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Abstrak :
ABSTRAK Diabetes merupakan penyakit yang dikarakterisasi dengan meningkatnya kadar gula darah yang yang diakibatkan defisiensi insulin, resistensi insulin atau keduanya. Pengobatan diabetes berfokus pada insulin, dimana efikasinya dapat berkurang seiring penyakit berprogresi. Golongan penghambat Sodium-Glucose Linked Transporter 2 (SGLT2) merupakan golongan obat diabetes baru dengan mekanisme pengaturan kadar glukosa darah independent dari insulin, ditambah khasiat menurunkan resiko kardiovaskular dan berat badan. Fakultas Farmasi Universitas Indonesia berkontribusi dalam pengembangan golongan obat ini dengan metode in silico melalui penapisan virtual berbasis ligan berdasarkan gugus farmakofor dari pangkalan data tanaman herbal Indonesia, dan penapisan virtual berbasis struktur dengan model homologi hSGLT2 dari pangkalan data ZINC15. Hasil penapisan virtual tersebut dilakukan identifikasi lebih lanjut dengan simulasi dinamika molekuler selama 20 nanodetik untuk memperoleh perkiraan yang paling mendekati kondisi eksperimental. Sebelum simulasi, dilakukan pemerolehan model interaksi pada hasil penapisan virtual berbasis ligan dilakukan dengan penambatan molekuler dengan AutoDock terhadap makromolekul hasil pemodelan homologi dari SWISSMODEL. Interaksi ligan-reseptor dilihat dari interaksi hidrogen dan energi bebas ikatan ligan dibandingkan kontrol positif dengan MM/PB(GB)SA. Hasil studi dinamika molekuler menunjukkan empat senyawa dengan ∆G MM/PB(GB)SA lebih kecil dibanding kontrol positif, diantaranya zinc000146809581, cucumerin A, zinc000038175116, dan zinc000095913941 dengan jumlah ikatan hidrogen yang lebih banyak atau dapat bersaing dengan kontrol positif.

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ABSTRACT Diabetes is a non-communicable disease that is characterized by the rising of blood glucose due to deficiency of insulin, insulin resistance, or both. Pharmacological treatment of diabetes mainly focuses on insulin, which decreases in efficacy once the disease progresses. SGLT2 inhibitors are diabetic treatments available in recent years with blood glucose control mechanism independent from insulin. Two in silico research were done in Faculty of Pharmacy from Universitas Indonesia to find more compounds of potential SGLT2 inhibition action by virtual screening of ligand based on Indonesian Herbal Database, dan of structure-based on the ZINC herbal database. In this study, the docked interaction models of the compounds acquired from those two virtual screening methods are analyzed for their ligand-receptor interactions by 20 nanoseconds of molecular dynamic simulations, with the ligand-based virtual screening results were first docked with macromolecule from homology modelling. The ligand-receptor interactions are observed by its calculated binding free energy and their hydrogen interactions with the protein, compared with known drugs of SGLT2 inhibitors as positive controls. The result of this study has shown four compounds with lower ∆G MM/PB(GB)SA than the positive controls, cucumerin A, zinc000146809581, zinc000038175116, and zinc000095913941 with more or comparable hydrogen interactions with positive controls.

Abstrak :
ABSTRAK
Diabetes melitus tipe 2 (DMT2) adalah jenis diabetes yang paling umum di dunia. Baris kedua pengobatan DMT2 yang dapat menghambat pelepasan glukagon dan meningkatkan sekresi insulin adalah inhibitor DPP-IV. Enzim DPP-IV yang terdapat dalam tubuh manusia dapat diproduksi oleh tubuh sendiri atau dari bakteri yang terdapat di usus, seperti Parabacteroides goldsteinii dan Bacteroides fragilis. Dalam penelitian ini dilakukan penyelarasan sekuens bakteri dan pemodelan homologi. Docking makromolekul DPP-IV manusia dan model bakteri dilakukan terhadap setiap situs aktif DPP-IV manusia menggunakan aplikasi PyRx. Persentase kemiripan urutan antara DPP-IV manusia dan model DPP-IV bakteri (% urutan yang dipertahankan;% dari semua urutan), P.goldsteinii (46,15%, 24,18%) dan B. fragilis (92,31%; 20, 04% ). Parameter optimasi untuk molecular docking DPP-IV yaitu kotak grid dengan ukuran 50x50x50 unit dengan jarak spasi 0,375 dan evaluasi energi sebesar 5.000.000. Berdasarkan hasil analisis nilai indeks selektivitas diperoleh senyawa penghambat DPP-IV yaitu gemigliptin yang relatif selektif pada P.goldsteinii dengan nilai indeks selektivitas 1,34 x10-4 dan retagliptin yang relatif selektif pada B. fragilis dengan nilai indeks selektivitas 0,05 x10 -4 diantara 16 ligan lain pada tiga sisi aktif enzim DPP-IV. Hasil ini menunjukkan bahwa gemigliptin dan retagliptin dapat digunakan sebagai data pendukung dalam perancangan molekul baru dan perkembangannya sebagai penghambat DPP-IV selektif untuk pasien diabetes melitus tipe 2 (DMT2).
ABSTRACT
Diabetes mellitus type 2 (T2DM) is the most common type of diabetes in the world. The second line of T2DM treatment that can inhibit glucagon release and increase insulin secretion are DPP-IV inhibitors. The DPP-IV enzyme found in the human body can be produced by the body itself or from bacteria found in the intestines, such as Parabacteroides goldsteinii and Bacteroides fragilis. In this study, bacterial sequence alignment and homology modeling were carried out. Docking of human DPP-IV macromolecules and bacterial models was carried out against each active human DPP-IV site using the PyRx application. Percentage of sequence similarity between the human DPP-IV and the bacterial DPP-IV model (% retained sequences;% of all sequences), P.goldsteinii (46.15%, 24.18%) and B. fragilis (92.31%; 20, 04%). The optimization parameters for the DPP-IV molecular docking are a grid box with a size of 50x50x50 units with a spacing of 0.375 and an energy evaluation of 5,000,000. Based on the results of the selectivity index value analysis, the DPP-IV inhibitor compound was obtained, namely gemigliptin which was relatively selective in P.goldsteinii with a selectivity index value of 1.34 x10-4 and retagliptin which was relatively selective in B. fragilis with a selectivity index value of 0.05 x10-4. among 16 other ligands on the three active sites of the DPP-IV enzyme. These results indicate that gemigliptin and retagliptin can be used as supporting data in the design of new molecules and their development as selective DPP-IV inhibitors for type 2 diabetes mellitus (T2DM) patients.

Abstrak :
In this book the authors take an alternate approach to these theorems and generalize them to the setting of Hilbert modular varieties of arbitrary dimension. The approach is conceptual and uses tools that were not available to Hirzebruch and Zagier, including intersection homology theory, properties of modular cycles, and base change. Automorphic vector bundles, Hecke operators and Fourier coefficients of modular forms are presented both in the classical and adèlic settings. The book should provide a foundation for approaching similar questions for other locally symmetric spaces.