一种新氨基酸描述子用于ACE抑制肽QSAR研究

A New Kind of Amino Acid Descriptor for ACE Inhibition QSAR study

摘要:

本文从20种天然氨基酸的41个randic molecular profiles非零描述符、44个eigenvalue based indices非零描述符和47个walk and path counts非零描述符分别进行主成分分析，得出一种新的氨基酸描述符－SVREW。将其应用于血管紧张素转化酶抑制二肽、三肽、四肽、九肽结构表征，应用多元线性回归(MLR)建立定量构效关系，同时采用内部与外部双重验证的方法验证模型的稳定性。所建ACE 抑制二肽、三肽、四肽、九肽、模型复相关系数（Rcum2）、留一法（LOO）交互校验复相关系数（Rcv2）、和外部样本校验复相关系数（Qext2）分别为：0.907、0.791、0.633；0.831、0.603、0.723；0.834、0.668、0.718；0.964、0.853、0.948。经研究表明SVREW描述符应用于ACE抑制肽结构表征所建模型模型稳定性与预测能力均较好，有望成为多肽定量构效关系研究中一种有效的结构表征方法，并对新药物的发现和研究提供指导。 关键词：定量构效关系；氨基酸描述子；血管紧张素转化酶抑制肽；多元线性回归；

Abstract:

A new descriptor of amino acids-SVREW was derived from principal components analysis of the matrix of 47 walk and path counts descriptors, 44 eigenvalue-based indices descriptors and 41 randic molecular profiles descriptors of amino acids. The structure of ACE Inhibition Peptides was characterized with SVREW, using multiple linear regression (MLR) to establish a quantitative structure-activity relationship, at the same time, adopt the method of internal and external double verify the stability of the model. The relevant statistical parameters as follows: the correlation coefficient (Rcum2), leava-one-out(LOO) cross-validation correlation coefficient (Rcv2) and external validation correlation coefficient (Qext2) were 0.907, 0.791, 0.633 for dipeptides model; 0.831, 0.603, 0.723 for tripeptides model; 0.834,0.668,0.718 for tripeptides model 0.964, 0.853, 0.948 for nonapeptides model; Studies show that the MLR models constructed by SVREW descriptor had good fitting and predictive abilities,to become an effective structure characterization methods in peptide drugs QSAR study and provide guidance for new drug discovery and research.