高等学校化学学报

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氨基酸描述子SZOTT用于多肽定量序效建模研究

梁桂兆1,2,3, 梅虎1,3, 周原1,2,3, 杨善彬1,3, 吴世容1,2, 李志良1,2
  

    1. 重庆大学化学化工学院药学系, 重庆400044;
    2. 湖南大学化学生物传感与计量学国家重点实验室, 湖南 410082;
    3. 重庆大学生物力学与组织工程教育部重点实验室, 重庆 400030
  • 收稿日期:2005-08-15 修回日期:1900-01-01 出版日期:2006-10-10 发布日期:2006-10-10
  • 通讯作者: 李志良

Using SZOTT Descriptors for the Development of QSAMs of Peptides

LIANG Gui-Zhao1,2,3, MEI Hu1,3, ZHOU Yuan1,2,3, YANG Shan-Bin1,3, WU Shi-Rong1,2, LI Zhi-Liang1,2   

    1. Department of pharmacy, College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China;
    2. State Key Laboratory for Chemobiosensors and Chemobiometrics under MOST, Hunan University, Changsha 410012, China;
    3. MOE Key Laboratory of Biomechanics and Tissue Engineering, Chongqing University, Chongqing 400030, China
  • Received:2005-08-15 Revised:1900-01-01 Online:2006-10-10 Published:2006-10-10

摘要: 在相关研究的基础上, 提出一新的氨基酸描述子SZOTT, 该描述子所含信息量大, 且操作简便. 将其用于两类肽体系序列表征, 用偏最小二乘和正交信号纠正-偏最小二乘建模, 获得较好的建模结果.

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

Abstract: A new descriptor, namely scores vector of zero dimension,one dimension,two dimension and three dimension (SZOTT), was derived from principle components analysis of a matrix of 1 369 structural variables including 0D, 1D, 2D and 3D information for 20 coded amino acids. SZOTT scales were then employed to express structures of 20 thromboplastin inhibitors and 34 bactericidal peptides. The correlation coefficients of both whole calibration (R2=R2cu) and of cross validation (Q2=R2cv) for the multiple-variable models by classical partial least squares (PLS) and orthogonal signal correction-partial least squares (OSC-PLS) of 20 thromboplastin inhibitors were 0.989 and 0.748, 0.994 and 0.936, respectively. R2 and Q2 for the models by PLS and OSC-PLS of 34 bactericidal peptides were 0.619 and 0.406, 0.910 and 0.503, respectively. Satisfactory results obtained showed that structural information related to biological activity in both data sets could be described by SZOTT which included plentiful information related to biological activity, and which was conveniently operated and easy interpreted, also predictive capability of models were relative robust. There is a high prospect for SZOTT wide applications on quantitative sequence-activity modeling (QSAM) of peptides.

Key words: SZOTT descriptor of amino acid, Peptide, Quantitative sequence-activity modeling(QSAM), Partial least squares(PLS)

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