ArticleArchives of microbiology2026
Computational prediction and docking studies of bioactive metabolites from grass-derived endophytic fungi.
Article in Archives of microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Endophytic fungi are prolific sources of structurally diverse secondary metabolites with significant agricultural and pharmacological potential. In the present study, bioactive compounds isolated from endophytic fungi (Curvularia tsudae (Ct), Aspergillus chevalieri (ARI 27), Aspergillus stellates (ARI 22), and Hypoxylon sp. (ARI 06) harbored in Cynodon dactylon were analyzed using GC-MS/LC-MS and subjected to computational prediction and molecular docking studies. A total of 26 major metabolites, including phenolics, lactones, alkaloids, coumarins, anthraquinones, and fatty acids, were characterized and evaluated for their drug-likeness, biological activity scores, and binding affinities using chemoinformatic and docking tools. Most compounds adhered to Lipinski's Rule of Five, with favorable logP values and topological polar surface areas indicating good bioavailability. Notably, curvularin, dextramycin, esculetin, and 1,4-dibutyl benzene-1,4-dicarboxylate showed strong docking affinities (- 6.6 to - 9.1 kcal/mol) toward antibacterial and antioxidant targets such as D-alanine-D-alanine ligase, lipoxygenase, 1-heptacosanol and myeloperoxidase. Molecular dynamics simulation was confirmed by normal mode analysis, in which the interactions of the top three protein-ligand pairs were found to be stable, with low eigenvalues of 5.4 × 10
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