Virtual screening of azoles libraries: the search for potential anti-mucormycotic agents using computational tools

Abstract Mucormycosis is a severe fungal infection caused by filamentous mould fungi belonging to the Mucorales order. Recently, the incidence of mucormycosis has been increased, especially in India and China. The emergence of multi-drug resistance invasive fungal strains and the high toxicity of the current antifungal therapy have increased the mortality rate of mucormycosis. This study aimed to suggest azoles as potential treatment for mucormycosis. Azoles are proven to have antifungal effects, and they are commonly used in the market to treat fungal infections. In this study, we conducted a virtual screening of more than 50,000 azoles retrieved from the COCONUT and the ChEMBL databases for anti-fungal activity against mucormycosis. This study was performed by molecular docking against a 1,3-beta-glucan synthase to identify potential inhibitors where iturin A was used as a positive control. In silico prediction of the pharmacokinetics properties were also performed using the ADMETLab and SwissADME servers as a second screening step. Molecular dynamics simulation and pharmacophore modelling were performed to investigate the stability of the ligand and protein complexes and to determine the main pharmacophoric features. Thuggacin B (1) and a ritonavir analogue (2) showed the highest binding affinity to the target protein and favourable pharmacokinetics properties among the screened azoles. This study identified the important pharmacophoric features and interacting residues that drive the inhibitory activity of 1,3-beta-glucan synthase which is valuable in the screening studies to find potential inhibitors for this biological target. In conclusion, compounds (1) and (2) are of great interest for further study as a potential treatment of mucormycosis. However, a computational approach was used in this study, thus more in vitro investigation is required.