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Length-independent structural similarities enrich the antibody CDR canonical class model

Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variabl...

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Autores principales: Nowak, Jaroslaw, Baker, Terry, Georges, Guy, Kelm, Sebastian, Klostermann, Stefan, Shi, Jiye, Sridharan, Sudharsan, Deane, Charlotte M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966832/
https://www.ncbi.nlm.nih.gov/pubmed/26963563
http://dx.doi.org/10.1080/19420862.2016.1158370
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author Nowak, Jaroslaw
Baker, Terry
Georges, Guy
Kelm, Sebastian
Klostermann, Stefan
Shi, Jiye
Sridharan, Sudharsan
Deane, Charlotte M.
author_facet Nowak, Jaroslaw
Baker, Terry
Georges, Guy
Kelm, Sebastian
Klostermann, Stefan
Shi, Jiye
Sridharan, Sudharsan
Deane, Charlotte M.
author_sort Nowak, Jaroslaw
collection PubMed
description Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variable structural clusters show strong sequence patterns suggesting either that they evolved from the same original structure or result from some form of convergence. We find that our length-independent method not only clusters a larger number of CDRs, but also predicts canonical class from sequence better than the standard length-dependent approach. To demonstrate the usefulness of our findings, we predicted cluster membership of CDR-L3 sequences from 3 next-generation sequencing datasets of the antibody repertoire (over 1,000,000 sequences). Using the length-independent clusters, we can structurally classify an additional 135,000 sequences, which represents a ∼20% improvement over the standard approach. This suggests that our length-independent canonical classes might be a highly prevalent feature of antibody space, and could substantially improve our ability to accurately predict the structure of novel CDRs identified by next-generation sequencing.
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spelling pubmed-49668322016-08-24 Length-independent structural similarities enrich the antibody CDR canonical class model Nowak, Jaroslaw Baker, Terry Georges, Guy Kelm, Sebastian Klostermann, Stefan Shi, Jiye Sridharan, Sudharsan Deane, Charlotte M. MAbs Report Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variable structural clusters show strong sequence patterns suggesting either that they evolved from the same original structure or result from some form of convergence. We find that our length-independent method not only clusters a larger number of CDRs, but also predicts canonical class from sequence better than the standard length-dependent approach. To demonstrate the usefulness of our findings, we predicted cluster membership of CDR-L3 sequences from 3 next-generation sequencing datasets of the antibody repertoire (over 1,000,000 sequences). Using the length-independent clusters, we can structurally classify an additional 135,000 sequences, which represents a ∼20% improvement over the standard approach. This suggests that our length-independent canonical classes might be a highly prevalent feature of antibody space, and could substantially improve our ability to accurately predict the structure of novel CDRs identified by next-generation sequencing. Taylor & Francis 2016-03-10 /pmc/articles/PMC4966832/ /pubmed/26963563 http://dx.doi.org/10.1080/19420862.2016.1158370 Text en © 2016, The Author(s), Published with license by Taylor & Francis Group, LLC http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted.
spellingShingle Report
Nowak, Jaroslaw
Baker, Terry
Georges, Guy
Kelm, Sebastian
Klostermann, Stefan
Shi, Jiye
Sridharan, Sudharsan
Deane, Charlotte M.
Length-independent structural similarities enrich the antibody CDR canonical class model
title Length-independent structural similarities enrich the antibody CDR canonical class model
title_full Length-independent structural similarities enrich the antibody CDR canonical class model
title_fullStr Length-independent structural similarities enrich the antibody CDR canonical class model
title_full_unstemmed Length-independent structural similarities enrich the antibody CDR canonical class model
title_short Length-independent structural similarities enrich the antibody CDR canonical class model
title_sort length-independent structural similarities enrich the antibody cdr canonical class model
topic Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966832/
https://www.ncbi.nlm.nih.gov/pubmed/26963563
http://dx.doi.org/10.1080/19420862.2016.1158370
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