Rapid, Precise, and Reproducible Prediction of Peptide-MHC Binding Affinities from Molecular Dynamics That Correlate Well with Experiment.

Peter V Coveney,Bernhard Knapp,David W Wright,Charlotte M Deane,Shunzhou Wan

doi:10.1021/acs.jctc.5b00179

Abstract

The presentation of potentially pathogenic peptides by major histocompatibility complex (MHC) molecules is one of the most important processes in adaptive immune defense. Prediction of peptide-MHC (pMHC) binding affinities is therefore a principal objective of theoretical immunology. Machine learning techniques achieve good results if substantial experimental training data are available. Approaches based on structural information become necessary if sufficiently similar training data are unavailable for a specific MHC allele, although they have often been deemed to lack accuracy. In this study, we use a free energy method to rank the binding affinities of 12 diverse peptides bound by a class I MHC molecule HLA-A*02:01. The method is based on enhanced sampling of molecular dynamics calculations in combination with a continuum solvent approximation and includes estimates of the configurational entropy based on either a one or a three trajectory protocol. It produces precise and reproducible free energy estimates which correlate well with experimental measurements. If the results are combined with an amino acid hydrophobicity scale, then an extremely good ranking of peptide binding affinities emerges. Our approach is rapid, robust, and applicable to a wide range of ligand-receptor interactions without further adjustment.

Highlights

The recognition of major histocompatibility complex (MHC) bound peptide ligands by T-cell receptors (TCRs) lies at the heart of the human immune response.[1]
The current molecular systems differ from the systems we have studied in both the ligands and the binding sites
Our new ESMACS protocol combines ensemble based Molecular dynamics (MD) simulations with free energy estimates computed from a combination of MMPB(GB)surface area (SA) and configurational entropy methods

Summary

Introduction

The recognition of major histocompatibility complex (MHC) bound peptide ligands by T-cell receptors (TCRs) lies at the heart of the human immune response.[1] To allow recognition, cytosolic peptides undergo the MHC class I (MHCI) pathway, while extracellular peptides undergo the MHC class II (MHCII) pathway. MHCI processing requires a protein to be cleaved into peptide fragments by the proteasome. These peptides are usually 8−11 amino acid residues long. The peptides enter the endoplasmatic reticulum (ER) via the “transporter associated with antigen processing” (TAP) or other transporter proteins such as Sec61.2 In the ER, the peptides are loaded on MHCI molecules. The pMHCI molecules are transported to the cell surface where they can be recognized by the TCRs of CD8+ T-cells

Objectives

Methods

Results

Conclusion