Hasil In Silico Senyawa Z12501572, Z00321025, SCB5631028 dan SCB13970547 dibandingkan Turunan Zerumbon terhadap Human Liver Glycogen Phosphorylase (1l5Q) sebagai Antidiabetes

Abstract

Abstrak Human Liver Glycogen Phosphorylase (HLGP), suatu katalis glikogen yang mengontrol pelepasan glukosa-1-fosfat glikogen dari hati. Enzim ini mempunyai peran sentral dalam luaran glukosa hati sehingga menjadi target obat antidiabetik. Kajian docking dilakukan pada komputer dengan prosesor Intel Pentium, RAM 1 GB dan Windows 7. Ligan yang digunakan adalah senyawa obat (Z12501572, Z00321025, SCB5631028 dan SCB13970547), dataset pembanding aktif glycogen phosphorylase outer dimer site (PYGL-out) dan decoysdari www.dekois.com dan turunan zerumbon. Protein dipisahkan dari ligan nativ dan semua ligan beserta protein dikonversi menggunakan PyRx. Visualisasi interaksi ligan-protein dihasilkan dengan program Protein-Ligand Interaction Profiler (PLIP) dan PyMOL. Senyawa ZER11 memiliki binding energy terbaik, yaitu -7.11 kkal/mol (untuk metode LGA dan GA) dan -4.08 kkal/mol untuk metode SA. Nilai binding energy tersebut lebih rendah dari pada nilai untuk ligan native dan satu dari keempat senyawa obat, terlebih jika dibandingkan dengan bindingaffinity dari dataset dan decoys. Interaksi ligan-protein pada ketiga metode tersebut ditemukan sangat bervariasi. Hal berbeda terjadi untuk metode Vina, bindingenergy ZER11 (-9.9 kkal/mol) lebih baik dibandingkan dengan ligan native dan keempat senyawa obat. Senyawa ZER11 memiliki residu interaksi yang sama dengan ligan native pada TRP67 dan LYS191 untuk metode Vina. Kata kunci: PDBID-1L5Q, AutoDock, docking molekuler, vina, antidiabetes Abstract Human Liver Glycogen Phosphorylase (HLGP) can catalyze glycogen and control the release of glucose-1-phosphate of glycogen from the liver. This enzyme has a central role in output rule of liver glucose as it can be used as an antidiabetic drug targets. Docking studies were carried out on PC with Intel Pentium, 1 GB RAM, in environment of Windows 7. Ligands used are drug compounds (Z12501572, Z00321025, SCB5631028 and SCB13970547), the active dataset comparator wasglycogenphosphorylase outer dimer site (PYGL-out) and decoys from www.dekois.com andzerumbonederivates. Protein was separated from its native ligand and all ligands including the protein were converted to pdbqt using PyRx. The interaction of protein-ligand was visualized using software of PLIP and PyMOL. Compound of ZER11 had the best binding energy were -7.11 kcal/mol (LGA and GA) and -4.08 kcal/mol (SA). The binding energy value was lower than the ligand native and one of the four drug compounds, especially compared with the binding affinity of dataset and decoys. Vice versa, for Vina method, the value of ligand binding protein for ZER11 (-9.9 kcal/mol) was better than the ligand native and all of the fourth drugcompounds. Vina result showed that ZER11 had the same residual interaction as the ligand native, which are TRP67 and LYS191. Keyword: PDBID-1L5Q, AutoDock, molecular docking, vina, antidiabetic DOI: http://dx.doi.org/10.15408/jkv.v0i0.4170

Pharmacophore Modeling and Binding Affinity of Secondary Metabolites from Angelica keiskei to HMG Co-A Reductase

“…In the discovery of new compounds, it is necessary to use active compounds and decoy compounds in a ratio of 1:10 [39,40]. Ligand-based pharmacophore modeling was conducted using 299 active compounds (actives) of HMG-CoA reductase inhibitors and 8884 inactive compounds (decoys) downloaded from the DUD-E database (A Database of Useful Decoys) [41].…”