QSAR modeling of human TAP-binding peptide based on amino acid properties

Abstract

The transporter associated with antigen processing (TAP) is essential for peptide delivery from the cytosol into the lumen of the endoplasmic reticulum (ER), where these peptides are loaded on a major histocompatibility complex (MHC) I molecules and form peptide-MHC complex. The peptide-MHC leaves the ER and displays their antigenic cargo on the cell surface to cytotoxic T cells and recognized by T-cell receptor. In this study, 89 physicochemical properties of amino acid were used to characterize the peptides which were binding to TAP. Then, quantitative structural activity relationship (QSAR) model was constructed by multiple linear regressions (MLR) with the parameters, which had significant contribution for affinity and screened by the stepwise regression (STR). The QSAR model had good reliability (Q2=0.663) and predictive ability (R test 2=0.673). The normalized regression coefficients (NRC) of the QSAR model could demonstrate the contributions of specific position for affinity and discovery the dominant amino acid TAP binding peptide. Therefore, the QSAR model constructed by STR-MLR has many advantages, such as, easier calculation and explanation, good performance, and definite physiochemical indication, which could be used to guide the design and modification of the TAP binding peptide.