Cited by 382Protein Structure and DynamicsMonoclonal and Polyclonal Antibodies ResearchEnzyme Structure and Function

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A New Clustering of Antibody CDR Loop Conformations

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North, Benjamin, Lehmann, Andreas, Dunbrack, Roland L.·2011·Journal of Molecular Biology

DOI 10.1016/j.jmb.2010.10.030PMC PMC3065967

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Abstract

Previous analyses of the complementarity-determining regions (CDRs) of antibodies have focused on a small number of "canonical" conformations for each loop. This is primarily the result of the work of Chothia and coworkers, most recently in 1997. Because of the widespread utility of antibodies, we have revisited the clustering of conformations of the six CDR loops with the much larger amount of structural information currently available. In this work, we were careful to use a high-quality data set by eliminating low-resolution structures and CDRs with high B-factors or high conformational energies. We used a distance function based on directional statistics and an effective clustering algorithm with affinity propagation. With this data set of over 300 nonredundant antibody structures, we were able to cover 28 CDR-length combinations (e.g., L1 length 11, or "L1-11" in our CDR-length nomenclature) for L1, L2, L3, H1, and H2. The Chothia analysis covered only 20 CDR-lengths. Only four of these had more than one conformational cluster, of which two could easily be distinguished by gene source (mouse/human; κ/λ) and one could easily be distinguished purely by the presence and the positions of Pro residues (L3-9). Thus, using the Chothia analysis does not require the complicated set of "structure-determining residues" that is often assumed. Of our 28 CDR-lengths, 15 have multiple conformational clusters, including 10 for which the Chothia analysis had only one canonical class. We have a total of 72 clusters for non-H3 CDRs; approximately 85% of the non-H3 sequences can be assigned to a conformational cluster based on gene source and/or sequence. We found that earlier predictions of "bulged" versus "nonbulged" conformations based on the presence or the absence of anchor residues Arg/Lys94 and Asp101 of H3 have not held up, since all four combinations lead to a majority of conformations that are bulged. Thus, the earlier analyses have been significantly enhanced by the increased data. We believe that the new classification will lead to improved methods for antibody structure prediction and design.

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Authors: North, B., Lehmann, A., & Dunbrack, R. L.
Affiliations: Fox Chase Cancer Center (US)
Corresponding author: Dunbrack, Roland L.
ORCID: Lehmann, Andreas
Dunbrack, Roland L.
Venue: Journal of Molecular Biology
Publisher: Elsevier BV
Published: 2011-02
Volume: 406
Issue: 2
Pages: 228-256
ISSN: 0022-2836 (ISSN-L)
DOI: 10.1016/j.jmb.2010.10.030
PMC: PMC3065967
OpenAlex: W1978499958
Cited by: 380
References: 38
Citations by year: 2026: 12 · 2025: 14 · 2024: 24 · 2023: 22 · 2022: 24 · 2021: 29 · 2020: 33 · 2019: 39 · 2018: 25 · 2017: 29 · 2016: 24 · 2015: 27 · 2014: 40 · 2013: 15 · 2012: 11
FWCI: 4.95
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Journal of Molecular Biology (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
Funders: National Cancer Institute (T32CA009035)
National Institute of General Medical Sciences (R01-GM84453, P20 GM76222, P20GM076222, R01GM084453)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
Keywords: hypervariable region, conformational clustering, circular statistics, affinity propagation, antibody structure prediction, antibody design
MeSH terms: Algorithms, Amino Acid Sequence, Animals, Antibodies, Humans, Immunoglobulin Variable Region, Immunoglobulin Heavy Chains, Markov Chains, Molecular Sequence Data, Protein Conformation, Complementarity Determining Regions, Mice

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A New Clustering of Antibody CDR Loop Conformations

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