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ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes.
Borrman, Tyler; Cimons, Jennifer; Cosiano, Michael; Purcaro, Michael; Pierce, Brian G; Baker, Brian M; Weng, Zhiping.
Afiliação
  • Borrman T; Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605.
  • Cimons J; Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana, 46556.
  • Cosiano M; Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana, 46556.
  • Purcaro M; Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605.
  • Pierce BG; University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland, 20850.
  • Baker BM; Department of Chemistry and Biochemistry and the Harper Cancer Research Institute, University of Notre Dame, Notre Dame, Indiana, 46556.
  • Weng Z; Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, 01605.
Proteins ; 85(5): 908-916, 2017 05.
Article em En | MEDLINE | ID: mdl-28160322
ABSTRACT
The ATLAS (Altered TCR Ligand Affinities and Structures) database (https//zlab.umassmed.edu/atlas/web/) is a manually curated repository containing the binding affinities for wild-type and mutant T cell receptors (TCRs) and their antigens, peptides presented by the major histocompatibility complex (pMHC). The database links experimentally measured binding affinities with the corresponding three dimensional (3D) structures for TCR-pMHC complexes. The user can browse and search affinities, structures, and experimental details for TCRs, peptides, and MHCs of interest. We expect this database to facilitate the development of next-generation protein design algorithms targeting TCR-pMHC interactions. ATLAS can be easily parsed using modeling software that builds protein structures for training and testing. As an example, we provide structural models for all mutant TCRs in ATLAS, built using the Rosetta program. Utilizing these structures, we report a correlation of 0.63 between experimentally measured changes in binding energies and our predicted changes. Proteins 2017; 85908-916. © 2016 Wiley Periodicals, Inc.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Software / Receptores de Antígenos de Linfócitos T / Antígenos de Histocompatibilidade Classe I / Bases de Dados Factuais / Mutação Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Software / Receptores de Antígenos de Linfócitos T / Antígenos de Histocompatibilidade Classe I / Bases de Dados Factuais / Mutação Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article