Supplementary Data from Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC–Peptide Binding Data Set

Abstract

<p>This file contains the combined supplementary figures and tables. Table S1. Prediction methods used in this study. Table S2. In silico predicted and in vitro validated binding affinities of peptides derived from HPV16 E6 and E7 proteins for the HLA types A1, A2, A3, A11, A24, B7 and B15. Figure S1. Performance evaluation of HLA binding prediction algorithms: the capacity to separate HLA-A1, A11, B7 and B15 binders from non-binders. Figure S2. Performance evaluation for the predictor SYFPEITII. Figure S3. Decision threshold-dependent performance analysis of indicated HLA-binding prediction methods for HLA-A1, A11, B7 and B15. Figure S4. Assessment of prediction performance for HLA-A1, A3, A11, A24, B7 and B15 using thresholds individually recommended for each HLA-type and peptide length vs. general intermediate and low binding affinity thresholds. Figure S5. Comparison of prediction accuracies obtained by applying criteria-based and bootstrapping-validated thresholds for each analyzed predictor for HLA-A1, A11, B7 and B15. Figure S6. Effect of using individually calculated criteria-based thresholds vs. commonly used thresholds for the prediction of HPV16 E6 and E7 derived ligands to HLA A1, A3, A11, A24, B7 and B15. Figure S7. Peptide sequence motifs of HLA-type- specific epitope entries from the immune epitope data base (IEDB) and the HPV dataset.</p>