摘要
目的 :利用噬菌体随机环七肽库在小鼠肾包膜下荷人胃癌模型体内筛选能够与人胃癌血管内皮细胞结合的特异性分子 ,对其多肽进行计算机空间结构模拟分析 .方法 :制备免疫抑制小鼠肾包膜下人胃癌移植瘤模型 ,用随机环七肽库在其体内进行 4轮筛选 ,对随机获得的 14个克隆进行测序 .通过细胞ELISA检测所得到的特异性小肽在脐静脉内皮细胞(HUVEC) ,SGC790 1,LoVo,Eca 10 9及Hep G2细胞系上的结合能力 .并通过计算机分子模拟多肽CGNSNPKSC的空间结构 .结果 :成功获得 14个噬菌体克隆 ,并呈现出 2种氨基酸序列 ,其中多肽CGNSNPKSC ,相比于对照细胞SGC790 1,LoVo ,Eca 10 9,Hep G2 ,其同HUVEC结合能力明显增强 .利用计算机技术成功地模拟并分析了该多肽的空间结构 .结论 :多肽CGN SNPKSC同血管内皮细胞结合能力较强 ;空间结构稳定 ,是一个高亲水多肽 ,更容易形成折曲的抗原表位 ,很有可能是一个极具肿瘤血管靶向治疗前景的多肽 .
AIM: To identify and analyze a peptide binding specifically to blood vessels of human gastric cancer by phage displayed C7C peptide library in vivo and to model its three dimensional structure of the peptide by computer. METHODS: Animal models were established using subrenal capsular assay (SRCA) in immunosupressed mice implanted with human gastric cancer xenografts. The phage displayed C7C peptide library was injected intravenously into mice. After 4 rounds of selection, 14 clones were picked up randomly and sequenced individually. The homing ability to human umbilical vein endothelial cells (HUVEC ) of peptide CGNSNPKSC was determined by cell-ELISA, with SGC7901, Eca-109, LoVo and Hep-G2 cells as control. Its three dimensional structure of peptide CGNSNPKSC was also established by computer modeling techniques. RESULTS: Fourteen clones were obtained and they displayed two kinds of peptides. The binding ability of a cyclic peptide of CGNSNPKSC toward HUVEC was higher than that of SGC7901, Eca-109, Hep-G2 and LoVo cells. The three dimensional structure of the peptide of CGNSNPKSC was modeled successfully. CONCLUSION: The peptide of CGNSNPKSC has high binding ability to HUVEC and its stable structure and highly hydrophilic character help it form a flexible epitope of antigen. The peptide of CGNSNPKSC can be used in target therapy of tumor angiogenesis.
出处
《第四军医大学学报》
CAS
北大核心
2004年第21期1958-1961,共4页
Journal of the Fourth Military Medical University
基金
国家自然科学基金 (30 1 30 2 60
30 0 2 4 0 0 2 )
关键词
胃癌
噬菌体随机肽库
血管生成
多肽
结构模拟
gastric cancer
phage displayed peptide library
angiogenesis
peptides
structure modeling