Acta Chimica Sinica ›› 2006, Vol. 64 ›› Issue (5): 393-396. Previous Articles     Next Articles

Original Articles

一组新氨基酸描述子用于肽定量构效关系研究

梁桂兆1,2,3,周鹏1,周原1,2,3,张巧霞1,李志良*,1,2   

  1. (1重庆大学化学化工学院 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 长沙 410082)
    (3重庆大学生物工程学院 重庆 400044)
  • 投稿日期:2005-06-15 修回日期:2005-11-03 发布日期:2006-03-15
  • 通讯作者: 李志良

New Descriptors of Aminoacids and Their Applications to Peptide Quantitative Structure-Activity Relationship

LIANG Gui-Zhao1,2,3, ZHOU Peng1, ZHOU Yuan1,2,3, ZHANG Qiao-Xia1, LI Zhi-Liang*,1,2   

  1. (1 College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044)
    (2 State Key Laboratory of Chemo/Biosensing and Chemometrics at Hunan University, Changsha 410082)
    (3 College of Bioengineering, Chongqing University, Chongqing 400044)
  • Received:2005-06-15 Revised:2005-11-03 Published:2006-03-15
  • Contact: LI Zhi-Liang

A new set of descriptors, namely vector of scores for zero dimension, one dimension, two dimension and three dimension (SZOTT), was derived from principle component analysis of a matrix of 1369 structural variables of 0D~3D information for 20 coded aminoacids. SZOTT scales were then employed to express structures of angiotensin-converting enzyme inhibitors and bitter tasting thresholds, and to construct QSAR models based on partial least square (PLS). The results obtained are as follows: the multiple correlation coefficient (RCU2) of 0.894 and 0.908, the leave one out cross validated RCV2 of 0.828 and 0.736, and root-mean-square error for estimated error (RMS) of 0.331 and 0.195, respectively. Satisfactory results showed that, as new aminoacid scales, data of SZOTT may be a useful structural expression methodology for study on peptide QSAR (quantitative structure-activity relationship) due to its many advantages such as plentiful structural information, easy manipulation, and high characterization competence.

Key words: peptide, quantitative structure-activity relationship, principal component analysis, genetic algorithm, partial least square