Design of anti-fungal agents by 3D-QSAR
Abstract
An increase in the number of invasive fungal infections especially in immunocompromised patients is increasing the mortality rate worldwide. Due to the emergence of drug-resistant fungi, the currently available antifungal drugs have become ineffective. Because no alternative treatment is available, some existing drugs are still used. Therefore, there is a need to design and develop novel and effective anti-fungal drugs. Molecular docking and 3-dimensional quantitative structure-activity relationship (3D-QSAR) methods have been useful approaches for the design of novel molecules. A set of 30 molecules reported in the literature containing azoles and non-azoles have been used in this study to derive 3D-QSAR.CoMFA and CoMSIA models for the most active compound and least active compounds have been developed. The structural requirements were obtained by analysing the contour maps. The partial least square analysis for CoMFA and CoMSIA showed a significant cross-validated correlation coefficient of 0.625 and 0.67 and a non-cross validated correlation coefficient of 0.991 and 0.99, respectively. The model was validated by observing the predicted correlation for test molecules with the value of 0.699 and 0.659, respectively.
Keyword(s)
Azoles, Anti-fungal, 3D-QSAR, CoMFA, CoMSIA
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