Maximum entropy models for antibody diversity

Recognition of pathogens relies on families of proteins showing great diversity. Here we construct maximum entropy models of the sequence repertoire, building on recent experiments that provide a nearly exhaustive sampling of the IgM sequences in zebrafish. These models are based solely on pairwise...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS Vol. 107; no. 12; p. 5405
Main Authors: Mora, Thierry, Walczak, Aleksandra M, Bialek, William, Callan, Jr, Curtis G
Format: Journal Article
Language:English
Published: United States 23.03.2010
Subjects:
Amino Acid Sequence
Animals
Antibody Diversity
Base Sequence
Biophysical Phenomena
DNA - chemistry
DNA - genetics
Entropy
Evolution, Molecular
Immunoglobulin M - chemistry
Immunoglobulin M - genetics
Models, Immunological
Zebrafish - genetics
Zebrafish - immunology
Zebrafish Proteins - chemistry
Zebrafish Proteins - genetics
ISSN:1091-6490, 1091-6490
Online Access:Get more information
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Summary:Recognition of pathogens relies on families of proteins showing great diversity. Here we construct maximum entropy models of the sequence repertoire, building on recent experiments that provide a nearly exhaustive sampling of the IgM sequences in zebrafish. These models are based solely on pairwise correlations between residue positions but correctly capture the higher order statistical properties of the repertoire. By exploiting the interpretation of these models as statistical physics problems, we make several predictions for the collective properties of the sequence ensemble: The distribution of sequences obeys Zipf's law, the repertoire decomposes into several clusters, and there is a massive restriction of diversity because of the correlations. These predictions are completely inconsistent with models in which amino acid substitutions are made independently at each site and are in good agreement with the data. Our results suggest that antibody diversity is not limited by the sequences encoded in the genome and may reflect rapid adaptation to antigenic challenges. This approach should be applicable to the study of the global properties of other protein families.
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ISSN:1091-6490
1091-6490
DOI:10.1073/pnas.1001705107