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Viruses like HIV and SIV escape from containment by CD8(+) T lymphocytes through generating mutations that interfere with epitope peptide:MHC class I binding. However, mutations in some viral epitopes are selected for that have no impact on this binding. We explored the mechanism underlying the evolution of such epitopes by studying CD8(+) T lymphocyte recognition of a dominant Nef epitope of SIVmac251 in infected Mamu-A*02(+) rhesus monkeys. Clonal analysis of the p199RY-specific CD8(+) T lymphocyte repertoire in these monkeys indicated that identical T cell clones were capable of recognizing wild-type (WT) and mutant epitope sequences. However, we found that the functional avidity of these CD8(+) T lymphocytes for the mutant peptide:Mamu-A*02 complex was diminished. Using surface plasmon resonance to measure the binding affinity of the p199RY-specific TCR repertoire for WT and mutant p199RY peptide:Mamu-A*02 monomeric complexes, we found that the mutant p199RY peptide:Mamu-A*02 complexes had a lower affinity for TCRs purified from CD8(+) T lymphocytes than did the WT p199RY peptide:Mamu-A*02 complexes. These studies demonstrated that differences in TCR affinity for peptide:MHC class I ligands can alter functional p199RY-specific CD8(+) T lymphocyte responses to mutated epitopes, decreasing the capacity of these cells to contain SIVmac251 replication.
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http://dx.doi.org/10.4049/jimmunol.1101080 | DOI Listing |
Nanoscale Horiz
September 2025
Programmable Biomaterials Laboratory, Institute of Materials, Interfaculty Bioengineering Institute, School of Engineering, Ecole Polytechnique Fédérale Lausanne, Lausanne, 1015, Switzerland.
The nanoscale spatial arrangement of T cell receptor (TCR) ligands critically influences their activation potential in CD8 T cells, yet a comprehensive understanding of the molecular landscape induced by engagement with native peptide-MHC class I (pMHC-I) remains incomplete. Using DNA origami nanomaterials, we precisely organize pMHC-I molecules into defined spatial configurations to systematically investigate the roles of valencies, inter-ligand spacings, geometric patterns, and molecular flexibility in regulating T cell function. We find that reducing the inter-ligand spacing to ∼7.
View Article and Find Full Text PDFIEEE Trans Comput Biol Bioinform
June 2025
The interaction between peptides and Major Histocompatibility Complex Class I (MHC-I) molecules plays a critical role in adaptive immune recognition. Although computational prediction algorithms have advanced over traditional experimental methods, challenges still remain. There is a scarcity of standardized datasets that provide comprehensive profiles of MHC-peptide structure.
View Article and Find Full Text PDFInt J Mol Sci
July 2025
Department of Neurology and Geriatrics, Kagoshima University, 8-35-1 Sakuragaoka, Kagoshima 890-8520, Japan.
T-cell receptors (TCRs) exhibit degeneracy, enabling individual TCRs to recognize multiple altered peptide ligands (APLs) derived from a single cognate antigen. This characteristic has been involved in the pathogenesis of autoimmune diseases through cross-reactivity between microbial and self-antigens. Cytotoxic T lymphocytes (CTLs), which recognize peptide-MHC class I complexes via TCRs, play a critical role in the immune response against viral infections.
View Article and Find Full Text PDFProtein Pept Lett
July 2025
Department of Pharmaceutics, Jayawantrao Sawant College of Pharmacy and Research, Savitribai Phule Pune University, Pune, 411028, India.
Immune responses depend on the identification and prediction of peptides that bind to MHC (major histocompatibility complex) class I molecules, especially when it comes to the creation of vaccines, cancer immunotherapy, and autoimmune disorders. The ability to predict and evaluate MHC class immunoproteomics have completely transformed I epitopes in conjunction with immunoinformatics technologies. However, precisely identifying epitopes across various populations and situations is extremely difficult due to the complexity and diversity of MHC class I binding peptides.
View Article and Find Full Text PDFBrief Bioinform
July 2025
School of Information and Control Engineering, China University of Mining and Technology, No. 1 Daxue Road, Tongshan District, Xuzhou, Jiangsu 221116, China.
Characterizing the binding interactions between major histocompatibility complex (MHC) class II molecules and peptides is crucial for studying the immune system, offering potential applications for neoantigen design, vaccine development, and personalized immunotherapy. Motivated by this profound meaning, we developed a model that integrates large language models (LLMs) and deep hypergraph learning for predicting MHC class II-peptide binding reactivity, affinity, and residue contact profiling. pMHChat takes MHC pseudo-sequences and peptide sequences as inputs and processes them through four stages: LLMs fine-tune stage, feature encoding and map fusion stage, task-specific prediction stage, and downstream analysis stage.
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