PyIgClassify: a database of antibody CDR structural classifications

被引:83
作者
Adolf-Bryfogle, Jared [1 ,2 ]
Xu, Qifang [1 ]
North, Benjamin [1 ]
Lehmann, Andreas [1 ]
Dunbrack, Roland L., Jr. [1 ]
机构
[1] Fox Chase Canc Ctr, Inst Canc Res, Philadelphia, PA 19111 USA
[2] Drexel Univ, Program Mol & Cell Biol & Genet, Coll Med, Philadelphia, PA 19102 USA
基金
美国国家卫生研究院;
关键词
HYPERVARIABLE REGIONS; CANONICAL STRUCTURES; ANALYSIS TOOL; IMMUNOGLOBULIN; DESIGN; COMPLEMENTARITY; PREDICTION; SEQUENCES; PROTEINS; IDENTIFICATION;
D O I
10.1093/nar/gku1106
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Classification of the structures of the complementarity determining regions (CDRs) of antibodies is critically important for antibody structure prediction and computational design. We have previously performed a clustering of antibody CDR conformations and defined a systematic nomenclature consisting of the CDR, length and an integer starting from the largest to the smallest cluster in the data set (e.g. L1-11-1). We present PyIgClassify (for Pythonbased immunoglobulin classification; available at http://dunbrack2.fccc.edu/pyigclassify/), a database and web server that provides access to assignments of all CDR structures in the PDB to our classification system. The database includes assignments to the IMGT germline V regions for heavy and light chains for several species. For humanized antibodies, the assignment of the frameworks is to human germlines and the CDRs to the germlines of mice or other species sources. The database can be searched by PDB entry, cluster identifier and IMGT germline group (e.g. human IGHV1). The entire database is down-loadable so that users may filter the data as needed for antibody structure analysis, prediction and design.
引用
收藏
页码:D432 / D438
页数:7
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