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A Computational Approach to Predict the Molecular Drug Targets Against Candida glabrata

Non- albicans Candida (NAC) species are responsible for 35-65% of all candidaemias in the general population and are associated with a high rate of morbidity and mortality (about 15% to 35%). The availability of few commercially used antifungal drugs against candidiasis and rapid emergences of antibiotic resistance among NAC species has significantly contributed to their increased global outbreak. Green tea is known for its multi-beneficial effects including antimicrobial potential against Candida. The present study investigated the molecular drug targets of green tea phytocompounds against inhibition of ergosterol biosynthesis in Candida glabrata using in silico tools.The molecular interaction was studied between ligands and essential proteins participating in ergosterol biosynthesis in C. glabrata using autodockvina software. The protein validation and homology modeling estimation were determined by the SWISS MODEL workspace. The Drug likeness study of all the test ligands was performed using SwissADME, while the toxicity of test compounds was analyzed using the admetSAR 2.0 version.The in silico analyses identified Rutin, Chlorogenic acid, Coumaroylquinic acid, Quercetin, Epigallocatechingallate as the potent phytocompounds with significant molecular binding with Erg 6, Erg 27, Erg 8, Erg 7, Erg 24 respectively. The ADMET data suggested an absence of the CYP2 inhibitors indicating the metabolism of all the tested drug candidates in the intestine and liver.The present study highlighted the possible drug targets of green tea phytocompounds against ergosterol biosynthesis protein in C. glabrata. It is pertinent that the current study has provided preliminary breakthroughs which could lead to exploring their avenues in potent drug development against NAC species.