Antibacterial Activity, Toxicity and Drug-Likeness Profiles of Woodfordia fruticosa-Derived Metabolites Using Computational-Aided Drug Design Platform

This study presents a comprehensive investigation into the phytoconstituents reported from Woodfordia fruticosa (L.) Kurz leaf and flower extracts using gas chromatography-mass spectrometry (GC-MS) analysis, along with some existing phytochemicals, to explore their potential antibacterial properties through molecular docking studies. Followed by bio-assay-guided leave and flower extraction with two solvent systems, i.e., methanol (polar) and petroleum ether (non-polar), was used and further subjected to GC-MS to identify and quantify various secondary metabolites. Based on spectral intensity and volume area, a total of 28 compounds (P1 to P28) have been selected from GC-MS analyses, and an additional 14 compounds (P29 to P42) from previous reports were selected for molecular docking studies against DNA gyrase subunit B (GryB) of Escherichia coli (PDB ID: 7P2M) and Staphylococcus aureus (PDB ID: 5D7R) with novobiocin as the standard. Further, docking score or binding affinity (kcal/mol.) of each ligand were investigated, where the 4,5-dihydro-4,4-undeca methylene-2-phenyl-1,3-oxazin-6-one (P20) with a docking score of -8.4 kcal/mol., from the GC-MS-derived group and the chrysophanol-8-O-?-d-glucopyranoside (P37) with a docking score of -9.7 kcal/mol., from existing phytochemical groups were reported as potential antibacterial. The predicted toxicity and drug-ability profiles also suggested that GC-MS-derived candidates displayed comparatively higher non-toxic profiles but lower drug-likeness profiles than existing groups. This integrative approach explores the phytochemical profiles of W. fruticosa responsible for antibacterial activity of the crude extracts and providing insights into in selection of lead antibacterial agent through cost-effective computer-aided drug design platform to accelerate antibacterial drug discovery with higher chance of experimental success.

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Publication Details

Journal
International Journal of experimental research and review
Published
2024-08-30
DOI
https://doi.org/10.52756/ijerr.2024.v42.022
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.72
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article

Antibacterial Activity, Toxicity and Drug-Likeness Profiles of Woodfordia fruticosa-Derived Metabolites Using Computational-Aided Drug Design Platform

S. Acharya, Shasank S. Swain, Gyanranjan Mahalik, Babu Ram et al.
2 citations
International Journal of experimental research and review
Computational Drug Discovery Methods
0.72
article

Antibacterial Activity, Toxicity and Drug-Likeness Profiles of Woodfordia fruticosa-Derived Metabolites Using Computational-Aided Drug Design Platform

S. Acharya, Shasank S. Swain, Gyanranjan Mahalik, Babu Ram, D. P. SAHU
article en
2 citations

Abstract

This study presents a comprehensive investigation into the phytoconstituents reported from Woodfordia fruticosa (L.) Kurz leaf and flower extracts using gas chromatography-mass spectrometry (GC-MS) analysis, along with some existing phytochemicals, to explore their potential antibacterial properties through molecular docking studies. Followed by bio-assay-guided leave and flower extraction with two solvent systems, i.e., methanol (polar) and petroleum ether (non-polar), was used and further subjected to GC-MS to identify and quantify various secondary metabolites. Based on spectral intensity and volume area, a total of 28 compounds (P1 to P28) have been selected from GC-MS analyses, and an additional 14 compounds (P29 to P42) from previous reports were selected for molecular docking studies against DNA gyrase subunit B (GryB) of Escherichia coli (PDB ID: 7P2M) and Staphylococcus aureus (PDB ID: 5D7R) with novobiocin as the standard. Further, docking score or binding affinity (kcal/mol.) of each ligand were investigated, where the 4,5-dihydro-4,4-undeca methylene-2-phenyl-1,3-oxazin-6-one (P20) with a docking score of -8.4 kcal/mol., from the GC-MS-derived group and the chrysophanol-8-O-?-d-glucopyranoside (P37) with a docking score of -9.7 kcal/mol., from existing phytochemical groups were reported as potential antibacterial. The predicted toxicity and drug-ability profiles also suggested that GC-MS-derived candidates displayed comparatively higher non-toxic profiles but lower drug-likeness profiles than existing groups. This integrative approach explores the phytochemical profiles of W. fruticosa responsible for antibacterial activity of the crude extracts and providing insights into in selection of lead antibacterial agent through cost-effective computer-aided drug design platform to accelerate antibacterial drug discovery with higher chance of experimental success.

International Journal of experimental research and reviewVol. 42
University of Delhi (IN), Centurion University of Technology and Management (IN)
Openalex Percentile: Top 26%
Computational Drug Discovery Methods
0.72
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