QSAR modeling of iNOS inhibitors based on a novel regression method: Multi-stage adaptive regression
QSAR modeling of iNOS inhibitors based on a novel regression method: Multi-stage adaptive regression
复制标题
基于新型回归方法的 iNOS 抑制剂的 QSAR 建模：多阶段自适应回归
DOI：
10.1016/j.chemolab.2013.07.011
复制
发表时间：
2013-10-15
影响因子：
3.9
通讯作者：
Fan, Saijun
中科院分区：
文献类型：
--
作者：
Long, Wei;Xiang, Jian;Fan, Saijun
采用一种新的回归方法--多阶段自适应回归(MAR)，建立了iNOS抑制化合物的定量构效关系(QSAR)模型。这个模型是基于从分子结构计算出来的描述符。通过最佳多元线性回归(BMLR)方法从描述符池中选择6个描述符。对于训练集和测试集，MAR方法得到了良好的模型，相关系数的平方(R-2)分别为0.92和0.86。同时，利用BMLR建立了竞争模型。结果表明，MAR模型比BMLR模型具有更好的预测能力和更高的可靠性。这表明MAR在定量构效关系研究中可能是一种很有前途的方法。(C)2013爱思唯尔B.V.保留所有权利。
A novel regression method, multi-stage adaptive regression (MAR), was employed to build a quantitative structure-activity relationship (QSAR) model for predicting iNOS inhibitory compounds. This model is based on descriptors which are calculated from the molecular structure. Six descriptors are selected from the pool of descriptors by best multiple linear regression (BMLR) method. The MAR method produced a good model with the square of correlation coefficient (R-2) 0.92 and 0.86 for the training and test set, respectively. Meanwhile, a competing model was built by using BMLR. The results show that the MAR model has better predictive ability and more reliable than the BMLR model. This indicates that MAR could be a promising method in QSAR studies. (C) 2013 Elsevier B.V. All rights reserved.