Identification of Potential Candida albicans Inhibitors Through Pharmacophore Modeling and Virtual Screening Techniques

Abstract

Fungal infections have increased significantly in recent years and represent a major threat to human health. A large number of these infections are caused by the opportunistic pathogen Candida albicans. Lanosterol 14-alpha demethylase (CYP51), a critical enzyme in the cytochrome P450 family, is a well-established target for antifungal drugs. However, the development of resistance to current antifungal treatments has created an urgent need to develop new inhibitors that are more effective and less likely to promote the emergence of resistance in candida albicans. Azoles are a large and relatively new group of synthetic compounds, of which imidazoles and triazoles are two clinically useful families used in the treatment of systemic fungal infections. In this study, we focused on Candida albicans and used the target protein (PDB code: 1EA1) to perform an In silico analysis of a series of benzimidazole derivatives. The aim was to identify novel chemotherapeutic agents with potential antifungal activity. To discover new Candida albicans inhibitors, pharmacophore models based on the molecular structure of benzimidazole derivatives were generated and validated using various methods. A virtual screening of the Enamine database containing 535,326 molecules was performed based on the combinatorial pharmacophore model. Compounds selected after virtual screening were subjected to molecular docking protocols (HTVS, SP, XP and IFD). 26 new compounds were identified and their absorption, distribution, metabolism and excretion (ADME) properties were calculated. These results suggest that the identified compounds could serve as promising chemical starting points for further structural optimisation in the development of Candida albicans inhibitors.