PREDIKSI INTERAKSI METABOLIT SEKUNDER SENYAWA TANAMAN SINGAWALANG (Petiveria alliace) PADA ENZIM SGLT2 MENGGUNAKAN MOLECULAR DOCKING

Background : In 2019, the number of people with diabetes mellitus (DM) worldwide reached 463 million individuals aged 20–79 years, accounting for approximately 9.3% of the total population. Effective management and prevention are necessary to reduce the number of DM cases in Indonesia (Khadafi et al., 2022). One of the treatments for diabetes is derived from traditional medicinal plants. Due to their lower cost and minimal side effects, these plants are commonly used by the community as an alternative treatment for DM.
Research Objective : This study aims to predict the secondary metabolite compounds of Singawalang as a diabetes mellitus (DM) drug that targets the SGLT2 protein.
Research Method : To predict the interaction of Singawalang (Petiveria alliacea), a quantitative approach was employed using molecular docking. Compounds were retrieved from the PUBCHEM and PDB webservers, then processed using the Autodock Pyrx version 0.8 application to analyze molecular binding. The interaction results were subsequently visualized in both 2D and 3D formats using the Protein.plus webserver.
Results and Conclusion : The results indicate that among the 15 compounds classified as secondary metabolite compounds, only one compound closely resembles the internal ligand through amino acid bonds, energy binding values, and its pKi. The docking results of leridal chalcone were not superior to the internal ligand and ligand Empagliflozin. However, this one compound shows potential to be predicted as an antidiabetic drug.