding and structural stability.

Bioinformatics study of the a222V substitution in sars-cov-2 spike protein

Allosteric effects of CDR-H3 mutations modulate binding and neutralization of a conserved SARS-CoV-2 RBD-targeting antibody

ABSTRACT SARS-CoV-2 antigenic evolution continues to erode the activity of first-generation monoclonal antibodies, underscoring the value of antibodies that recognize conserved features within the spike receptor-binding domain (RBD). As a model for breadth-oriented engineering, we assessed the RBD-directed antibody XG83, which has a CDRH3-dominated paratope. Utilizing the XG83-Wuhan RBD crystal structure as a reference, we integrated MOE alanine scanning and residue scanning with CDRH3 (A116-Y132) to identify chemically reasonable replacements and test interaction to an Omicron BA.1 RBD. The parental CDRH3-centric pose in comparative docking had a better score (−280.18) than the mutant MuXG83 (−254.2), along with 100-ns molecular dynamics showed that MuXG83 was less stable (with higher RMSD/RMSF with less favorable interaction energy). The ELISA results against Omicron BA.1 RBD demonstrated that XG83 had 40% stronger binding than MuXG83; convergence happened only at the highest concentration, concordant with SPR studies and the fact that mutation increased dissociation. According to this binding gap, BA.1 pseudovirus neutralization demonstrated that XG83 was much more powerful than MuXG83, showing that the E118L/F130H CDR-H3 alterations decreased functional activity against Omicron BA.1. These results imply that allosteric influences on interface stability and conformational dynamics by non-epitope CDR-H3 residues can affect antibody performance. Functional testing was confined to Omicron BA.1; therefore, larger variant-panel studies are needed to ascertain if such mutations affect antibody breadth. Our findings highlight a structure-guided approach for optimizing paratopes and indicate that non-epitope (potentially allosteric) changes to CDRH3 are also important while investigating potential development and neutralization before advancement. IMPORTANCE This study shows how modest allosteric characteristics in CDR-H3 control the delicate balance between neutralizing potency and breadth, making a timely and significant addition to SARS-CoV-2 antibody engineering. Using crystallography, alanine scanning, residue scanning, docking, molecular dynamics, and experimental ELISA and neutralization assays, this study offers a structure-guided framework for rational paratope optimization. The discovery of CDR-H3 residues that regulate long-range stability rather than just direct epitope contacts reveals an unappreciated aspect of antibody design and explains why some alterations improve anticipated interactions but degrade functional performance. Importantly, the comparison of wild-type XG83 and modified MuXG83 shows how allosteric tuning affects antibody-antigen compatibility in developing variations like Omicron. These findings illuminate conserved RBD recognition and offer strategies for building next-generation therapeutic antibodies that are more resistant to viral evolution. This study shows how modest allosteric characteristics in CDR-H3 control the delicate balance between neutralizing potency and breadth, making a timely and significant addition to SARS-CoV-2 antibody engineering. Using crystallography, alanine scanning, residue scanning, docking, molecular dynamics, and experimental ELISA and neutralization assays, this study offers a structure-guided framework for rational paratope optimization. The discovery of CDR-H3 residues that regulate long-range stability rather than just direct epitope contacts reveals an unappreciated aspect of antibody design and explains why some alterations improve anticipated interactions but degrade functional performance. Importantly, the comparison of wild-type XG83 and modified MuXG83 shows how allosteric tuning affects antibody-antigen compatibility in developing variations like Omicron. These findings illuminate conserved RBD recognition and offer strategies for building next-generation therapeutic antibodies that are more resistant to viral evolution.

Helicase Mutations in United States Isolates of SARS-CoV-2 Altered Protein Stability and Binding Dynamics

Severe Acute Respiratory Syndrome Coronavirus-2, which causes Coronavirus 2019, has resulted in the deaths of more than 7 million people. The helicase, encoded by non-structural protein-13 in the virus genome, plays a critical role in the virus's life cycle and is at the heart of treatment approaches. The study revealed the impact of helicase protein mutations on protein stability and nucleic acid binding dynamics in United States SARS-CoV-2 isolates. Nine recurrent mutations exceeding the predefined occurrence threshold were identified and subjected to structural modeling, protein stability prediction, and helicase–nucleic acid docking analysis. Utilizing data from nine mutations (Ser36Pro, Thr127Asn, His164Tyr, Met233Ile, Tyr324Cys, Ala368Val, Ala389Val, Arg392Cys, Thr599Ile) identified from isolates, mutant protein models were generated using deep learning algorithms. Protein stability alterations were assessed using SDM2, mCSM, DUET, and DynaMut2 tools. The helicase-nucleic acid interaction was evaluated through molecular docking analysis. Consensus-based stability prediction indicated that several mutations were predicted to reduce nsp13 stability, whereas His164Tyr was consistently predicted to have a stabilizing effect across all four tools. Some substitutions, including Met233Ile and Thr599Ile, showed method-dependent effects. Molecular docking analysis suggested that the recurrent mutation set may alter helicase–RNA interface energetics and spatial arrangement. However, these docking-derived changes should be interpreted as computational estimates rather than direct evidence of increased nucleic acid-binding affinity. The concurrent occurrence of reduced predicted protein stability and more favorable docking-derived nucleic acid interface scores suggests that these mutations may influence helicase–nucleic acid recognition; however, direct effects on viral replication kinetics require experimental validation.