ArticleNature communications2025
De novo design of epitope-specific antibodies via a structure-driven computational workflow.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed.
- Combining AI Structure Prediction and Integrative Modeling for Nanobody-Antigen Complexes.Journal of chemical information and modeling · 2026Article
- Review
- Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.Briefings in bioinformatics · 2026Review
- Evidence-aware comparison of sequence-centric machine learning for antibody discovery and optimization.Briefings in bioinformatics · 2026Article
- From Algorithms to Assets: A Comprehensive Review of AI's Role in Preclinical Drug Discovery and the Hurdles to Clinical Translation.Pharmaceuticals (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate modeling of antibody-antigen complex structures holds significant potential for advancing biomedical research and the design of therapeutic antibodies. Compared to general proteins, progress in antibody structure prediction and design has been slow, and antibody discovery is still based on time-consuming animal immunization or library screening methods. Here, we present tFold System, a high-throughput computational workflow that integrates antibody structure prediction (tFold-Ab), antibody-antigen complex modeling (tFold-Ag), structure-guided virtual screening, and de novo epitope-specific antibody design. Using this system, we de novo design monoclonal antibodies (mAbs) against four therapeutically relevant antigens: influenza hemagglutinin (Flu A), PD-1, PD-L1, and SARS-CoV-2 RBD (SC2RBD). Experimental validation by surface plasmon resonance (SPR) following high-throughput screening via phage display shows the designed antibodies achieve nanomolar binding affinities and precise epitope targeting, demonstrating the efficiency of the integrated computational-experimental pipeline. Our results demonstrate that tFold System overcomes key limitations of existing methods by enabling rapid, high-throughput antibody discovery against user-defined epitopes.
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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.