Abstract

The rapid emergence of multidrug-resistant microbial pathogens has created an urgent need for new antimicrobial agents. Marine organisms are a rich source of structurally diverse bioactive metabolites with therapeutic potential, and the sea cucumber H. scabra contains numerous secondary metabolites that may exhibit favorable predicted interactions with antimicrobial targets. This study aimed to identify potential antimicrobial metabolites from H. scabra using an integrated computational approach. Metabolites were identified by gas chromatography–mass spectrometry (GC–MS) and screened against selected bacterial and fungal target proteins using molecular docking. The top-ranked compounds were further evaluated for pharmacokinetic properties through ADME prediction, while the stability of the protein–ligand complexes was assessed using 100 ns molecular dynamics simulations and MM/GBSA binding free energy calculations. GC–MS analysis tentatively identified sixteen metabolites, among which CID 21820889 and CID 304 exhibited favorable predicted binding interactions with target proteins from Acinetobacter baumannii and Candida albicans, respectively. These compounds also demonstrated acceptable predicted pharmacokinetic properties, stable protein–ligand interactions throughout the simulations, and favorable MM/GBSA binding free energies, supporting the stability of the predicted complexes. Overall, MM/GBSA binding free energies ranged from −35.46 to −47.17 kcal/mol, with CID 441130 exhibiting the most favorable overall binding energy (−47.17 kcal/mol), while CID 21820889 also showed a favorable binding free energy (−44.85 kcal/mol). These findings identify several putatively identified, computationally prioritized metabolites from H. scabra as candidates for further investigation and demonstrate the utility of integrating chemical profiling with computational approaches for the early stage screening of marine natural products.

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