Abstract

Background: Candida albicans is a fungal species associated with opportunistic fungal infectious agents in human populations, especially in immunocompromised patients, such as transplant patients, HIV-positive patients, chemotherapy patients, and low-birth-weight newborns. The death rate for systemic Candida illnesses ranges from 29 to 76 percent. Only a few medications are available to treat them, such as amphotericin B, fluconazole, terbinafine, and caspofungin, which have adverse reactions and are harmful. Objective: The goal of this research is to apply specialized bioinformatics approaches, such as molecular docking, scaffold hopping, virtual screening, pharmacophore modeling, and molecular dynamics (MD) simulation, to discover possibly novel and potent therapeutic drug candidates against Candida albicans in a shorter period and at a low cost. Methods: MDPI, MayBridge, Hitfinder, Mcule library, SQLite Database, DrugBank, ZINC, and NCI database were used to perform pharmacophore modeling, scaffold hopping, virtual screening, docking, and ADMET characteristics study against NMT. The molecular dynamics simulations for the best ten docked protein-ligand complexes were examined to determine the stability of protein-ligand interactions during a 200 ns simulation period, demonstrating their potential for lead molecule production via more improvement and experimental verification. Results: We have identified that compounds DB01940 ((3R,4R)-3-(4-hydroxybenzamido)azepan-4-yl 4- (2-hydroxybenzoyl)benzoate), DB01772 (3-(3-{[(2S)-2,3-dihydroxypropyl]amino}phenyl)-4-(5-fluoro-1- methyl-1H-indol-3-yl)-2,5-dihydro-1H-pyrrole-2,5-dione), and NCI5485 (1,3-bis((7-chloro-4- quinolinyl)amino)-2-propanol) could be more promising Candida albicans NMT inhibitors. Conclusion: In conclusion, these compounds have the potential to be effective anti-NMT medicines. The results demonstrated that our computational technique found some potential and effective NMT inhibitors that may be tested in clinical trials.

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