医学信息2026，Vol.39Issue(17)：12-18,7.DOI:10.3969/j.issn.1006-1959.2026.17.002
TSP50生物信息学分析及抗原决定簇预测
Bioinformatics Analysis and Epitope Prediction of TSP50
摘要
Abstract
Objective To provide a reliable basis for the screening of monoclonal antibodies against testes-specific serine protease 50(TSP50)and the determination of their corresponding antigen-binding sites.Methods In this study,different bioinformatics analysis techniques were employed to analyze the properties and antigenic epitopes of TSP50.The amino acid sequence of TSP50 was obtained from the NCBI database.The physicochemical properties of TSP50 were predicted using tools such as Expasy Protparam,and its hydrophilicity and hydrophobicity were analyzed.The transmembrane regions and spatial structure of TSP50 were predicted using DeepTMHMM and the homology modeling method of Swiss-Model,respectively.The protein-protein interaction(PPI)network was constructed using STRING.Finally,the antigenic epitopes of TSP50 were predicted using the functional modules in DNAstar Protean.Results TSP50 was composed of 385 amino acids,with a molecular weight of 43.1 kDa and a theoretical isoelectric point of 8.58.Its instability index was 41.79,and the aliphatic index was 87.14.It was a hydrophilic protein and did not contain transmembrane domains.TSP50 consisted of 15.06%α helices,6.23%β turns,57.66%random coils,and 21.04%extended strands.NFKBIA,PAGE5,SPA17,and SAGE1 were four proteins that interacted with TSP50.Protean predicted that there were 14 regions with high antigenicity in TSP50.BepiPred-2.0 predicted 11 antigen-binding regions in TSP50,and ABCpred predicted that 37 peptides could serve as potential antigenic epitopes for TSP50.Conclusion This study integrates the prediction results from DNASTAR Protean,BepiPred-2.0,and ABCpred,and ultimately successfully predictes that TSP50 has 7 dominant antigenic epitopes.关键词
TSP50/生物信息学/理化性质/蛋白结构/抗原决定簇Key words
TSP50/Bioinformatics/Physicochemical properties/Protein structure/Epitope分类
医药卫生引用本文复制引用
金淑娟,乔晓婷..TSP50生物信息学分析及抗原决定簇预测[J].医学信息,2026,39(17):12-18,7.基金项目
深圳市科技计划项目(编号:JCYJ20230807153800002) （编号:JCYJ20230807153800002）
