H3-OPT: Accurate prediction of CDR-H3 loop structures of antibodies with deep learning
Open accessPreprint — published as 10.7554/elife.91512 · Paper page
Abstract
Accurate prediction of the structurally diverse complementarity determining region heavy chain 3 (CDR-H3) loop structure remains a primary and long-standing challenge for antibody modeling. Here, we present the H3-OPT toolkit for predicting the 3D structures of monoclonal antibodies and nanobodies. H3-OPT combines the strengths of AlphaFold2 with a pre-trained protein language model, and provides a 2.24 Å average RMSD Cα between predicted and experimentally determined CDR-H3 loops, thus outperforming other current computational methods in our non-redundant high-quality dataset. The model was validated by experimentally solving three structures of anti-VEGF nanobodies predicted by H3-OPT. We examined the potential applications of H3-OPT through analyzing antibody surface properties and antibody-antigen interactions. This structural prediction tool can be used to optimize antibody-antigen binding, and to engineer therapeutic antibodies with biophysical properties for specialized drug administration route.
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- Authors
- Chen, H., Fan, X., Zhu, S., Pei, Y., Zhang, X., Zhang, X., Liu, L., Qian, F., & Tian, B.
- Affiliations
- State Key Laboratory of Molecular Oncology (CN)
- Tsinghua University (CN)
- Baidu (China) (CN)
- Corresponding author
- Qian, Feng
- Tian, Boxue
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2023-08-21
- OpenAlex
- W4386023377
- Cited by
- 1
- References
- 13
- Citations by year
- 2026: 1
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Funders
- Tsinghua University (20231080030, 20221080048)
- Peking University
- Peking Union Medical College
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- monoclonal antibodies, nanobodies, AlphaFold2, protein language models, antigen-antibody reaction
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