ArticleResearch square2026
Structure-Guided Design of Therapeutic Antibodies Targeting SARS-CoV-2 Omicron Variants.
Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The ongoing evolution of SARS-CoV-2, particularly the emergence of Omicron subvariants, compromised the effectiveness of many therapeutic antibodies. In this study, we employed a structure-guided computational design strategy to systematically optimize the COV2-2196 antibody for improved neutralization of Omicron variants. Through iterative rounds of computational design and experimental validation, we identified key paratope mutations that restored and enhanced antibody binding and neutralization potency against resistant viral strains. Cryo-EM structural analysis revealed the molecular basis for these improvements, highlighting how targeted modifications can accommodate epitope changes introduced by viral evolution. Our approach demonstrates that effective antibody optimization can be achieved using accessible computational resources, providing a practical framework for rapid therapeutic development. These findings underscore the potential of structure-based design to address challenges posed by viral antigenic drift and support the development of broadly effective antibody therapeutics for emerging infectious diseases.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.