ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes
dc.contributor.author | Borrman, Tyler M. | |
dc.contributor.author | Cimons, Jennifer M. | |
dc.contributor.author | Cosiano, Michael | |
dc.contributor.author | Purcaro, Michael | |
dc.contributor.author | Pierce, Brian G. | |
dc.contributor.author | Baker, Brian M. | |
dc.contributor.author | Weng, Zhiping | |
dc.date | 2022-08-11T08:07:58.000 | |
dc.date.accessioned | 2022-08-23T15:37:55Z | |
dc.date.available | 2022-08-23T15:37:55Z | |
dc.date.issued | 2017-05-01 | |
dc.date.submitted | 2017-07-12 | |
dc.identifier.citation | Proteins. 2017 May;85(5):908-916. doi: 10.1002/prot.25260. Epub 2017 Feb 16. <a href="https://doi.org/10.1002/prot.25260">Link to article on publisher's site</a> | |
dc.identifier.issn | 0887-3585 (Linking) | |
dc.identifier.doi | 10.1002/prot.25260 | |
dc.identifier.pmid | 28160322 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14038/25827 | |
dc.description.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. | |
dc.language.iso | en_US | |
dc.relation | <a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=28160322&dopt=Abstract">Link to Article in PubMed</a> | |
dc.relation.url | https://doi.org/10.1002/prot.25260 | |
dc.subject | Biochemistry, Biophysics, and Structural Biology | |
dc.subject | Bioinformatics | |
dc.subject | Computational Biology | |
dc.subject | Integrative Biology | |
dc.subject | Systems Biology | |
dc.title | ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes | |
dc.type | Journal Article | |
dc.source.journaltitle | Proteins | |
dc.source.volume | 85 | |
dc.source.issue | 5 | |
dc.identifier.legacycoverpage | https://escholarship.umassmed.edu/bioinformatics_pubs/119 | |
dc.identifier.contextkey | 10417172 | |
html.description.abstract | <p>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.</p> | |
dc.identifier.submissionpath | bioinformatics_pubs/119 | |
dc.contributor.department | Program in Bioinformatics and Integrative Biology | |
dc.source.pages | 908-916 |