一种新的三维氨基酸描述子及其在肽类药物QSAR中的应用

A New 3D-Descriptor of Amino Acids and Its Application in Quantitative Structure Activity Relationship of Peptide Drugs

从20种天然氨基酸197个GETAWAY指数经主成分分析得出一种新3D氨基酸描述子——VSGETAWAY[vector of principal component scores for GETAWAY(geometry,topology and atom-weights assembly)].将其应用于48个苦味活性二肽、31个血管舒缓激肽促进剂和20个促凝血酶原激酶抑制剂结构表征并以偏最小二乘(PLS)对3个体系建立定量构效关系(QSAR)模型,得复相关系数(Rc2um)与交互检验复相关系数(Qc2um)分别为0.887和0.753;0.995和0.708;0.999和0.802.研究结果表明,VSGETAWAY描述子操作简便、结构表达能力强,有望成为多肽药物QSAR研究中一种有效的结构表征方法.

A new descriptor, vector of principal component scores for GETAWAY index, was derived from a principal components analysis of a matrix of 197 GETAWAY indexes of 20 natural amino acids. The scale was then applied to construct three panels of polypeptide quantitative structure activity relationship （QSAR） based on partial least squares （PLS） regression. The correlation coefficient （R^2 cum） and cross-validation correlation coefficient （Q^2 cum） of the obtained models were 0.887 and 0.753 for 48 bitter tasting dipeptides, 0.995 and 0.708 for 31 bradykinin- potentiating pentapeptides, 0.999 and 0.802 for 20 thromboplastin inhibitors, respectively. The satisfactory results showed that, as new amino acid scales, data of VSGETAWAY may be a useful structural expression methodology for study on peptide QSAR due to its many advantages such as easy manipulation, plentiful structural information and high characterization competence.