Machine learning modeling and response surface methodology driven antioxidant and anticancer activities of chitosan nanoparticle-mediated extracts of Bacopa monnieri.

Journal: International journal of biological macromolecules
Published Date:

Abstract

This study investigates the potential of chitosan nanoparticles (CNPs) in enhancing the bioavailability and efficacy of Bacopa monnieri extracts, known for their neuroprotective, antioxidant, and anticancer properties. Different concentrations of CNPs were added to the culture medium for in vitro shoot regeneration. Antioxidant activity (DPPH free radical scavenging and HO removal assays) and cytotoxicity assay (LDH release and XTT viability) were performed. The results demonstrated the highest DPPH radical scavenging activity of 95.60 % at 125 μg/mL CNPs from methanol extract. Whereas, HO scavenging activity increased with higher extract concentrations, and the maximum was recorded from methanol extract when used at 1000 μg/mL. Cytotoxicity assays revealed a dose-dependent increase in LDH activity and XTT reduction, and water-based extracts demonstrated the strongest cytotoxic effects. IC analysis indicated that CNP-enriched methanol and water extracts were significantly more cytotoxic to HeLa cells as compared to ethanol extracts. Response surface regression analysis and ML models confirmed the reliability of the experimental data, with the multilayer perceptron (MLP) model exhibiting the best predictive accuracy, followed by the random forest (RF) model. It can be concluded that CNP enrichment significantly improved the antioxidant and anticancer properties of B. monnieri extracts, highlighting the potential of CNP-based formulations for future studies.

Authors

  • Seyma Bulut
    Department of Biotechnology, Faculty of Science, Necmettin Erbakan University, 42090 Konya, Turkey.
  • Muhammad Aasim
    Department of Plant Protection, Faculty of Agricultural Sciences and Technology, Sivas University of Science and Technology, 58000 Sivas, Turkey. Electronic address: mshazim@gmail.com.
  • Bugrahan Emsen
    Department of Biology, Kamil Ozdag Faculty of Science, Karamanoglu Mehmetbey University, 70200 Karaman, Turkey.
  • Seyid Amjad Ali
    Department of Information Systems and Technologies, Bilkent University, 06800 Ankara, Turkey.
  • Hakan Askin
    Department of Molecular Biology and Genetics, Faculty of Science, Ataturk University, 25240 Erzurum, Turkey.
  • Mehmet Karatas
    Department of Biotechnology, Faculty of Science, Necmettin Erbakan University, 42090 Konya, Turkey.