Current Enzyme Inhibition - Volume 21, Issue 2, 2025

Reactive oxygen species (ROS)-mediated oxidative damage in arsenic pathogenesis disrupts redox balance, impairs free radical neutralization, and affects bacterial metabolism, leading to cell death. This study investigated the antibacterial activity and antioxidant system augmentation of Jatropha curcas aqueous leaf extract (JCALE) in-silico, and on arsenic-induced oxidative-stressed D. melanogaster.

The bioactive components of JCALE obtained from the gas chromatography-mass spectroscopy (GCMS) technique were used for molecular docking in PyRx and Biovia Discovery Studio 2021. Sodium-arsenite (SA) toxicity (0.0625 mM) was induced in D. melanogaster and treated with JCALE (0.4 and 0.8 g/10g diet) for 7 days. Thereafter, the ameliorative role of JCALE in SA-induced toxicity was evaluated using oxidative stress (hydrogen peroxide and lipid peroxidation), antioxidant (catalase and glutathione-s-transferase), and hepatic enzymes (alanine and aspartate transaminases) biomarkers, and the antibacterial activity by agar diffusion method.

The results of this study showed potent inhibition of Proteus mirabilis (20 mm), Salmonella typhi (20 mm), Pseudomonas aeruginosa (19 mm), and Escherichia coli (16 mm) by JCALE. However, Staphylococcus aureus showed resistance. Treatment of the arsenic induced flies with the concentrations of JCALE significantly increased (p<0.05) catalase and glutathione-s-transferase activities but reduced (p<0.05) both alanine and aspartate transaminases activities and the levels of hydrogen peroxide generation and lipid peroxidation. Additionally, out of the seven drugs predicted in this study, decane-3,7-dimethyl- showed the best binding energy with the selected target proteins.

The results indicate that the extract significantly improved key biochemical parameters, suggesting its potential therapeutic effect. These findings support its biological activity, though further studies are needed to confirm its mechanisms and long-term safety.

In conclusion, JCALE showed antibacterial activity, prevented oxidative stress, and augmented the antioxidant system of D. melanogaster, possibly due to its richly embedded secondary metabolites.

Breast cancer is a leading cause of death among women worldwide. The limitations of current therapies, drug resistance, and toxicity emphasize the urgent need for targeted therapeutic agents. The 4H-chromen-4-one scaffold has emerged as a promising framework for developing potent anticancer agents, particularly against MCF-7 breast cancer cells. This study investigates the anticancer potential of 4H-chromen-4-one derivatives against the MCF-7 breast cancer cell line using computational modelling.

QSAR models were constructed using PaDEL molecular descriptors using conventional QSARINS software and state-of-the-art machine learning techniques.

The QSAR model through QSARINS demonstrated strong predictive performance with a leave-one-out cross-validated R² (Q²loo) value of 0.7790 (internal validation) and a squared correlation coefficient of the test set (R²ext) value of 0.5049 (external validation). Whereas, machine learning models yielded R² values of 0.6614, 0.9404, 0.9093, 0.9093, and 0.714 for random forest, support vector regression, multiple linear regressions, partial least squares, and ordinary least squares, respectively.

Key molecular descriptors contributing significantly to the model included MATS2e (electronic descriptor), SCH-5 (topological descriptor), and minaasC (electronic descriptor), indicating their importance in breast cancer activity. The predicted pIC50 values for the 4H-chromen-4-one derivatives from QSARINS and machine learning techniques fit well within the chemical space, further validating the models.

This study highlights the potential of 4H-chromen-4-one derivatives as leads for anticancer drug development. The identified electronic descriptors are essential for their activity and can guide structural optimization. Further in vitro and in vivo studies are warranted to validate their therapeutic potential.

Effective inhibition of pathogenic bacterial urease activity aligned with satisfied dissolution of struvite stone by purified flavonoid moieties can overcome several life-threatening renal disorders. The objective of this study was to investigate the in vitro inhibition of urease enzyme and an effective control over the formation of infectious renal stone (Struvite stone) by the extract and purified flavonoid of Citrus limon seeds.

Standard spectrophotometry analysis to determine urease activity, Gel diffusion method for in vitro antibacterial activity, Artificial Neural Network (ANN) to validate the urease inhibitory activity, and LC-MS-PDA analysis to predict the structures of polyphenols were employed.

Complete urease inhibition was noticed in hot water extract (HWE) and 50% ethanolic extract, and an appreciable inhibition was recorded by preparative thin layer chromatography (PTLC) purified polyphenols (78.3±2.6%). A satisfactory struvite stone dissolution of about 49.6±3.2% and 40.9±2.1%, was recorded by HWE and PTLC eluate, respectively. ANN-based training model proved a significant correlation (r² = 0.987) between the predicted and conducted experimental results of urease inhibitory activity. Two new novel polyphenols were identified (luteolin-7-0-rutinoside glycoside derivative [m/z 786] and an unknown compound [m/z 651]) through LC-MS-PDA analysis. Likewise, simulated bioimplant coated with purified polyphenols recorded a satisfactory urease inhibitory activity.

Significant inhibition of urease activity aligned with satisfied dissolution of struvite stone was probably due to the presence of appreciable quantum of polyphenolic entities.

A correlated result of urease inhibition, growth inhibition against clinically significant bacterial pathogens, and in vitro struvite stone dissolution strongly support the efficacy of renoprotective effect of C. limon seeds.