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任意のT細胞エピトープ同定法の開発

任意T细胞表位鉴定方法的开发

基本信息

批准号：
07670366
负责人：
UDAKA Keiko
金额：
$ 1.47万
依托单位：
KYOTO UNIVERSITY
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07670366/
关键词：
MHC peptide library T cell epitope ペプチドライブラリー結合能

项目摘要

1) Positional scanning of MHC calss Imolecules.Peptide binding specificities of Kb, Db and Ld were analyzed with 9-mer peptide libraries. The basic design of the libraries is Oxxxxxxxx, for instance, to evaluate the relative fitness of an amino acid at position, O.xdesignates the positions where 19 am ino acids but Cys are equally represented. Binding of peptides was quantitated by stabilization of empty MHC class Imolecules expressed on TAP deficient cell lines. Energetic advantages and disadvantages among different amino acids in MHC binding are most prominent at the positions that have been previously identified as major anchors by pool sequencing. Positions 4,6,7 and 8 exhibited the least selectivity.2) Prediction of T cell epitopes.A scoring system was devised from the positional scanning data by assuming that the energetic contribution of each amino acid can be additive in binding of the whole peptide. Most of known T cell epitope peptides are scored 1-5th among the highest scoring 9-mers present in parental proteins.3) Correlation of predicted vs actual binding.Arbitorarily chosen peptides were synthesized and their MHCbinding capacities were compared with the predicted binding scores. A positive correlation between these values were observed, but there were also substantial fluctuations, indicating a limit in predicting power by the positional scannning.4) Prediction of repertoire overlap of MHC binding peptides among different MHC molecules.By using the above mentioned scoring system, MHC binding peptides were predicted for thres murine MHC allomorphs. Their repertoiree are suggested to share relatively small overlaps.

1)MHC钙离子的定位扫描：利用9-肽文库分析了KB、DB和LD的多肽结合特性。文库的基本设计是Oxxxxxxxx，例如，为了评估氨基酸在位置上的相对适合性，O.x指定了19个Am氨基酸但Cys等同代表的位置。通过稳定表达在TAP缺陷细胞系上的空MHC I类分子来定量多肽的结合。不同氨基酸在MHC结合中的能量优势和劣势在先前通过池测序确定的主要锚定位置上最为突出。4、6、7和8位对T细胞表位的预测能力最差。根据位置扫描数据，假设每个氨基酸的能量贡献在与整个多肽的结合中是相加的，设计了一个评分系统。已知的大多数T细胞表位多肽在亲本蛋白中得分最高的9-MERS中为1-5。3)预测结合与实际结合的相关性。这些值之间存在正相关，但也有很大的波动，这表明位置扫描的预测能力有限。4)预测不同MHC分子之间MHC结合肽的谱系重叠。建议他们的曲目有相对较小的重叠。