Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1181016 | Chemometrics and Intelligent Laboratory Systems | 2013 | 6 Pages |
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 (R2) 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.