In-silico, in-vitro and in-vivo Biological Activities of Flavonoids for the Management of Type 2 Diabetes.
Jyoshna Rani DashBiswakanth KarGurudutta PattnaikPublished in: Current drug discovery technologies (2024)
In spite of the fact that many medicinal plants have been truly utilized for the management of diabetes all through the world, very few of them have been reported scientifically. Recently, a diverse variety of animal models have been established to better understand the pathophysiology of diabetes mellitus, and new medications to treat the condition have been introduced in the market. Flavonoids are naturally occurring substances that can be found in plants and various foods and may have health benefits in the treatment of neuropathic pain. Flavonoids have also been shown to have an anti-inflammatory impact that is significant to neuropathic pain, as indicated by a decrease in several pro-inflammatory mediators such TNF-, NF-B IL-6, and IL-1. Flavonoids appear to be a viable novel therapy option for macrovasular complications in preclinical models; however, human clinical data is still inadequate. Recently, several in silico, in-vitro and in-vivo aproaches were made to evaluate mechanisms associated with the pathogenesis of diabetes in a better way. Screening of natural antidiabetic agents from plant sources can be analysed by utilizing advanced in-vitro techniques and animal models. Natural compounds, mostly derived from plants, have been studied in diabetes models generated by chemical agents in the majority of research. The aim of this work was to review the available in silico, in-vitro and animal models of diabetes for screening of natural antidiabetic agents. This review contributes to the scientist's design of new methodologies for the development of novel therapeutic agents having potential antihyperglycemic activity.
Keyphrases
- neuropathic pain
- type diabetes
- glycemic control
- spinal cord
- cardiovascular disease
- spinal cord injury
- molecular docking
- drinking water
- healthcare
- anti inflammatory
- endothelial cells
- stem cells
- oxidative stress
- insulin resistance
- mental health
- skeletal muscle
- risk factors
- adipose tissue
- mesenchymal stem cells
- inflammatory response
- machine learning
- big data
- health information
- climate change
- metabolic syndrome
- induced pluripotent stem cells
- nuclear factor
- deep learning
- bone marrow
- toll like receptor
- health promotion