Abstract

Objectives: Malaria remains a major global health burden, particularly in endemic regions such as Djibouti, where Plasmodium falciparum and Plasmodium vivax co-circulate, complicating disease control strategies. Increasing resistance to current antimalarial drugs reduces treatment effectiveness and highlights the urgent need for new, safe, and affordable therapeutic agents. This study aimed to identify potential inhibitors from Djiboutian medicinal plants using an integrated in silico approach targeting key proteins from both parasite species. Methods: A library of 222 phytoconstituents was screened against Plasmodium vivax FK506-binding protein 35 (PDB ID: 3IHZ) and Plasmodium vivax dihydrofolate reductase–thymidylate synthase (PDB ID: 1J3K) using molecular docking. Top-ranked compounds were further analyzed for binding interactions and evaluated for drug-likeness and pharmacokinetic properties using QikProp in Maestro v11.5. Selected protein–ligand complexes were subjected to 100 ns molecular dynamics simulations, and their stability was assessed using multiple descriptors, including structural deviation, flexibility, compactness, solvent exposure, and hydrogen bond persistence. Results: Several phytoconstituents exhibited strong binding affinities, with docking scores ranging from −6.09 to −7.54 kcal/mol, outperforming the reference drug artemisinin. Interaction analysis revealed key hydrogen bonds and hydrophobic contacts with essential active-site residues. ADMET predictions indicated favorable pharmacokinetic profiles, including high oral absorption, good membrane permeability, and low predicted toxicity. Molecular dynamics simulations demonstrated stable behavior for most complexes, with compound 121 showing enhanced stability in the 1J3K system and compound 123 exhibiting consistent dynamic stability in the 3IHZ system. In contrast, compound 82 displayed greater structural fluctuations despite maintaining stable hydrogen bond interactions. Conclusions: The integration of molecular docking, ADMET prediction, and molecular dynamics simulations identified compounds 121 and 123 as the most promising antimalarial candidates, exhibiting an optimal balance of binding affinity, favorable pharmacokinetic properties, and dynamic stability. These findings highlight the potential of Djiboutian medicinal plants as a valuable source of novel antimalarial agents and provide a strong computational foundation for future experimental validation.

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