点突变p53抗原肽的预测及其与MHCⅠ类分子的结合

Prediction and binding of a mutant p53 peptide to MHC class I molecule

目的从肿瘤抗原的全长氨基酸序列中预测肿瘤抗原肽，据此指导肿瘤肽疫苗的设计和制备。方法采用基序（ｃｏｎｓｅｎｓｕｓｍｏｔｉｆ）预测法，经计算机ＰＥＰＭＯＴＩＦ软件预测含点突变的小鼠ｐ５３蛋白肽，并建立一个计分系统来估测预测肽与ＭＨＣⅠ类分子结合的可能性，进一步通过ＭＨＣⅠ类分子－肽结合试验和ＭＨＣⅠ类分子－肽结合稳定性试验检测它们与ＭＨＣⅠ类分子的结合力和亲和力。结果预测了３条肽，其中ｍｐ５３Ｐ１３２Ｆ（ＬＮＫＬＦＦＱＬ）能与Ｈ－２Ｋｂ结合而不与Ｈ－２Ｄｂ结合；ｍｐ５３Ｐ２４６Ｓ（ＭＧＧＭＮＲＳＰＩＬ）和ｍｐ５３Ｐ２７０Ｃ（ＧＲＤＳＦＥＶＣＶ）既不与Ｈ－２Ｋｂ结合也不与Ｈ－２Ｄｂ结合。肽与ＭＨＣⅠ类分子之间的结合与用计分系统计算的肽积分高低有关，即高分值的肽能与相应的ＭＨＣⅠ类分子结合。结论计算机ＰＥＰＭＯＴＩＦ软件配合肽计分是简便有效的ＭＨＣⅠ类分子结合肽预测法。

Objective To predict tumor antigenic peptides from the intact amino acid sequence of tumor antigens, thereby providing a guide to the design and development of tumor peptide based vaccines. Methods Antigenic peptides were predicted by using a computer program PEPMOTIF based on MHC class I allele specific consensus motifs; and a scoring system was established to assess the likelihood of the peptides to bind to MHC class I molecules. MHC class I peptide binding assay and MHC class I peptide stabilization assay were used to determine the binding ability and affinity of the predicted peptides. Results Three peptides derived from mouse mutant p53 were predicted. mp53P 132F (LNKLFFQL) was shown to bind to H 2K b, but not H 2D b. mp53P 246S (MGGMNRSPIL) and mp53P 270C (GRDSFEVCV) bound to neither H 2K b nor H 2D b. A relationship was found between peptide scores and binding of the peptides to the relevant MHC class I molecules. Conclusion The computer program PEPMOTIF combining with a scoring system is a simple and efficient tool for predicting MHC class I binding peptides derived from antigenic proteins.