The development of 3D-QSAR study and recursive partitioning of heterocyclic quinone derivatives with antifungal activity

It was reported that some 1,4-quinone derivatives such as 6-(N-arylamino)-7-chloro/6,7-bis[S-(aryl)thio]-5,8-quinolinedione and 6-arylthio-/5,6-arylamino-4,7-dioxobenzothiazoles have antifungal effects. To understand the structural basis for antifungal activity and guide in the design of more potent agents, we performed three-dimensional quantitative structure–activity relationship studies for a series of compounds using comparative molecular field analysis (CoMFA). The MIC values of 1,4-quinone derivatives on Aspergillus niger exhibited a strong correlation with steric and electrostatic factors of the 3D structure of molecules. The statistical results of the training set, cross-validated q2 (0.683) and conventional r2 (0.877) values, gave reliability to the prediction of inhibitory activity of a series of compounds. We also performed recursive partitioning (RP) analysis, used for the classification of molecules with activity using CART methods. Physicochemical, structural, and topological connectivity indices and E-state key descriptors were used for obtaining the decision tree models. The decision tree could classify the inhibitory activity of 1,4-quinone derivatives and its essential descriptors were S_aaN, Hbond donor, and Kappa-3.

Quantitative structure–activity relationship studies for antifungal 1,4-quinone derivatives using comparative molecular field analysis (CoMFA) and recursive partitioning (RP) analysis are reported.Figure optionsDownload as PowerPoint slide