Quantitative structural–activity relationship (QSAR) study for fungicidal activities of thiazoline derivatives against rice blast

For the development of new fungicides against rice blast, the quantitative structural–activity relationship (QSAR) analyses for fungicidal activities of thiazoline derivatives were carried out using multiple linear regression (MLR) and neural network (NN). We have studied the substituent effects at para site of R1 and at three sites (ortho, meta, or para) of R2 aromatic rings in compounds. The results of MLR and NN analyses in the training set of Set-3 showed good correlations (r2 values of 0.829 and 0.966, respectively) between the descriptors and the fungicidal activities. Five descriptors including the non-overlap steric volume (SVR2C2)(SVR2C2), Connolly surface area (SAR1)(SAR1), hydrophobicity (∑πR2)(∑πR2), and Hammett substituent constants (σpR1σpR1 and σmR2σmR2) were selected as important factors of fungicidal activities. Although the descriptors of optimum MLR model were used in NN, the results were improved by NN. This means that the descriptors used in MLR model include non-linear relationships.

Graphical abstractFor the development of new fungicides from thiazoline derivatives against rice blast, the quantitative structural–activity relationship (QSAR) analyses were performed using multiple linear regression (MLR) and neural network (NN).Figure optionsDownload full-size imageDownload as PowerPoint slide