Biological Activities of Withanolides from Datura innoxia

Abstract

Aims: This study aimed to explore the therapeutic potential of Datura innoxia through the chemoinformatic and antibacterial evaluation of withanolides extracted from it. Study Design: The pharmacokinetic and pharmacodynamic properties and drug-likeness of the withanolides—withametelinol A, withametelinol B, witharifeen, withametelin, dinoxin B, and daturalicin—of D. innoxia were analyzed using the SwissADME program. Schrodinger software was used to target and evaluate their antibacterial potentialities through docking studies. The penicillin-binding protein, DNA gyrase, efflux pump protein, and quorum sensing regulators of S. aureus and E. coli were selected as target proteins for assessing protein–ligand interactions. All observations were comparatively analyzed with the properties of withanolide A and withaferin A, the best-known withanolides. Most active dinoxin B withanolide (12500–100000 μg/ml) extracted from leaves of Datura innoxia; was subjected to antibacterial assay against methicillin-resistant S. aureus (MRSA) and multi-drug resistant(MDR) E. coli isolated from the urine samples of urinary tract infected patients. Results: In-silico studies revealed the therapeutical properties of various withanolides present in D. innoxia. In particular, the drug-likeness and antibacterial properties of withametelin and dinoxin B were significantly and remarkably high due to their binding affinity toward cell membrane proteins. Docking studies have shown that the efflux pump protein of E. coli and penicillin-binding proteins of S. aureus to be the ligand -interaction targets. A significant antibacterial assay revealed that the MRSA isolates were susceptible to dinoxin B, with a zone of inhibition of 21±0.5 mm to 24±0.5 mm, and the bacteria were susceptible at a concentration rate of ≤ 12.5 mg/ml. Conclusion: It is crucial to bring awareness of the therapeutical importance of D. innoxia and to preserve this vital plant from being largely destroyed. As computational studies promote the effective selection of drug molecules, this research also helps to select the best compound for further clinical analysis.