Investigating the conformational dynamics of the Major Histocompatibility Complex class I

Abstract

The major histocompatibility complex class I (MHC-I) protein provides a snapshot of the cellular proteome by binding peptide fragments and trafficking them to the cell surface. This facilitates immunosurveillance by cytotoxic lymphocytes enabling the detection and destruction of infected and cancerous cells. The underlying mechanistic processes that determine which peptide fragments bind to an individual’s particular set of MHC-I alleles remain incompletely characterised. This inhibits our ability to predict possible antigens that will sustain through the antigen processing pathway for use in personalised cancer immunotherapy vaccine formulations. Computational simulations have allowed us to model the dynamics of the major histocompatibility complex to understand the mechanisms by which they bind and release peptides to curate their bound peptide repertoire. We investigate the variable dependency of MHC-I alleles on the molecular chaperone tapasin, to efficiently select high affinity peptide cargo and enable successful surface expression. Here, we describe an exact mechanistic model of peptide editing, at an atomistic resolution, that enables the selective dissociation of peptides with less than optimal binding affinity. It was found that the mechanism of independent peptide editing by MHC-I is mediated through transient disruption of peptide backbone hydrogen bonds to the peptide binding groove by local sidechain interaction networks. We have further improved our molecular dynamics simulation capabilities through development of the gaussian accelerated molecular dynamics enhanced sampling method reweighing strategies, providing improved accuracy of simulation results and greater enhanced sampling capacity of larger biomolecular systems. This work describes a critical stage of the antigen processing pathway, providing the theoretical foundations for improving the prediction of antigen binding to MHC-I. These findings will open the door to a new wave of possible predictive metrics for accurate classification of viable antigen targets, as well as potentially provide new strategies to curate the immunopeptidome for therapeutic effect.

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Identifiers

ORCID for Jonathan Essex: orcid.org/0000-0003-2639-2746

ORCID for Andy Van Hateren: orcid.org/0000-0002-3915-0239

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