Antibody H3 structure prediction
Open accessAbstract
Antibodies are proteins of the immune system that are able to bind to a huge variety of different substances, making them attractive candidates for therapeutic applications. Antibody structures have the potential to be useful during drug development, allowing the implementation of rational design procedures. The most challenging part of the antibody structure to experimentally determine or model is the H3 loop, which in addition is often the most important region in an antibody's binding site. This review summarises the approaches used so far in the pursuit of accurate computational H3 structure prediction.
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Knowledge-based methods are currently capable of providing accurate predictions for the five canonical CDR loops.
“Knowledge-based methods are currently capable of providing accurate predictions for the five canonical loops, but CDRH3 remains a challenge [156].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [156]
CDRH3 remains a challenge for knowledge-based CDR loop modelling.
“Knowledge-based methods are currently capable of providing accurate predictions for the five canonical loops, but CDRH3 remains a challenge [156].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [156]
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Computational approaches to therapeutic antibody design: established methods and emerging trends
Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219 · see citing works
“Knowledge-based methods are currently capable of providing accurate predictions for the five canonical loops, but CDRH3 remains a challenge [156].”
MethodJain, T., Boland, T., Lilov, A., Burnina, I., Brown, M., Xu, Y., & Vásquez, M. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx519 · Cited by 61 · see citing works
- Authors
- Marks, C., & Deane, C. M.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Marks, C.
- ORCID
- Venue
- Computational and Structural Biotechnology Journal
- Published
- 2017-01
- Volume
- 15
- Pages
- 222-231
- ISSN
- 2001-0370 (ISSN-L)
- PMC
- PMC5312500
- OpenAlex
- W2583289470
- Cited by
- 56
- References
- 88
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 9 · 2023: 8 · 2022: 4 · 2021: 10 · 2020: 6 · 2019: 5 · 2018: 8 · 2017: 3
- FWCI
- 0.56
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computational and Structural Biotechnology Journal (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Engineering and Physical Sciences Research Council (EP/G037280/1)
- UCB Pharma Ltd.
- Roche
- 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
- antibody structure prediction, antibody binding sites, therapeutic antibodies, rational antibody design, computational protein structure prediction
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