No abstract

Objective: Obesity is the major problem which may lead to many other health ailments such as atherosclerosis, stroke, and depression. Both the cause as well as the treatment lies in the adipose tissue. The two main adipocytes, white adipose tissue (WAT) and brown adipose tissue (BAT) are responsible for the accumulation of fat and transformation of fat into heat, respectively. This review discusses the induction of BAT and browning of WAT by different pathways and activators to decrease the rate of obesity.Methods: Understanding the regulators, activators and secreted proteins which induce browning of WAT to BAT, as the BAT engage in thermogenesis process and transform fat into heat rather than storing it (WAT). Some of the core regulators are peroxisome proliferator-activated receptor-γ, PRDM16, PGC-1α. Results:A basic study explained about the origin of BAT and its functions, the function of hormones in BAT growth and its regulations. These studies provided the platform to understand about the mechanism of regulators, activators and secreted proteins which help in treating obesity and its related disorders by inducing the amount of BAT. Conclusion:The major health ailments caused by obesity can be reduced by increasing the activity of BAT and transforming WAT into BAT. A challenging way to treat these ailments is by regulating the activators and hormones responsible for the induction of BAT, so it transforms the excess fat into heat and avoiding the accumulation of fat. By understanding the role of regulators in the adipose tissue can provide various methods to reduce the chance of obesity and enhance efficient treatment in both children and adults.

The main aim of this study is to determine the bioactive compounds which have drug-like properties and has the potential to combat the spike-glycoprotein of SARS-CoV-2. The 6LXT protein of covid-19 was chosen from the protein data bank as a target protein. The compounds which are potentially capable to bind with the target were picked from the PubChem database and docked using the tool Autodock 4.2. Molecular docking of the molecules was done with the best conformations of the ligands and grid size was selected according to the hit compounds' interaction with the target protein. The ligand binding sites with the target molecules were predicted using MetaPocket 2.0. The docking Score of 50 compounds wascarried out and also toxicity studies were carried out. The compounds selected were calculated to identify the best conformations having druglikeness properties. The top 10 compounds were chosen for the structure-activity relationship based on their binding interactions with the protein and ligand. The ligands then underwent the pharmacokinetic analysis followed by Lipinski's and all the results were finalized and categorized. ManzamineA, Imatinib, and basotinib were elected as the peak compounds with the binding energy -9.01kcal/mol, -8.71kcal/mol, and -8.01kcal/mol.