Experimental and modelling studies on antifungal compounds

Abstract

Antifungal activity of organic compounds (aromatic, salicylic derivatives, cinnamyl derivatives etc) on Fusarium Rosium (14 compounds) and Aspergillus niger (17 compounds) was studied and QSAR models were developed relating molecular descriptors with the observed activity. Back propagation Neural Network models and single and multiple regression models were tested for predicting the observed activity. The data fit as well as the predictive capability of the neural network models were satisfactory (R 2 = 0.84, q 2 = 0.73 for Fusarium Rosium and R 2 = 0.75, q 2 = 0.62 for Aspergillus niger ). The descriptors used in the network for the former were X4 (connectivity) and Jhetv (topological); and TIC1 (information) and SPI (topological) for the latter fungus. Antifungal activities of these organic compounds were generally lower against the latter than with the former fungus.

Synthesis, anti-fungal activity evaluation and QSAR studies on podophyllotoxin derivatives

“…The literature reports the use of structural descriptors for developing QSAR for several fungi [14,17]. The topology descriptor has been used for developing QSAR for predicting the activity of small organic molecules towards Fusarium Rosium and Aspergillus niger [25]. Structural, thermodynamic and molecular operating environment descriptors have been reported by researchers developing QSAR for podophyllotoxin compounds [5,10].…”