Speaker
Description
Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of healthcare-associated infections with limited treatment options due to multidrug resistance. Medicinal plants Artemisia annua and Aloe barbadensis have demonstrated antibacterial activity, but the specific bioactive compounds and their molecular targets remain largely unknown. This study employed molecular docking to screen 61 drug-like phytochemicals (33 from A. annua, 28 from A. barbadensis) against eleven MRSA protein targets involved in cell-wall synthesis (PBP2a, MurA, MurB, FemA/FemB, LtaS), DNA replication (DNA gyrase, topoisomerase IV), folate metabolism (DHFR, DHPS), virulence (sortase A), and stress response (ClpP). AutoDock Vina was used to calculate binding affinities, and Lipinski’s Rule of Five was applied to assess drug-likeness. Twenty-eight compounds showed binding affinities ≤ −7.0 kcal/mol against at least one target. Aloesaponarin I (from A. barbadensis) exhibited the strongest interaction with MurB (−10.5 kcal/mol). Other high-affinity compounds included 7-O-methylaloesin (MurA, −9.4 kcal/mol; LtaS, −8.8 kcal/mol), aloesaponol I (DHFR, −9.3 kcal/mol), and luteolin (sortase A, −7.7 kcal/mol; DNA gyrase, −7.7 kcal/mol). MurA was the most frequently inhibited target (23 compounds with ΔG ≤ −8.0 kcal/mol). All active compounds satisfied Lipinski’s criteria, indicating favorable oral bioavailability. These findings identify aloesaponarin I, 7-O-methylaloesin, luteolin, and kaempferol as promising multi-target MRSA inhibitors, warranting further in vitro and in vivo validation. The study recommends that future work should focus on determination of MIC and MBC for the top compounds (aloesaponarin I, 7-O-methylaloesin, luteolin, kaempferol) against MRSA clinical isolates as well as molecular dynamics simulations of the best complexes together with related synergies.
| Corresponding Author's Email | loicewechuli@gmail.com |
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| Keywords | Aloe barbadensis, Artemisia annua, Drug-Likeness, Molecular Docking, MRSA, Multi-Target, MurA |