QSAR model for predicting the fungicidal action of 1,2,4-triazole derivatives against Candida albicans

Abstract

QSAR analysis of a series of previously synthesised 1-(1H-1,2,4-triazole-1-yl)-2-(2,4-difluorophenyl)-3-substituted-2-propanols(TDFPP) as analogues of fluconazole were tested for growth inhibitory activity against Candida albicans using computer assisted multiple regression analysis. This was in order to explore the selectivity requirements for fungicidal activity against C. albicans among these congeners. A training set comprising 40 analogues and a test set comprising ten analogues of 1-(1H-1, 2, 4-triazole-1-yl)-2-(2,4-difluorophenyl)-3-substituted-2-propanols were selected for the present investigation by using the sphere exclusion method embedded in the Vlife MDS 3.5 software. With respect to the modelling of the growth inhibitory activity of the reported compounds, the regression analysis shows that even in the mono-parametric correlations the topological and physicochemical parameters give significant regression coefficients. The validation of the QSAR models was performed by cross-validation and external test set prediction. The model is not only able to predict the activity of new compounds but also explains the important region in the molecules in a quantitative manner.

Keywords::

• 2D-QSAR
• 1; 2; 4-triazole
• MDS; multiple regression analysis
• Candida albicans

Acknowledgements

The authors would like to thank Vlife Company for providing such user friendly software. The authors would also like to thank Xiaoyun Chai et al, Takuya Uchida and colleagues for providing the study literature.

Declaration of interest

The authors would like to thank Manipal University for funding of the software. The authors have no conflicting financial interests.