Design, graph theoretical analysis and in silico modeling of Dunaliella bardawil biomass encapsulated keratin nanoparticles: a scaffold for effective glucose utilization
Abstract
The aim of the present study is to develop keratin nanoparticles (NPs) encapsulated in Dunaliella bardawil (D. bardawil) biomass, in order to improve their glucose uptake in 3T3-L1 adipocytes. The graph theoretical approach has provided a platform to identify PTP-1B and AMPK as an effective drug target. Docking results of the active constituents of D. bardawil showed a strong interaction with binding pockets of identified PTP-1B and AMPK. The encapsulation efficiency, drug release, stability and physicochemical properties of prepared NPs were analyzed using UV-visible spectrophotometry, Fourier transform infrared spectrophotometry, x-ray diffraction, scanning and tunneling electron microscopy, and Zeta size analysis. Further, encapsulated keratin NPs were screened for their in vitro cytotoxicity and glucose uptake studies. The study report of biomass encapsulated keratin NPs showed no toxicity at lower concentrations and 81.23 ± 6.56% cellular viability at 30 μg in 3T3-L1 adipocytes. Moreover, the effect of keratin NPs (30 μg) on glucose utilization (58.56 ± 4.54%) was higher than that of Metformin (10 μM) or insulin (10 μM). The observed higher level of glucose utilization may lead to the development of novel ways to enhance biological activities.
Read the paper
Related studies
- Metformin as an adjuvant in breast cancer treatment
- Metformin Lysosomal Targeting: A Novel Aspect to Be Investigated for Metformin Repurposing in Neurodegenerative Diseases?
- Aberrant HSF1 signaling activation underlies metformin amelioration of myocardial infarction in mice
- Metformin induces ZFP36 by mTORC1 inhibition in cervical cancer-derived cell lines
- Protein Interaction Network for Identifying Vascular Response of Metformin (Oral Antidiabetic)
- Preventing Long COVID With Metformin
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.