Integrating deep learning model for precision design of MERS antibodies with augmented affinity against SARS-CoV-2

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.

Authors

Institutions

Publication Details

Journal
Journal of Biomolecular Structure and Dynamics
Published
2026-10-06
DOI
https://doi.org/10.1080/07391102.2026.2741688
Primary Topic
SARS-CoV-2 and COVID-19 Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating deep learning model for precision design of MERS antibodies with augmented affinity against SARS-CoV-2

Rana Rehan Khalid, Atta Ur-Rehman, Taskeen Koser, Areesha Irshad et al.
Journal of Biomolecular Structure and Dynamics
SARS-CoV-2 and COVID-19 Research
article

Integrating deep learning model for precision design of MERS antibodies with augmented affinity against SARS-CoV-2

Rana Rehan Khalid, Atta Ur-Rehman, Taskeen Koser, Areesha Irshad, Mudasir Alvi, Hunza Usman
article en

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.

Journal of Biomolecular Structure and Dynamics
Quaid-i-Azam University (PK)
Openalex Percentile: Top 11%
SARS-CoV-2 and COVID-19 Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.