Conserved biophysical compatibility among the highly variable germline-encoded regions shapes TCR-MHC interactions
Abstract
T cells are critically important components of the adaptive immune system primarily responsible for identifying and responding to pathogenic challenges. This recognition of pathogens is driven by the interaction between membrane-bound T cell receptors (TCRs) and antigenic peptides presented on major histocompatibility complex (MHC) molecules. The formation of the TCR-peptide-MHC complex (TCR-pMHC) involves interactions among germline-encoded and hypervariable amino acids. Germline-encoded and hypervariable regions can form contacts critical for complex formation, but only interactions between germline-encoded contacts are likely to be shared across many of all the possible productive TCR-pMHC complexes. Despite this, experimental investigation of these interactions have focused on only a small fraction of the possible interaction space. To address this, we analyzed every possible germline-encoded TCR-MHC contact in humans, thereby generating the first comprehensive characterization of these largely antigen-independent interactions. Our computational analysis suggests that germline-encoded TCR-MHC interactions that are conserved at the sequence level are rare due to the high amino acid diversity of the TCR CDR1 and CDR2 loops, and that such conservation is unlikely to dominate the dynamic protein-protein binding interface. Instead, we propose that binding properties such as the docking orientation are defined by regions of biophysical compatibility between these loops and the MHC surface.
Data availability
All data and code used for the analysis in this manuscript are freely available online with no restrictions. All input FASTA sequences and code needed to recreate the analysis can be found via the AIMS GitHub page: github.com/ctboughter/AIMS. Specific analysis for structural comparisons between interaction potentials and TCR-pMHC complexes are found via a separate repository, called PRESTO, also hosted on GitHub: github.com/ctboughter/PRESTO. Due to the significant time required to calculate the interaction scores calculated via AIMS, the calculated scores can be found on Zenodo at the following DOI: 10.5281/zenodo.7023681. In case of future updates to either AIMS or PRESTO, the specific versions used for this manuscript are also hosted on Zenodo, as AIMS v0.8 [DOI: 10.5281/zenodo.7025972] and PRESTO v0.2 [DOI: 10.5281/zenodo.7025652].
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Author details
Funding
National Institutes of Health
- Christopher T Boughter
- Martin Meier-Schellersheim
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
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