Diabetes type 2 is a common disease with clinical symptoms of abnormal insulin secretion. One of the pathways involved in the pathogenic mechanism of Type 2 Diabetes Mellitus (T2DM) is NF-κB pathway. The walnuts contain natural compounds such as gallic acid, ellagic acid, urolithin A, urolithin B, and it is potential to be antioxidants and anti-inflammatory. In this research, we focus on the comparative study of 4 compounds as an inhibitor of NF-κB complex by molecular docking interactions between NF-κB and these ligands as anti-T2DM compounds. The method is preparation of NF-κB protein using Discovery Studio 4.1, preparation of ligand: gallic acid, ellagic acid, urolithin, and urolithin B using Pyrx software. After that, molecular docking of protein-ligand was conducted by using Hex 8.0.0 software, then visualized with Discovery Studio 2019 and then analyzed the bioactivity of the compound through Mollinspiration web, respectively. The result of Mollinspiration shows that 4 compounds have good quality as a drug based on the lipinski 5 rules. The docking results show that four compounds can actively bind to the active site of NF-κB with the different bond energies. Ellagic acid is the most stable compound and the highest activity to inhibit the NF-κB pathway because it has highest binding energy than the other (-228,9 kcal/mol). Ellagic acid is an active polyphenol compound that is good to use as an antidepressant. Based on these comparative studies, ellagic acid has the best potential among the three other compounds in inhibiting NF-κB activity. In addition, all compounds can effectively inhibit the activation and translocation of NF-kB from the cytoplasm to the nucleus so the NF-κB is unable to regulate DNA sequences that encode proinflammatory proteins and then be able to reduce the pathophysiological effects of type 2 diabetes mellitus.
CITATION STYLE
Hikmaranti, M., M. Astiyani, A., … M. Maghfiroh, N. (2020). A Comparative Study of Gallic Acid, Ellagic Acid, Urolithin A, and Urolithin B with NF-κB Protein as Anti Type 2 Diabetes Mellitus by In Silico. JSMARTech, 1(2), 31–35. https://doi.org/10.21776/ub.jsmartech.2020.001.02.2
Mendeley helps you to discover research relevant for your work.