tetano
Editor, Senior Moderator
J Biomol Struct Dyn
. 2026 Oct 6:1-28.
doi: 10.1080/07391102.2026.2741688. Online ahead of print.
Areesha Irshad 1 , Atta Ur-Rehman 1 , Taskeen Koser 1 , Mudasir Alvi 1 , Hunza Usman 1 , Rana Rehan Khalid 1
Affiliations Expand
The rapid emergence of SARS-CoV-2 has renewed interest in cross-reactive antibody therapeutics targeting conserved epitopes across divergent coronaviruses. Building on our deep-learning driven protein engineering pipeline, we sought to redirect experimentally validated MERS-CoV antibodies toward the SARS-CoV-2 receptor-binding domain. A structural comparison identified a conserved Site 2 epitope capable of supporting cross-neutralizing interactions and three MERS-CoV antibodies showing measurable compatibility with this region were selected as templates. Using the customized ProteinMPNN based design framework, with multi-parameter biophysical filtering, we introduced context-specific substitutions to strengthen interfacial complementarity with the SARS-CoV-2 RBD. The study extends our earlier workflow by adding two evaluation parameters, antigen processing and T cell immunogenicity, to assess mutational impact on developability and immune compatibility. Top-ranked variants underwent molecular dynamics simulations and post-trajectory analyses, including stability profiling, hydrogen-bond and hydrophobic network evaluation, and per-residue binding energetics. Developability assessments, including aggregation propensity and immunogenicity profiling, were integrated to ensure therapeutic readiness. Across all scaffolds, several engineered variants, most notably D12(T721E), MERS27(D722N), and JC57-14(S618G), exhibited enhanced interface organization, favorable energy landscapes, and can improved structural stability relative to their parental antibodies. Many also showed reduced aggregation potential and lower predicted antigen presentation across MHC class I and II alleles, further refined by the added processing and immunogenicity metrics. Together, these findings suggest that MERS-CoV antibody scaffolds can be repurposed to target SARS-CoV-2 through a conserved epitope, highlighting a promising strategy for broad-spectrum coronavirus antibodies and providing strengthened leads for experimental development.
Keywords: Antibody design; SARS-CoV-2 receptor-binding domain; coronavirus cross-reactivity; deep learning; molecular dynamics.
. 2026 Oct 6:1-28.
doi: 10.1080/07391102.2026.2741688. Online ahead of print.
Integrating deep learning model for precision design of MERS antibodies with augmented affinity against SARS-CoV-2
Areesha Irshad 1 , Atta Ur-Rehman 1 , Taskeen Koser 1 , Mudasir Alvi 1 , Hunza Usman 1 , Rana Rehan Khalid 1
Affiliations Expand
- PMID: 42836566
- DOI: 10.1080/07391102.2026.2741688
Abstract
The rapid emergence of SARS-CoV-2 has renewed interest in cross-reactive antibody therapeutics targeting conserved epitopes across divergent coronaviruses. Building on our deep-learning driven protein engineering pipeline, we sought to redirect experimentally validated MERS-CoV antibodies toward the SARS-CoV-2 receptor-binding domain. A structural comparison identified a conserved Site 2 epitope capable of supporting cross-neutralizing interactions and three MERS-CoV antibodies showing measurable compatibility with this region were selected as templates. Using the customized ProteinMPNN based design framework, with multi-parameter biophysical filtering, we introduced context-specific substitutions to strengthen interfacial complementarity with the SARS-CoV-2 RBD. The study extends our earlier workflow by adding two evaluation parameters, antigen processing and T cell immunogenicity, to assess mutational impact on developability and immune compatibility. Top-ranked variants underwent molecular dynamics simulations and post-trajectory analyses, including stability profiling, hydrogen-bond and hydrophobic network evaluation, and per-residue binding energetics. Developability assessments, including aggregation propensity and immunogenicity profiling, were integrated to ensure therapeutic readiness. Across all scaffolds, several engineered variants, most notably D12(T721E), MERS27(D722N), and JC57-14(S618G), exhibited enhanced interface organization, favorable energy landscapes, and can improved structural stability relative to their parental antibodies. Many also showed reduced aggregation potential and lower predicted antigen presentation across MHC class I and II alleles, further refined by the added processing and immunogenicity metrics. Together, these findings suggest that MERS-CoV antibody scaffolds can be repurposed to target SARS-CoV-2 through a conserved epitope, highlighting a promising strategy for broad-spectrum coronavirus antibodies and providing strengthened leads for experimental development.
Keywords: Antibody design; SARS-CoV-2 receptor-binding domain; coronavirus cross-reactivity; deep learning; molecular dynamics.