Prediction of the binding affinities of peptides to class II MHC using a regularized thermodynamic model

Abstract

Background: The binding of peptide fragments of extracellular peptides to class II MHC is a crucial event in the adaptive immune response. Each MHC allotype generally binds a distinct subset of peptides and the enormous number of possible peptide epitopes prevents their complete experimental characterization. Computational methods can utilize the limited experimental data to predict the binding affinities of peptides to class II MHC. Results: We have developed the Regularized Thermodynamic Average, or RTA, method for predicting the affinities of peptides binding to class II MHC. RTA accounts for all possible peptide binding conformations using a thermodynamic average and includes a parameter constraint for regularization to improve accuracy on novel data. RTA was shown to achieve higher accuracy, as measured by AUC, than SMM-align on the same data for all 17 MHC allotypes examined. RTA also gave the highest accuracy on all but three allotypes when compared with results from 9 different prediction methods applied to the same data. In addition, the method correctly predicted the peptide binding register of 17 out of 18 peptide-MHC complexes. Finally, we found that suboptimal peptide binding registers, which are often ignored in other prediction methods, made significant contributions of at least 50% of the total binding energy for approximately 20% of the peptides.

The Utility and Limitations of Current Web-Available Algorithms To Predict Peptides Recognized by CD4 T Cells in Response to Pathogen Infection

“…Incorporation of data from these assays might also improve accuracy of the 9 amino acid core predicted to bind to in the MHC class II pocket. We hypothesize that limitations in our understanding of peptide:class II interactions have led to incorrect core assignments, a hypothesis recently supported by discrepancies between predicted cores and co-crystallization of peptide: class II complexes (25, 63) and our own data shown here. Faulty core designation may “contaminate” the prediction accuracy of preferences in binding going forward.…”

Towards Universal Structure-Based Prediction of Class II MHC Epitopes for Diverse Allotypes

“…It also suggests that the 1AQD peptide may in fact have two alternative binding registers for DRB1*0101, with the observed register favored by the crystallization environment. Such multiple binding registers have been computationally predicted to be fairly prevalent in strong binders [26], [34] and have also been experimentally observed [48], [49], [50]. The RTA results for the 1FV1 peptide binding to DRB5*0101 shows a similar trend, with the binding affinity of the incorrectly predicted register (VHFFKNIVT), 8.76 kcal/mol, the second highest just after the correct register (FKNIVTPRT), 10.5 kcal/mol, although the affinity difference is greater than for 1AQD.…”

SVM based Prediction of Major Histocompatibility Complex Binders: Identification and Analysis of Dracunculus medinensis Peptide

“…In the MHC class II antigen presentation process, antigenic protein NADH dehydrogenase subunit 6 (mitochondrion) from D. medinensis are ingested by antigen-presenting cells through the process of endocytosis or phagocytosis, then cleaved by cathepsins a class of protease into oligopeptides in the endosomes, than are fuse with lysosomes containing MHC class II molecules [27] and present them at the cell surface for recognition by T cells [28][29][30][31][32][33][34][35][36]. Where T helper cells trigger an immune response by inflammation and swelling due to phagocytes or may lead to an antibody-mediated immune response via B-cell activation.…”