# Predicting reverse-bound peptide conformations in MHC Class II with PANDORA

## TL;DR

This paper introduces an updated version of PANDORA, a tool that can model reverse-bound peptides in MHC class II molecules, which is important for understanding immune recognition and vaccine design.

## Contribution

The novel contribution is the development of PANDORA's ability to model reverse-bound peptides using algorithmically reversed templates.

## Key findings

- PANDORA achieved an average backbone binding-core L-RMSD of 0.63 Å in validation experiments.
- The tool maintains low RMSD values even with templates from different alleles and peptides.
- PANDORA is positioned as a valuable resource for immunology and vaccine development.

## Abstract

Recent discoveries have transformed our understanding of peptide binding in Major Histocompatibility Complex (MHC) molecules, showing that peptides, for some MHC class II alleles, can bind in a reverse orientation (C-terminus to N-terminus) and can still effectively activate CD4+ T cells. These finding challenges established concepts of immune recognition and suggests new pathways for therapeutic intervention, such as vaccine design. We present an updated version of PANDORA, which, to the best of our knowledge, is the first tool capable of modeling reversed-bound peptides. Modeling these peptides presents a unique challenge due to the limited structural data available for these orientations in existing databases. PANDORA has overcome this challenge through integrative modeling using algorithmically reversed peptides as templates. We have validated the new PANDORA feature through two targeted experiments, achieving an average backbone binding-core L-RMSD value of 0.63 Å. Notably, it maintained low RMSD values even when using templates from different alleles and peptide sequences. Our results suggest that PANDORA will be an invaluable resource for the immunology community, aiding in the development of targeted immunotherapies and vaccine design.