University of Massachusetts Medical School Faculty Publications
Title
An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants
UMMS Affiliation
Program in Bioinformatics and Integrative Biology
Publication Date
2021-01-29
Document Type
Article
Disciplines
Amino Acids, Peptides, and Proteins | Bioinformatics | Computational Biology | Structural Biology
Abstract
Accurate predictive modeling of antibody-antigen complex structures and structure-based antibody design remain major challenges in computational biology, with implications for biotherapeutics, immunity, and vaccines. Through a systematic search for high-resolution structures of antibody-antigen complexes and unbound antibody and antigen structures, in conjunction with identification of experimentally determined binding affinities, we have assembled a non-redundant set of test cases for antibody-antigen docking and affinity prediction. This benchmark more than doubles the number of antibody-antigen complexes and corresponding affinities available in our previous benchmarks, providing an unprecedented view of the determinants of antibody recognition and insights into molecular flexibility. Initial assessments of docking and affinity prediction tools highlight the challenges posed by this diverse set of cases, which includes camelid nanobodies, therapeutic monoclonal antibodies, and broadly neutralizing antibodies targeting viral glycoproteins. This dataset will enable development of advanced predictive modeling and design methods for this therapeutically relevant class of protein-protein interactions.
Keywords
affinity prediction, antibody design, biotherapeutics, monoclonal antibodies, nanobody, protein-protein docking, viruses
DOI of Published Version
10.1016/j.str.2021.01.005
Source
Guest JD, Vreven T, Zhou J, Moal I, Jeliazkov JR, Gray JJ, Weng Z, Pierce BG. An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants. Structure. 2021 Jan 29:S0969-2126(21)00005-8. doi: 10.1016/j.str.2021.01.005. Epub ahead of print. PMID: 33539768. Link to article on publisher's site
Related Resources
Journal/Book/Conference Title
Structure (London, England : 1993)
PubMed ID
33539768
Repository Citation
Guest JD, Vreven T, Zhou J, Moal I, Jeliazkov JR, Gray JJ, Weng Z, Pierce BG. (2021). An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants. University of Massachusetts Medical School Faculty Publications. https://doi.org/10.1016/j.str.2021.01.005. Retrieved from https://escholarship.umassmed.edu/faculty_pubs/1943