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Integrated in vivo and in silico evaluation of antimalarial compounds from Vernonia ambigua leaves identified by GC-MS profiling

Article scientifique 2025 Anglais

Résumé

Background Malaria remains a global health challenge, and the emergence of drug-resistant Plasmodium strains has necessitated the search for new antimalarial agents. Vernonia ambigua is used traditionally to treat malaria in parts of Africa, but its pharmacological potential remains underexplored. The aim of this study was to evaluate the antimalarial activity and chemical constituents of the chloroform leaf extract (CLE) of V. ambigua using in vivo and in silico approaches. Methods Acute toxicity was evaluated using Lorke’s method, and antimalarial activity was assessed via Ryley and Peter’s 4-day curative test in Plasmodium berghei –infected Swiss albino mice, followed by GC–MS profiling and in silico analyses (molecular docking and dynamics simulations) of the identified compounds. Results The CLE showed a 73.8% parasite cure rate at 500 mg/kg, with no observed toxicity up to 5,000 mg/kg. GC-MS profiling revealed thirteen compounds, of which 9H-fluorene-4-carboxylic acid and Tolnaftate showed strong Pf LDH binding (docking scores of −7.7 and −7.6 kcal/mol, respectively). Tolnaftate demonstrated potentially modest stability in the active site of Pf LDH during MD simulation. ADME/toxicity profiling identified 9H-fluorene-4-carboxylic acid as the most promising compound, combining favorable bioavailability, low predicted toxicity, and good synthetic accessibility. Conclusion V. ambigua possesses potent antimalarial properties, with 9H-fluorene-4-carboxylic acid and Tolnaftate emerging as promising Pf LDH inhibitors. These findings support further investigation and development of its bioactive constituents as antimalarial drug leads.

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Yusuf, A., Alpha, A., Salihu, M., Aminu, J., Şahin, N., Yelekçi, K., Uba, A., Imam, M. (2025). Integrated in vivo and in silico evaluation of antimalarial compounds from Vernonia ambigua leaves identified by GC-MS profiling. https://doi.org/10.3389/fddsv.2025.1635697

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