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Structure-based prediction of T cell receptor:peptide-MHC interactions

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.08.05.503004Source: DataRank Database

Structure-based prediction of T cell receptor:peptide-MHC interactions is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2022). On theSindex it has a DataRank of 0. It has been cited 2 times.

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Open Access2 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)OA: greenTopics (35)IDs (PubMed, OpenAlex)SDGs (1)

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Authors (1)

Philip Bradley ORCID

Live enrichment

PubMed:21097893 OpenAlex:https://openalex.org/W4300361778

National Institutes of Health

Grant: 1S10OD028685-01

High-Performance Compute Cluster for Comprehensive Cancer and Infectious Diseases Research

National Institutes of Health

Grant: 5R35GM141457-06

Molecular modeling and machine learning for protein structures and interactions

National Institutes of Health

Grant: 5R01AI136514-05

Decoding the interactions between T cell receptors and peptide-MHC

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2022/08/06/2022.08.05.503004.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2022.08.05.503004

repositoryhttps://doi.org/10.1101/2022.08.05.503004

https://doi.org/10.7554/elife.82813

Fields of Study

vaccines and immunoinformatics approachesRNA and protein synthesis mechanismsAntimicrobial Peptides and Activities0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

T-cell receptorMajor histocompatibility complexEpitopeComputational biologyBiologyPeptideT cellImmune systemAntigenImmunologyBiochemistryQH301-705.5ScienceT-LymphocytesQRReceptors, Antigen, T-Celldeep learningstructure predictionEpitopesMedicineT cell receptorMHCbinding specificityBiology (General)PeptidesT cell epitopeComputational and Systems BiologyProtein Binding

Sustainable Development Goals

SDG 0: Reduced inequalities