ArticleFrontiers in cellular and infection microbiology2025
High-affinity optimization potential of the virus neutralizing antibody with twin cysteine-stabilized complementarity-determining region 3.
Article in Frontiers in cellular and infection microbiology, 2025. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The optimization of neutralizing monoclonal antibodies (NMAbs) is crucial to counter viral evolution. The structural stability of the heavy-chain complementarity-determining region 3 (H3 CDR) significantly influences affinity maturation potential, yet its impact on computational optimization remains unclear. Methods: This study employed an artificial intelligence (AI) model to optimize two categories of SARS-CoV-2 NMAbs: one featuring a conformationally stabilized H3 CDR via a twin cysteine motif, and another with flexible H3 CDR loops. Optimized antibody derivatives were evaluated for binding affinity to the SARS-CoV-2 spike protein, pseudovirus and live virus neutralization, and in vivo efficacy in a murine infection model. Structural analyses were conducted to elucidate interaction mechanisms with the angiotensin-converting enzyme 2 (ACE2) receptor. Results: H3 CDR stabilization via twin cysteines markedly enhanced AI-driven optimization efficacy. Optimized derivatives from the stabilized antibody category exhibited improved binding affinity and superior neutralization potency against both pseudotyped and authentic SARS-CoV-2 viruses. Structural analyses revealed optimized antibodies formed tighter interactions with the ACE2 receptor, including enhanced binding between key residues and ACE2, which correlated with biological efficacy. In contrast, antibodies lacking H3 CDR stabilization showed no affinity improvement after the same optimization process. In vivo, optimized antibodies effectively suppressed viral replication and reduced viral loads in infected mice. Mechanistically, the twin cysteine stabilization minimized structural perturbations caused by affinity-enhancing mutations, unlocking the optimization potential of the H3 CDR. Discussion: These findings establish that conformational stabilization of the H3 CDR in seed antibodies is a critical determinant for successful AI-driven affinity maturation. The study proposes a strategic framework for antibody development that prioritizes structurally stabilized H3 CDR regions, offering a robust approach to generating high-potency therapeutics against rapidly evolving viral pathogens.
Indexed as
Identifiers
What OpenQuestion holds
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.