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All Journal JSMARTech : Journal of Smart Bioprospecting and Technology
Izzatur Rochmah, Evalina
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Biochemistry, Genetics & Molecular Biology Chemistry Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience

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In Silico Approach of Predicting The Interaction of Epigallocatechin-3 Gallate and Chlorogenic Acid on E47 and THOC5 in Macrophage Differentiation: In Silico Study of EGCG and CGA on Macrophage Differentiation Rohman, Mohammad Saifur; Izzatur Rochmah, Evalina; Abdullah, Fuad; Alvianoes Guterez Hose, Victor
JSMARTech: Journal of Smart Bioprospecting and Technology Vol. 7 No. 1 (2026): Vol. 7 No. 1 (2026): JSMARTech Volume 7, No 1, 2026
Publisher : JSMARTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jsmartech.2026.007.01.24

Abstract

Diabetes mellitus is a metabolic disease characterized by chronic hyperglycemia and glucose intolerance. Vascular hyperglycemia triggers the release of inflammatory mediators, which can increase monocyte differentiation into macrophages. Compounds such as epigallocatechin-3 gallate (EGCG) from green tea and chlorogenic acid (CGA) from green coffee are known to have anti-inflammatory effects. This study aimed to analyze the effect of EGCG and CGA on macrophage differentiation markers by assessing their binding activity with THOC5 and E47 proteins. An in silico assessment was conducted using metformin, which is widely used as a first-line antidiabetic drug, as the control ligand. Pharmacokinetic and drug-likeliness predictions were carried out. Additionally, molecular docking and molecular dynamics analysis were performed on the active residues of the proteins to assess the binding affinity and complex stability. The results obtained demonstrate that the binding affinity energy of EGCG and CGA to THOC5 and E47 was more favorable than that of metformin, yet their bioavailability value was poor. Molecular dynamics simulation showed that EGCG had a more stable complex compared to CGA and metformin. In conclusion, EGCG and CGA could potentially be effective as anti-inflammatory agents in diabetes mellitus.
Co-Authors Abdullah, Fuad Alvianoes Guterez Hose, Victor Mohammad Saifur Rohman