Hoffman B, Cho S J, Zheng W, Wyrick S, Nichols D E, Mailman R B, Tropsha A
Division of Medicinal Chemistry and Natural Products, School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina 27599, USA.
J Med Chem. 1999 Aug 26;42(17):3217-26. doi: 10.1021/jm980415j.
Several quantitative structure-activity relationship (QSAR) methods were applied to 29 chemically diverse D(1) dopamine antagonists. In addition to conventional 3D comparative molecular field analysis (CoMFA), cross-validated R(2) guided region selection (q(2)-GRS) CoMFA (see ref 1) was employed, as were two novel variable selection QSAR methods recently developed in one of our laboratories. These latter methods included genetic algorithm-partial least squares (GA-PLS) and K nearest neighbor (KNN) procedures (see refs 2-4), which utilize 2D topological descriptors of chemical structures. Each QSAR approach resulted in a highly predictive model, with cross-validated R(2) (q(2)) values of 0.57 for CoMFA, 0.54 for q(2)-GRS, 0.73 for GA-PLS, and 0.79 for KNN. The success of all of the QSAR methods indicates the presence of an intrinsic structure-activity relationship in this group of compounds and affords more robust design and prediction of biological activities of novel D(1) ligands.
几种定量构效关系（QSAR）方法被应用于29种化学结构各异的D(1)多巴胺拮抗剂。除了传统的三维比较分子场分析（CoMFA）外，还采用了交叉验证R(2)引导区域选择（q(2)-GRS）CoMFA（见参考文献1），以及我们实验室最近开发的两种新型变量选择QSAR方法。后两种方法包括遗传算法-偏最小二乘法（GA-PLS）和K最近邻（KNN）程序（见参考文献2-4），它们利用化学结构的二维拓扑描述符。每种QSAR方法都得到了一个高度预测性的模型，CoMFA的交叉验证R(2)（q(2)）值为0.57，q(2)-GRS为0.54，GA-PLS为0.73，KNN为0.79。所有QSAR方法的成功表明这组化合物中存在内在的构效关系，并为新型D(1)配体的生物活性提供了更可靠的设计和预测。
