Antibody modeling assessment II. Structures and models
Abstract
To assess the state‐of‐the‐art in antibody structure modeling, a blinded study was conducted. Eleven unpublished Fab crystal structures were used as a benchmark to compare Fv models generated by seven structure prediction methodologies. In the first round, each participant submitted three non‐ranked complete Fv models for each target. In the second round, CDR‐H3 modeling was performed in the context of the correct environment provided by the crystal structures with CDR‐H3 removed. In this report we describe the reference structures and present our assessment of the models. Some of the essential sources of errors in the predictions were traced to the selection of the structure template, both in terms of the CDR canonical structures and VL/VH packing. On top of this, the errors present in the Protein Data Bank structures were sometimes propagated in the current models, which emphasized the need for the curated structural database devoid of errors. Modeling non‐canonical structures, including CDR‐H3, remains the biggest challenge for antibody structure prediction. Proteins 2014; 82:1563–1582. © 2014 Wiley Periodicals, Inc.
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MSAs of homologous proteins are not always available, such as with orphan proteins or fast-evolving proteins like antibodies.
“However, MSAs of homologous proteins are not always available, such as with orphan proteins or fast-evolving proteins like antibodies, and a protein typically folds in a natural setting from its primary amino acid sequence into its three-dimensional structure, suggesting that evolutionary information and MSAs should not be necessary to predict a protein's folded form.”
From High-resolution <i>de novo</i> structure prediction from primary sequence (2022) · cites this paper as [39]
Antibody complementarity-determining regions (CDRs) are the most diverse and variable parts of the molecules.
“Antibody complementarity-determining regions (CDRs) are the most diverse and variable parts of the molecules (38,39).”
From High-resolution <i>de novo</i> structure prediction from primary sequence (2022) · cites this paper as [39]
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- Authors
- Teplyakov, A., Luo, J., Obmolova, G., Malia, T. J., Sweet, R., Stanfield, R. L., Kodangattil, S., Almagro, J. C., & Gilliland, G. L.
- Affiliations
- Janssen Research & Development (United States) (US)
- Scripps Research Institute (US)
- Pfizer (United States) (US)
- Corresponding author
- Teplyakov, Alexey
- ORCID
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2014-03-31
- Volume
- 82
- Issue
- 8
- Pages
- 1563-1582
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2159599720
- Cited by
- 72
- References
- 50
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 6 · 2022: 8 · 2021: 3 · 2020: 9 · 2019: 5 · 2018: 1 · 2017: 11 · 2016: 6 · 2015: 7 · 2014: 8
- FWCI
- 4.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Keywords
- antibody structure prediction, Fab crystal structure
- MeSH terms
- Amino Acid Sequence, Animals, Humans, Immunoglobulin Variable Region, Immunoglobulin Heavy Chains, Immunoglobulin Light Chains, Isomerism, Models, Molecular, Molecular Sequence Data, Protein Conformation, Crystallography, X-Ray, Complementarity Determining Regions, Databases, Protein
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