引用本文格式: 吴朋,邓聿杉,陈放,徐莺. Curcin和curcin C与腺嘌呤互作位点的比较分析 [J]. 四川大学学报: 自然科学版, 2020, 57: 1186~1192.
 
Curcin和curcin C与腺嘌呤互作位点的比较分析
Comparative analysis of the interaction sites of curcin, curcin C with adenine
摘要点击 121  全文点击 73  投稿时间:2020-03-09  修订日期:2020-04-24
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DOI编号   
中文关键词   麻疯树  核糖体失活蛋白  结构预测  分子对接  腺嘌呤
英文关键词   Jatropha curcas  Ribosome+inactivating protein  Structure prediction  Molecular docking  Adenine
基金项目   国家自然科学基金(31870315)
作者单位E-mail
吴朋 四川大学生命科学学院 生物资源与生态环境教育部重点实验室 1347357302@qq.com 
邓聿杉 四川大学生命科学学院 生物资源与生态环境教育部重点实验室  
陈放 四川大学生命科学学院 生物资源与生态环境教育部重点实验室  
徐莺 四川大学生命科学学院 生物资源与生态环境教育部重点实验室 xuying@scu.edu.cn 
Author NameAffiliationE-mail
WU Peng Key Laboratory of Bio-Resources and Eco-Environment Ministry of Education, College of Life Sciences, Sichuan University 1347357302@qq.com 
DENG Yu-Shan Key Laboratory of Bio-Resources and Eco-Environment Ministry of Education, College of Life Sciences, Sichuan University  
CHEN Fang Key Laboratory of Bio-Resources and Eco-Environment Ministry of Education, College of Life Sciences, Sichuan University  
XU Ying Key Laboratory of Bio-Resources and Eco-Environment Ministry of Education, College of Life Sciences, Sichuan University xuying@scu.edu.cn 
中文摘要
    麻疯树核糖体失活蛋白curcin和curcin C均具有抗肿瘤活性,但后者的活性水平显著高于前者,为了探索造成这一差异的结构基础,本文采用在线的同源建模预测软件SWISSMODEL,对两种麻疯树核糖体失活蛋白curcin、curcin C的三维结构模型进行预测,采用SYBYL对预测模型进行能量最小化优化,采用PROCHECK、VERIFY 3D和ERRAT软件对优化前后的模型进行质量评估,随后采用AutoDock软件将预测的模型与腺嘌呤进行分子对接分析.结果显示,两种蛋白采用与Ricin A类似的方式与腺嘌呤相互作用,但在相互作用的氨基酸残基种类、数量以及形成的氢键和疏水相互作用上还是存在差异,其中,curcin C与腺嘌呤具有最强的结合能力,curcin则最低.
英文摘要
    The ribosome-inactivating proteins of Jatropha curcas curcin and curcin C have antitumor activity, but the activity level of the latter is significantly higher than the former. In order to explore the structural basis for this difference, the online homology modeling prediction software SWISSMODEL was used to predict the three dimensional structural models of the ribosomal inactivating proteins curcin and curcin C. SYBYL was used to optimize the energy of the prediction model, and PROCHECK, VERIFY 3D and ERRAT software were used to evaluate the quality of the model before and after the optimization, and then AutoDock software was used to analyze the predicted model and adenine for molecular docking. The results show that the two proteins interacted with adenine in a similar way to Ricin A, but there were differences in the types and number of amino acid residues that interact, as well as the hydrogen bonds and hydrophobic interactions formed. Among them, curcin C had the strongest binding ability with adenine, and curcin had the lowest.

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