高等学校化学学报

高等学校化学学报

• 研究论文 • 上一篇    下一篇

氨基酸描述子VHSEH用于多肽定量序效建模研究

杨善彬1,2,4, 夏之宁1,2, 舒茂1,2, 梅虎1,2, 吕凤林3, 张梅5, 吴玉乾2, 李志良1,2   

    1. 重庆大学生物工程学院,
    2. 化学化工学院, 重庆 400044;
    3. 第三军医大学野战外科研究所, 重庆 400038;
    4. 宜宾学院化学与化工系, 宜宾 644000;
    5. 重庆大新药业有限公司质检部, 重庆 400700
  • 收稿日期:2008-01-29 修回日期:1900-01-01 出版日期:2008-11-10 发布日期:2008-11-10
  • 通讯作者: 夏之宁

VHSEH Descriptors for the Development of QSAMs of Peptides

YANG Shan-Bin1,2,4, XIA Zhi-Ning1,2*, SHU Mao1,2, MEI Hu1,2 , LÜ Feng-Lin3, ZHANG Mei5, WU Yu-Qian2, LI Zhi-Liang1,2   

    1. College of Bioengineering,
    2. College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400030, China;
    3. Faculty of Clinical Laboratory Sciences, PLA Third Military Medical University, Chongqing 400038, China;
    4. Department of Chemistry and Chemical Engineering, Yibin University, Yibin, Sichuan 644000, China;
    5. Department of Quality Control, Chongqing Daxin Pharmaceutical Co. Ltd., Chongqing 400700, China
  • Received:2008-01-29 Revised:1900-01-01 Online:2008-11-10 Published:2008-11-10
  • Contact: XIA Zhi-Ning

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被引次数

20

摘要： 从20 种天然氨基酸的171个物化性质出发, 按照疏水、立体和电性特征及氢键贡献将其分类后, 分别进行主成分分析, 得到一个新描述子VHSEH(Principal component score vector of hydrophobic, steric, electronic properties and, hydrogen bonds contributions). 对后叶催产素的结构进行了表征, 并以偏最小二乘法及D-优化划分样本建立了PLS定量序效关系模型, 得到复相关系数R2分别为 0.958 和 0.957, Q2分别为0.903和0.845, 约高于VHSE描述子模型值; 对抗菌肽进行了结构表征, 建立了PLS和OSC-PLS模型, 其R2分别为0.84和 0.995, Q2分别为0.546和0.926, 较SZOTT描述子结果好; 对58 个血管紧张素转化酶抑制剂进行QSAM研究, 得到R2, Q2及RMS分别为0.877, 0.838和0.361. 研究结果表明, VHSEH 描述子信息量大, 物化意义明确, 结果更易解释.

关键词: 氨基酸描述子(VHSEH), 肽, 定量序效建模(QSAM), 偏最小二乘法

Abstract: A new set of descriptors, VHSEH(principal component score vector of hydrophobic, steric, electronic properties, and hydrogen bonds contributions), was derived from principal components analyses of 171 physicochemical variables of 20 natural amino acids separately according to different properties described, namely, hydrophobic, steric, and electronic properties, hydrogen bonds contributions. VHSEH scales were employed to express the structures of oxytocin analogues, antimicrobial peptides and angiotensin-converting enzyme inhibitors. The correlation coefficients R2 and cross validation Q2 for the multiple-variable models by PLS and PLS by D-Optimal Designs of oxytocin analogues were 0.958 and 0.903, 0.957 and 0.845, respectively. R2 and Q2 for the models by PLS and OSC-PLS of bactericidal peptides were 0.84 and 0.546, 0.995 and 0.926, respectively. The value of R2, Q2 and RMS in the PLS model of angiotensin-converting enzyme inhibitors were 0.877, 0.838 and 0.361, respectively. Satisfactory results show that, as new amino acid scales, data of VHSEH may be a useful structural expression methodology for the study on quantitative sequence-activity modeling(QSAM) of peptides, due to its many advantages such as plentiful structural information, definite physical and chemical meaning and easy interpretation.

Key words: VHSEH descriptors of amino acid, Peptide, Quantitative sequence-acitivty modeling(QSAM), Partial least squares(PLS)

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