Program in Bioinformatics and Integrative Biology
Bioinformatics | Computational Biology | Immunology and Infectious Disease | Structural Biology
How T-cell receptors (TCRs) can be intrinsically biased toward MHC proteins while simultaneously display the structural adaptability required to engage diverse ligands remains a controversial puzzle. We addressed this by examining alphabeta TCR sequences and structures for evidence of physicochemical compatibility with MHC proteins. We found that human TCRs are enriched in the capacity to engage a polymorphic, positively charged "hot-spot" region that is almost exclusive to the alpha1-helix of the common human class I MHC protein, HLA-A*0201 (HLA-A2). TCR binding necessitates hot-spot burial, yielding high energetic penalties that must be offset via complementary electrostatic interactions. Enrichment of negative charges in TCR binding loops, particularly the germ-line loops encoded by the TCR Valpha and Vbeta genes, provides this capacity and is correlated with restricted positioning of TCRs over HLA-A2. Notably, this enrichment is absent from antibody genes. The data suggest a built-in TCR compatibility with HLA-A2 that biases receptors toward, but does not compel, particular binding modes. Our findings provide an instructional example for how structurally pliant MHC biases can be encoded within TCRs.
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Citation: Proc Natl Acad Sci U S A. 2016 Mar 1;113(9):E1276-85. doi: 10.1073/pnas.1522069113. Epub 2016 Feb 16. Link to article on publisher's site
Publisher PDF posted as allowed by the publisher's author rights policy at http://www.pnas.org/site/aboutpnas/authorfaq.xhtml.
MHC bias, T-cell receptor, binding, peptide/MHC, structure
Proceedings of the National Academy of Sciences of the United States of America
Blevins, Sydney J.; Pierce, Brian G.; Singh, Nishant K.; Riley, Timothy P.; Wang, Yuan; Spear, Timothy T.; Nishimura, Michael I.; Weng, Zhiping; and Baker, Brian M., "How structural adaptability exists alongside HLA-A2 bias in the human alphabeta TCR repertoire" (2016). Program in Bioinformatics and Integrative Biology Publications and Presentations. 86.