Abstract
The prediction of peptide binders to Major Histocompatibility Complex (MHC) class II receptors is of great interest to study autoimmune diseases and for vaccine development. Most approaches predict the affinities using sequence-based models trained on experimental data and multiple alignments from known peptide substrates. However, detecting activity differences caused by single-point mutations is a challenging task. In this work, we used interactions calculated from simulations to build scoring matrices for quickly estimating binding differences by single-point mutations. We modelled a set of 837 peptides bound to an MHC class II allele, and optimized the sampling of the conformations using the Rosetta backrub method by comparing the results to molecular dynamics simulations. From the dynamic trajectories of each complex, we averaged and compared structural observables for each amino acid at each position of the 9°mer peptide core region. With this information, we generated the scoring-matrices to predict the sign of the binding differences. We then compared the performance of the best scoring-matrix to different computational methodologies that range in computational costs. Overall, the prediction of the activity differences caused by single mutated peptides was lower than 60% for all the methods. However, the developed scoring-matrix in combination with existing methods reports an increase in the performance, up to 86% with a scoring method that uses molecular dynamics.
Highlights
The Major Histocompatibility Complex (MHC) class II is a key receptor responsible for recognizing fragments of proteins belonging to external pathogens, as well as recognizing human proteins that can boost the emergence of autoimmune events and immunological processes (Wieczorek et al, 2017)
To evaluate the impact of interactions in affinity changes caused by single-point mutations in MHC class II peptide binders, a set of scoring-matrices was calculated to assign probabilities for each type of amino acid in each position of the peptide core region
Examples comparing the results of molecular dynamics (MD) to backrub sampling using kT 0.35 and kT 1.2 are shown in Figure 2 for two amino acids
Summary
The Major Histocompatibility Complex (MHC) class II is a key receptor responsible for recognizing fragments of proteins belonging to external pathogens, as well as recognizing human proteins that can boost the emergence of autoimmune events and immunological processes (Wieczorek et al, 2017). The structures of multiple MHC class II alleles have been elucidated. They are composed of α and β chains split into four sub-units, two of them forming a groove where the peptides bind (Bjorkman, 2015) (see Supplementary Figure S1). The peptides contain a core region, which is a fragment of nine amino acids responsible to stabilize the peptide-MHC class II interaction. The available structures of MHC class II bound to peptides provide
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