辛诺柏病毒抑制肽的定量构效关系研究及优化设计

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卢永忠, 康道乐

（青岛科技大学 化工学院，山东 青岛 266042）

摘要： 利用多肽分子整体描述符，对70条辛诺柏病毒(sin nombre virus,SNV)抑制肽的结构和理化性质进行表征，结合遗传算法进行变量筛选，并借助偏最小二乘算法建立定量构效关系（QSAR）模型，对多肽进行优化设计。基于遗传算法-偏最小二乘算法的QSAR模型具有较好的预测能力（R²>0.84,Q²_ext>0.61）；依据模型设计出了一组具有较高预测活性的多肽。建立的QSAR模型对辛诺柏病毒抑制肽的优化设计具有指导作用，为高活性抗病毒多肽的合成和实验验证打下了基础。

关键词：  辛诺柏病毒； 病毒抑制肽； 定量构效关系研究； 遗传算法； 偏最小二乘法

中图分类号： Q 514文献标志码： A

Optimization and Quantitative Structure-activity Relationships Research on Sin Nombre Virus Inhibitory Peptides

LU Yongzhong, KANG Daole

(CollegeofChemical Engineering,QingdaoUniversityof Science and Technology,Qingdao266042,China)

Abstract: A group of cyclic nonamer peptides exhibited SNV inhibitory activity, and were of potential value for therapy, so in this work they were optimized based on quantitative structure-activity relationships(QSAR) research. The structural and physicochemical features of seventy SNV inhibitory peptides were described from the whole molecular aspect, and the Genetic algorithm-Partial least squares(GA-PLS)models were built and applied to optimize the sepeptides. The QSAR models were exhibited good performance in stability and predictability(R²>0.84,Q²_ext>0.61). A group of peptides with higher activity were designed based on these models. The QSAR models can help to optimize the SNV inhibitory peptides,which will lay foundation for further synthesis and experimental test.

Key words: Sin Nombre virus; inhibitory peptide; quantitative structure-activity relationships; genetic algorithm; partial least squares

收稿日期： 20150415

作者简介： 卢永忠（1968—），男，副教授.

文章编号： 16726987（2016）05048405； DOI： 10.16351/j.16726987.2016.05.003