Computational molecular docking and simulation-based prediction of natural compounds from nyctanthes arbor-tristis as potential antifungal agents
Abstract
Mycoses, or fungal illnesses, are common health problems that frequently impact crops, animals, and food. Molecular docking and dynamics simulation techniques were used to predict the multitargeted antifungal potential of phytochemicals from Nyctanthes arbor-tristis against multiple drug targets of fungi. We analyzed the binding interaction and dynamics of phytochemicals of the Nyctanthes arbor-tristis plant with multiple drug targets of fungi through a computational study. The strong binding affinities with the targets studied of fungi were found to be more significant compared to the reference drug (lupeol -11.5 kcal/mol; DB01263, a synthetic azole drug -8.7 kcal/mol). The investigated ligands, Lupeol, Nyctanthic acid, Beta-amyrin, and Apigenin, interacted more significantly with fungal drug targets through hydrogen bonds and hydrophobic interactions. The structural assessment of the 5FSA-ligand complexes showed stability with root mean square deviation (RMSD) values between 0.2 and 0.4nm, also investigated through 500 ns molecular dynamics simulations, which considered different geometric properties and computed the binding free energy. We also observed significant ligand-receptor interactions and high drug-likeness properties for the observed molecules using the pkCSM absorption, distribution, metabolism, and excretion ( ADMET) method. This study suggested the screened phytochemicals of this plant, namely Lupeol, Nyctanthic acid, Beta-amyrin, and Apigenin, or their combination, could inhibit fungal pathogens and could be beneficial to control the fungal-mediated food spoilage and aspergillosis in both plants and animals. Nevertheless, more in vitro and in vivo research is required to validate these findings.
Fields of Study & Subjects
Phytochemistry and Biological Activities
Computational Drug Discovery Methods
Phytochemistry and Bioactive Compounds
Publication details
- Journal / source
- Journal of King Saud University - Science
- Publisher
- Scientific Scholar
- Volume
- 38
- Pages
- 16672025–16672025
- Publication date
- 4 April 2026
- Language
- EN