Identification of discontinuous antigenic determinants on proteins based on shape complementarities
Abstract
Diverse procedures for identifying antigenic determinants on proteins have been developed, including experimental as well as computational approaches. However, most of these techniques focus on continuous epitopes, whereas fast and reliable identification and verification of discontinuous epitopes remains barely amenable. In this paper, we describe a computational workflow for the detection of discontinuous epitopes on proteins. The workflow uses a given protein 3D structure as input, and combines a per residue solvent accessibility constraint with epitope to paratope shape complementarity measures and binding energies for assigning antigenic determinants in the conformational context. We have developed the procedure on a given set of 26 antigen-antibody complexes with a known structure, and have further expanded the available paratope shapes by generating a virtual paratope library in order to improve the screening for candidate residues constituting discontinuous epitopes. Applying the workflow on the 26 given antigens with known discontinuous epitopes resulted in the correct identification of the spatial proximity of 12 antigen-antibody interaction sites. Combining solvent accessibility, shape complementarity and binding energies towards the identification of discontinuous epitopes clearly outperforms approaches solely considering accessibility and residue distance constraints.
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Arbitrary molecular surfaces appear to be indistinguishable from epitope regions, suggesting that predictions should be performed with reference to a particular antibody.
“However, arbitrary molecular surfaces appear to be indistinguishable from epitope regions [167–169] suggesting that predictions should be performed with reference to a particular antibody [116, 118–120].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [116]
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- Authors
- Rapberger, R., Lukas, A., & Mayer, B.
- Affiliations
- University of Vienna (AT)
- EmergenTec (Austria) (AT)
- Corresponding author
- Mayer, Bernd
- Venue
- Journal of Molecular Recognition
- Publisher
- Wiley
- Published
- 2007-03
- Volume
- 20
- Issue
- 2
- Pages
- 113-121
- ISSN
- 0952-3499 (ISSN-L)
- 1099-1352
- OpenAlex
- W2013366764
- Cited by
- 31
- References
- 44
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 1 · 2020: 2 · 2019: 2 · 2018: 1 · 2017: 2 · 2016: 1 · 2015: 3 · 2014: 2 · 2013: 5 · 2012: 3
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Molecular Recognition (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- conformational epitopes, antigenic determinants, immune complexes, solvent accessibility, binding energy, epitope prediction, protein 3D structure
- MeSH terms
- Algorithms, Antigen-Antibody Complex, Epitopes, Binding Sites, Antibody, Models, Molecular, Protein Binding, Protein Structure, Tertiary, Protein Folding, Computational Biology, Imaging, Three-Dimensional
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