Literature DB >> 28160322

ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes.

Tyler Borrman1, Jennifer Cimons2, Michael Cosiano2, Michael Purcaro1, Brian G Pierce3, Brian M Baker2, Zhiping Weng1.   

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; 85:908-916.
© 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  3D viewer; Rosetta; adaptive immunity; binding energy; protein modeling; scoring functions

Mesh:

Substances:

Year:  2017        PMID: 28160322      PMCID: PMC5860664          DOI: 10.1002/prot.25260

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  39 in total

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8.  T cell receptor cross-reactivity directed by antigen-dependent tuning of peptide-MHC molecular flexibility.

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Review 4.  Structural Prediction of Peptide-MHC Binding Modes.

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Review 5.  An overview of immunoinformatics approaches and databases linking T cell receptor repertoires to their antigen specificity.

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Authors:  Nishant K Singh; Esam T Abualrous; Cory M Ayres; Frank Noé; Ragul Gowthaman; Brian G Pierce; Brian M Baker
Journal:  Proteins       Date:  2019-10-21

7.  High-throughput modeling and scoring of TCR-pMHC complexes to predict cross-reactive peptides.

Authors:  Tyler Borrman; Brian G Pierce; Thom Vreven; Brian M Baker; Zhiping Weng
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8.  An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants.

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Journal:  Structure       Date:  2021-02-03       Impact factor: 5.871

9.  Stitchr: stitching coding TCR nucleotide sequences from V/J/CDR3 information.

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10.  Interpreting T-Cell Cross-reactivity through Structure: Implications for TCR-Based Cancer Immunotherapy.

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Journal:  Front Immunol       Date:  2017-10-04       Impact factor: 7.561

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