摘要
目的:利用生物信息学网络资源分析融合蛋白的二级结构及其理化性质,以及探讨分泌型抗成骨肉瘤单链双功能抗体基因的表达.方法:采用PCR方法将人工合成的抗体分泌信号肽序列加在抗成骨肉瘤ScFv基因5′端,其3′与人的肿瘤坏死因子TNF-α基因连接构成分泌型单链双功能抗体ScFv-TNF-α基因,将该基因克隆至逆转录病毒表达载体PLx-SN,重组质粒pL(ScFv-TNF-α)SN在脂质体介导下转染PA317包装细胞,G418筛选,直至出现抗性克隆,扩大培养,用NIH3T3测定病毒滴度,将重组病毒感染人成骨肉瘤细胞命名为OSC/ScFv-TNF-α,以PCR,RT-PCR以及WesternBlot对ScFv-TNF-α基因修饰的OSC9901细胞进行鉴定.在构建融合蛋白之后,运用DNA分析软件(DNAssist)和蛋白质分析软件(ANTHEPROTV5)分析融合蛋白的氨基酸序列、二级结构及其理化性质.结果:经酶切分析鉴定,成功地构建了融合基因表达载体pL(ScFv-TNF-α)SN,以及WesternBlot分析证明ScFv-TNF-α基因融合蛋白的表达.运用DNAssist核酸序列分析软件分析ScFv-TNF-αDNA序列翻译并获得了氨基酸序列,运用蛋白质分析软件(ANTHEPROTV5)分析融合蛋白的二级结构及其理化性质.结论:利用生物信息学网络资源进行分析预测融合蛋白的性质,为进一步探讨单链双功能抗体基因融合蛋白提供依据.
AIM： To analyze the secondary structure of the fusion protein with bioinformatical approach, and to establish and express a recombinant secretory anti-osteogenic sarcoma singlechain bi-functional antibody gene. METHODS： By the technology of directional cloning, the sequenced genes were subcloned into corresponding restriction sites of PLxSN in turn to generate coexpression vector. The pL （ScFv-TNF-α）SN was packaged with PA317 and selected in G418 to obtain the positive clones, which were able to produce stable retrovirus, and then OSC9901 cells were infected by the recombinant retrovirus. The positive clones were obtained after G418 selection and were termed OSC/ScFv- TNF-α, and fusion protein was identified by Western blot in the transfected OSC9901 cells. In our works, DNAssist and ANTHEPROT V5 were used to analyze the fusion genes sequence, the secondary structure, and the physical and chemical characteristics. RESULTS： The inserted fragments in all constructed plasmids were structurally confirmed to he consistent with that of the published data. Similarly, the vectors pL （ ScFv-TNF-α ） SN was confirmed to be successful in the stable expression of the objective proteins in the target cells, and the expression of the recombinant protein was confirmed by Western blot. On the fusion genes, the secondary structure of the protein was analyzed with DNAssist, and the physical and chemical characteristics of the protein was forecasted with ANTHEPROT VS. CONCLUSION： The softwares which were downloaded from web should be fully used to analyze biologic information, and the approach may have application in a gene therapy context.
出处
《第四军医大学学报》
北大核心
2006年第24期2256-2258,共3页
Journal of the Fourth Military Medical University
关键词
单链抗体
生物信息学资源
融合蛋白
single-chain bi-functional antibody
bioinformaticalresource
fusion protein
