Antifungal activity of amino-alcohols based cationic surfactants and in silico, homology modeling, docking and molecular dynamics studies against lanosterol 14-α-demethylase enzyme

Abstract

Fungi are being responsible for causing serious infections in humans and animals. The opportunistic microorganisms provoke environmental contaminations in health and storage facilities to represent a serious concern to health security. The present work investigates the antifungal activity of two amino-alcohols based cationic surfactants such as C n EtOH, C n PrOH (with n = 14 and 16 are the carbon numbers of alkyl chain and EtOH = Ethanol and PrOH = Propanol) against a collection of different Candida species (Candida tropicalis, Candida albicans, Candida auris, Cyberlindnera jadinii, Candida parapsilosis, Candida glabrata and Candida rugosa) respectively. The amino-alcohols based cationic surfactants exhibited good antifungal activity against all Candida strains tested with minimum inhibitory concentrations (MIC) ranging from 0.002 to 0.30 mM. The MIC evaluation shows an increase as a function of the hydrophobicity of all inhibitors against the majority of the Candida strains tested. The different location of the alcoholic OH function in the polar head shows the influence on the availability of N+ responsible for electrostatic interactions with the candidate’s cell walls, which remains a very important step in the mode of action of quaternary ammonium cationic surfactants. Hence, a 3D structure of lanosterol 14-α-demethylase enzyme from C. auris was constructed by homology modeling using an online SWISS-MODEL server. The predicted model was analyzed by serval servers. Furthermore, a molecular docking study was carried out to better understand the binding mechanism of lanosterol homologous protein with surfactant ligands. Then, the docked complexes lanosterol–surfactants were refined by the molecular dynamic simulation to analyze their interaction behavior during the simulation. Communicated by Ramaswamy H. Sarma