# MORITS: An improved method to predict peptides from heterologous proteins that are recognized by the same T-cell receptor

**Authors:** Matthias Bruhn, Moritz Spatz, Ulrich Kalinke

PMC · DOI: 10.1038/s41598-024-58350-x · Scientific Reports · 2024-04-08

## TL;DR

This paper introduces MORITS, a new algorithm that helps identify peptides from different sources that can trigger similar T-cell responses.

## Contribution

The novel contribution is the development of MORITS, which improves peptide prediction by focusing on TCR-relevant MHC residues.

## Key findings

- MORITS identified peptide similarities between SARS-CoV-2 and allergens.
- The method outperforms existing workflows in predicting heterologous immune responses.
- It enhances screening efficiency by emphasizing TCR interaction residues.

## Abstract

Antigen-specific priming of T cells results in the activation of T cells that exert effector functions by interaction of their T-cell receptor (TCR) with the corresponding self-MHC molecule presenting a peptide on the surface of a target cell. Such antigen-specific T cells potentially can also interact with peptide-MHC complexes that contain peptides from unrelated antigens, a phenomenon that often is referred to as heterologous immunity. For example, some individuals that were pre-immunized against an allergen, could subsequently mount better anti-viral T-cell responses than non-allergic individuals. So far only few peptide pairs that experimentally have been shown to provoke heterologous immunity were  identified, and available prediction tools that can identify potential candidates are imprecise. We developed the MORITS algorithm to rapidly screen large lists of peptides for sequence similarities, while giving enhanced consideration to peptide residues presented by MHC that are particularly relevant for TCR interactions. In combination with established peptide-MHC binding prediction tools, the MORITS algorithm revealed peptide similarities between the SARS-CoV-2 proteome and certain allergens. The method outperformed previously published workflows and may help to identify novel pairs of peptides that mediate heterologous immune responses.

## Linked entities

- **Proteins:** HLA-C (major histocompatibility complex, class I, C)

## Full-text entities

- **Genes:** TRBV20OR9-2 (T cell receptor beta variable 20/OR9-2 (non-functional)) [NCBI Gene 6962] {aka CDR3, TCRBV20S2, TCRBV2O, TCRBV2S2O}, HLA-C (major histocompatibility complex, class I, C) [NCBI Gene 3107] {aka D6S204, HLA-JY3, HLAC, HLC-C, MHC, PSORS1}
- **Diseases:** SARS-CoV-2 (MESH:D000086382)

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11002005/full.md

## References

29 references — full list in the complete paper: https://tomesphere.com/paper/PMC11002005/full.md

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Source: https://tomesphere.com/paper/PMC11002005