Molecular Docking and QSAR studies for Modeling Antifungal Activity of Triazine Analogues against Therapeutic Target NMT of Candida albicans
Abstract
The s-triazine derivatives have been attracting the attention of researchers due to a broad range of biological applications. Present research deals with combination of GA- MLR based QSAR modeling and molecular docking as relevant to triazine analogues in an attempt to investigate their role as novel NMT inhibitors of Candida albicans. A penta-varient model which assure all validation criteria up to considerable echelon (R2 = 0.792, Q2 = 0.679 and = 0.603) supplemented by multicollinearity diagnosis by VIF and tolerance data analysis, signaling the robustness of the QSAR model. The descriptors RDF040v, Ds, Mor04m, X4v and MATS2p in the projected QSAR model have quantified the role of atomic properties such as topology; atomic van der Waals volume, mass and polarizability execute vital part to modify the antifungal activity of compounds under investigation. Further, molecular docking simulation study revealed that three compounds in particular showed superior binding affinity with re-rank score of -142.594, -138.972, -137.540 kcal/mol respectively. Consequently this study may turn out to be helpful towards development and optimization of existing antifungal activity of compounds under investigation.
Keywords:
QSAR, Molecular Docking, Candida Albicans, NMT inhibitors, Anti fungal, drug developmentDOI
https://doi.org/10.25004/IJPSDR.2021.130204References
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