GC-MS, Antibacterial and In silico Studies of Sudanese Acacia polyacantha Stem Bark Alcoholic Extract

Abubakr A Hammad; Abdelgadir A Abdelgadir; Sitelbanat Yassin; Abdulrahim A Alzain; Elhadi M Ahmed

doi:10.2147/JEP.S480839

GC-MS, Antibacterial and In silico Studies of Sudanese Acacia polyacantha Stem Bark Alcoholic Extract

J Exp Pharmacol. 2024 Oct 10:16:365-376. doi: 10.2147/JEP.S480839. eCollection 2024.

Authors

Abubakr A Hammad^{1

2}, Abdelgadir A Abdelgadir^{2

3}, Sitelbanat Yassin⁴, Abdulrahim A Alzain⁵, Elhadi M Ahmed^{2

3}

Affiliations

¹ Department of Pharmacognosy, Faculty of Pharmacy, Omdurman Islamic University, Omdurman, Sudan.
² Department of Pharmacognosy, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan.
³ Medicinal and Aromatic Plants Research Center, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan.
⁴ Department of Pharmaceutics, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan.
⁵ Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Gezira, Wad Madani, Sudan.

Abstract

Introduction: Antimicrobial resistance is a critical global issue, and medicinal plants, as a key source of therapeutic agents, offer potential solutions by offering new antibacterial agents. Acacia polyacantha tree, known as Al Kakamout in Sudan, is a significant source of Gum Arabic and has been traditionally used to treat bacterial diseases. This study aimed to investigate a hydro-ethanol extract of Kakamout stem bark through GC-MS analysis, evaluate its antibacterial activity against two standard bacterial strains, and conduct molecular docking and ADME studies.

Methods: The stem bark of the plant was extracted by maceration using a hydro-ethanol solvent and analyzed via GC-MS. The antibacterial activity of the extract was evaluated against Staphylococcus aureus ATCC 25923 and Pseudomonas aeruginosa ATCC 27853 using the well diffusion method. The identified compounds were studied in silico to investigate their binding affinities with the target bacterial proteins. The ADMET properties were predicted for the top scoring compounds.

Results: GC-MS analysis revealed the presence of 11 compounds, with the major ones being dopamine, N, N-dimethyl-, dimethyl ether (43.76%), 4-O-methylmannose (23.27%), sucrose (8.09%), 1,4,7-triazacyclononane, 1-benzoyl- (5.41%), and lupeol, trifluoroacetate (5.24%). The extract demonstrated significant effectiveness against both bacterial strains, even at a low concentration of 50 mg/mL. Molecular docking showed that compounds 1, 3, 4, and 6 had the best docking scores with enoyl-acyl carrier protein reductase (FabI) (PDB ID: 3GR6) from S. aureus (-6.142, -10.843, -6.218 and -7.14 Kcal/mol). Similarly, compounds 1-6 exhibited favorable binding energies with LasR-TP4 complex (PDB ID: 3JPU) from P. aeruginosa (-10.025, -9.127, -8.623, -7.092, -7.722, and -6.019 Kcal/mol).

Conclusion: This study provides the first GC-MS analysis of Acacia polyacantha stem bark, identifying potential antibacterial compounds. Molecular docking and ADMET predictions suggest several promising compounds for further investigation as antibacterial agents.

Keywords: ADME; Acacia polyacantha; GC-MS; antibacterial; molecular docking.