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ANARCI: antigen receptor numbering and receptor classification
James Dunbar1, Charlotte M Deane1
1Department of Statistics, Oxford University, Oxford, UK.
Bioinformatics (Oxford, England)
|October 2, 2015
Summary
ANARCI is a new tool that classifies and numbers antibody and T-cell receptor sequences using five popular schemes. This open-source software aids in antibody sequence comparison and protein structure modeling.
Area of Science:
- Immunoinformatics
- Computational Biology
- Structural Biology
Background:
- Antibody amino-acid sequence numbering is crucial for comparative analysis, protein modeling, and engineering.
- Existing numbering schemes vary in nomenclature, position definitions, and adoption across disciplines.
- A need exists for a comprehensive, publicly available software tool for antibody sequence annotation.
Purpose of the Study:
- To develop and provide a software tool for classifying and numbering antibody and T-cell receptor sequences.
- To implement the most widely used antibody sequence numbering schemes within a single tool.
Main Methods:
- Development of the ANARCI software tool.
- Implementation of five popular numbering schemes: Kabat, Chothia, Enhanced Chothia, IMGT, and AHo.
- Provision of downloadable software under an open-source license (GPLv3).
Main Results:
- ANARCI successfully classifies and numbers antibody and T-cell receptor amino-acid variable domain sequences.
- The tool supports annotation using the Kabat, Chothia, Enhanced Chothia, IMGT, and AHo numbering schemes.
- ANARCI is available as a downloadable open-source tool with an accompanying web interface.
Conclusions:
- ANARCI addresses the lack of a unified, open-source software for antibody sequence numbering.
- The tool facilitates standardized annotation, improving antibody sequence comparison, modeling, and engineering.
- ANARCI provides a valuable resource for researchers in immunoinformatics and related fields.
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