Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment
Safwat, Sally; Hathout, Rania M; Aziz Ishak, Rania; Mortada, Nahed D.;
Abstract
This study focuses on the preparation and optimization of caffeic acid (CA)-loaded casein nanoparticles (CS NPs) via the Box–Behnken design (BBD) for potential applications in cancer treatment. CS NPs were loaded with CA as a promising anti-cancer molecule. Non-hazardous green materials were exploited for nanoparticle fabrication. The BBD was used, followed by a desirability function to select the optimum formulation. The BBD was adopted as it avoids the runs implemented in extreme conditions, hence making it suitable for proteins. CS NPs were characterized regarding particle size (PS), size distribution (PDI), zeta potential (ZP), drug entrapment, morphology using TEM, differential scanning calorimetry, molecular docking, in vitro release, and cytotoxicity studies. PS, PDI, and ZP had significant responses, while EE% was insignificant. The suggested models were quadratic with high fitting. Optimized NPs showed PS = 110.31 ± 1.02 nm, PDI = 0.331 ± 0.029, ZP = −23.94 ± 1.64 mV, and EE% = 95.4 ± 2.56%. Molecular modeling indicated hydrophobic and electrostatic interactions between CA and CS, accounting for the high EE%. Almost spherical particles were realized with a sustained CA release pattern. Optimized NPs effectively suppressed the growth of MCF-7 cell lines by scoring the lowest IC50 = 78.45 ± 1.7 µg/mL. A novel combination of bioinspired-derived materials was developed for use in breast cancer treatment.
Other data
| Title | Back to Nature: Development and Optimization of Bioinspired Nanocarriers for Potential Breast Cancer Treatment | Authors | Safwat, Sally; Hathout, Rania M ; Aziz Ishak, Rania ; Mortada, Nahed D. | Keywords | Box–Behnken design | caffeic acid | casein | nanoparticles | optimization | Issue Date | 1-Jan-2024 | Journal | Scientia Pharmaceutica | ISSN | 00368709 | DOI | 10.3390/scipharm92030050 | Scopus ID | 2-s2.0-85205109537 |
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