Ding Jun-jie, Ding Xiao-qin, Zhao Li-feng, Chen Ji-sheng
Beijing Institute of Pharmaceutical Chemistry, Beijing 102205, China.
Yao Xue Xue Bao. 2005 Apr;40(4):340-6.
To establish a new amino acid structure descriptor that can be applied to polypeptide QSAR studies.
The new amino acid structure descriptor c-scales were derived from a principal components analysis of 167 amino acid structure descriptor indexes by theoretic calculation. The c1,c2,c3-scales were related to 3D structural features of amino acid such as steric, electronic and conformation properties etc. G/PLS regression method was used to find out the relationship between the c-scales and the biological activity and developed QSAR models of the polypeptides.
Using the established method, we developed accordingly QSAR models of Bitter tasting dipeptide, ACE inhibitors and bradykinin-potentiating pentapeptides and their r2 and XV-r2 were more than 0.70.
The c-scales can quantitatively describe the 3D structural features of any coded and non-coded amino acid and can be used to establish a QSAR model of good predictability.
建立一种可应用于多肽定量构效关系（QSAR）研究的新型氨基酸结构描述符。
通过理论计算，从167个氨基酸结构描述符指标的主成分分析中得出新型氨基酸结构描述符c-标度。c1、c2、c3-标度与氨基酸的三维结构特征相关，如空间、电子和构象性质等。采用广义偏最小二乘（G/PLS）回归方法找出c-标度与生物活性之间的关系，并建立多肽的QSAR模型。
利用所建立的方法，相应地建立了苦味二肽、血管紧张素转换酶（ACE）抑制剂和缓激肽增强五肽的QSAR模型，其r2和XV-r2均大于0.70。
c-标度可以定量描述任何编码和非编码氨基酸的三维结构特征，并可用于建立具有良好预测能力的QSAR模型。
