TCRmodel2: high-resolution modeling of T cell receptor recognition using deep learning.

Autor:	Yin R; University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA.; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742, USA., Ribeiro-Filho HV; University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA.; Brazilian Biosciences National Laboratory, Brazilian Center for Research in Energy and Materials, Campinas 13083-100, Brazil., Lin V; University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA.; Thomas S. Wootton High School, Rockville, MD 20850, USA., Gowthaman R; University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA.; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742, USA., Cheung M; University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA.; Department of Chemistry and Biochemistry, University of Maryland, College Park, MD 20742, USA., Pierce BG; University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA.; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742, USA.; University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD 21201, USA.
Jazyk:	angličtina
Zdroj:	Nucleic acids research [Nucleic Acids Res] 2023 Jul 05; Vol. 51 (W1), pp. W569-W576.
DOI:	10.1093/nar/gkad356
Abstrakt:	The cellular immune system, which is a critical component of human immunity, uses T cell receptors (TCRs) to recognize antigenic proteins in the form of peptides presented by major histocompatibility complex (MHC) proteins. Accurate definition of the structural basis of TCRs and their engagement of peptide-MHCs can provide major insights into normal and aberrant immunity, and can help guide the design of vaccines and immunotherapeutics. Given the limited amount of experimentally determined TCR-peptide-MHC structures and the vast amount of TCRs within each individual as well as antigenic targets, accurate computational modeling approaches are needed. Here, we report a major update to our web server, TCRmodel, which was originally developed to model unbound TCRs from sequence, to now model TCR-peptide-MHC complexes from sequence, utilizing several adaptations of AlphaFold. This method, named TCRmodel2, allows users to submit sequences through an easy-to-use interface and shows similar or greater accuracy than AlphaFold and other methods to model TCR-peptide-MHC complexes based on benchmarking. It can generate models of complexes in 15 minutes, and output models are provided with confidence scores and an integrated molecular viewer. TCRmodel2 is available at https://tcrmodel.ibbr.umd.edu. (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)
Databáze:	MEDLINE
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