Identification of two terpenoids from Withania coagulans with predicted multitarget binding affinity: An in vitro and in silico study
Abstract
Withania coagulans (Dunal) Stocks, a medicinal plant of the Solanaceae family, has long been recognized in traditional medicine for its antidiabetic, antimicrobial, and antioxidant activities. In the present study, gas chromatography-mass spectrometry (GC-MS) analysis of the aqueous stem extract of W. coagulans revealed a diverse phytochemical profile, comprising phenolics, terpenoids, and fatty acids. The extract was subsequently assessed for its biological potential using in vitro assays. It exhibited notable antibacterial activity against Salmonella Typhi and Escherichia coli, producing inhibition zones between 15 and 25 mm, comparable to that of standard antibiotics, underscoring its potential as a natural antibacterial agent. The antidiabetic potential of the extract was established by starch hydrolysis and α-amylase inhibition, where the extract achieved 58.33% and 75.8% inhibition, respectively. Antioxidant activity was demonstrated in the DPPH assay, showing a progressive increase in radical scavenging from 27.5% at 100 µg/mL to 57.3% at 500 µg/mL concentration. In silico docking, ADMET analysis, and molecular dynamics simulations identified caryophyllene oxide and 2,2-dimethyl-3-(…)-oxirane as promising lead terpenoids, exhibiting strong predicted binding affinities across antibacterial, antidiabetic, and antioxidant targets. These findings provide scientific support for the ethnopharmacological use of W. coagulans and suggest its potential compounds with predicted…
Read the paper
Related studies
- Quantum dots: synthesis, bioapplications, and toxicity
- A Guide to In Silico Drug Design
- Quantum Computing for Healthcare: A Review
- Automated in Silico Design of Homogeneous Catalysts
- Identification of Novel 3-Hydroxy-pyran-4-One Derivatives as Potent HIV-1 Integrase Inhibitors Using in silico Structure-Based Combinatorial Library Design Approach
- In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.