Green synthesis enhances antibacterial activity of nanocomposites in drug-resistant bacteria, suggesting new biomedical uses.
Green synthesis of antimicrobial nanocomposites (NCs) offers a promising strategy to combat drug-resistant bacteria, a growing global health threat. In this work, we report the first-time green synthesis of CuO/TiO 2 @Chitosan NCs using Matricaria chamomilla extract, uniquely combining phytochemicals and a natural biopolymer in a single-step biosynthesis. An anthrone assay confirms that CuO/TiO 2 NC stability is due to carbohydrates, while the interaction of NCs with chitosan causes increased carbohydrate content. The addition of chitosan to CuO/TiO 2 NC increased their antioxidant activity and antibacterial efficacy. CuO/TiO 2 @Cs NC showed excellent antibacterial activity against E. coli , S. typhimurium , B. cereus , S. aureus , and S. epidermidis bacteria, and the results were between 12.0 ± 1.27 mm and 19.0 ± 1.60 mm. The antibacterial findings, on the other hand, confirmed that M. chamomilla extract and CuO/TiO 2 NC were not effective in inhibiting the growth of the bacterial strains. In addition, a molecular docking study was conducted to assess the interaction among phytochemicals of M. chamomilla with bacterial targets. Compared to similar nanocomposites in the literature, the CuO/TiO 2 @Chitosan NCs developed here demonstrate enhanced dispersion stability, biofunctional surface chemistry, and selective antibacterial activity against Gram-positive and Gram-negative strains, positioning them as competitive candidates for biomedical applications. This paper reports for the first time green synthesis of CuO/TiO 2 @Chitosan NCs from M. chamomilla extract, wherein phytochemicals complement chitosan to enhance antibacterial efficacy against multidrug-resistant bacteria. Although M. chamomilla has been used in a few instances in research for metal nanoparticle synthesis and antioxidant studies, its use in a CuO/TiO 2 -chitosan hybrid is novel. This work offers a green protocol and provides a baseline for further optimization and in vivo studies towards biomedical applications.
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Abumelha et al. (2026) studied this question.
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