糖尿病為國人十大死因之前五名，本研究以第二型糖尿病為目標，自中草藥為資料庫，致力研發新治療藥物或尋找天然食材成份，來達到治療及預防疾病之用。目前，治療糖尿病相關的口服藥物有五大類，包括：dipeptidyl piptidase-4 (DPP4)inhibitor。DPP4廣泛分佈於人體各組織中，經由切割dipeptide，而有多種功能。DPP4在腸道之主要功能為分解腸泌素GLP-1 (glucagon-like peptide)，即是調控血糖平衡重要的激素。若GLP-1被分解，失去調控血糖之能力，將導致體內葡萄糖無法正常調控，而衍生出糖尿病末期因血糖控制不佳之後遺症。因此，DPP4成為研發治療糖尿病藥物之重要標靶，而DPP4 inhibitor已發現為治療二期糖尿病之有效藥物。近年來，因生物資訊學及結構生物學的進步，使得電腦輔助藥物設計蓬勃發展。電腦輔助藥物設計可以快速篩選出對受體分子結合能力強的小分子，與傳統藥物篩選不同，只需有標靶蛋白之3D structure、ligand之3D資料庫與電腦軟體，即可進行快速篩選，再經過一系列過濾，選出可能有效果的compound，再進行生物實驗。本研究利用Dicovery Studio軟體，針對DPP4進行分子對接 (docking)，最後篩選出六個天然物分子，分別來自白茅根、鉤藤、育亨賓、黃柏、黃連、太白蔥木。未來將取得compound，進行生物實驗，期望能成為副作用更低，有潛力抑制DPP4之藥物。

Diabetes has been one of the top five leading causes of death in Taiwan. The present study aimed to develop new therapeutic drugs or natural ingredients as supplement for the treatment and prevention of type II diabetes. Currently, the diabetes-related oral drugs can be classified into five categories including dipeptidyl peptidase-4 (DPP4) inhibitors. DPP4 has been widely distributed in human tissues and cell. Through cleaving dipeptides, DPP4 performs a variety of physiological functions. The main function of DPP4 in human guts is to cleave GLP-1 (glucagon-like peptide-1), the most important hormone which regulating blood sugar level. If GLP-1 lost its function, severe syndromes will be developed at the late stage of diabetes. Therefore, DPP4 has become an important target for the development of drugs against type II diabetes .
　　In recent years, the advances in bioinformatics and structural biology have made the computer-aided drug design (computer aided drug design) feasible. We employed high-throughput virtual screening (in silico) approach, using DPP4 as molecular target, to screen for novel drug candidates from the TCM (Traditional Chinese Medicine) database. Finally, we selected six molecule, originally isolated from Aralia taibaiensis, Imperata cylindrical, Pausinystalia yohimbe, Coptis chinensis Franch, Uncaria rhynchophylla and Phelloendron amurense. Through further DPP4 inhibition experimental studies, it is anticipated that they may have the potential to become drug candidates against type II diabetes.

致謝……………………………………………………………...…....…….II
目錄………………………………………………………………...……...III
中文摘要....………………………………...……………………………..V
英文摘要……………………………………...…………………………..VI
壹、研究目的及策略…………………………………………………...…..1
貳、研究背景………………………………………………………...…......2
1. 糖尿病之致病原因……………………………………….…………………..2
2. 腸泌素與GLP-1…………………………………………………......4
3. Dipeptidyl piptidase-4 (DPP-4)……………………………………..8
4. 電腦輔助藥物設計………………………………………………….10
5. 蛋白質資料庫 (Protein Data Bank, PDB)………………..……..12
6. 小分子資料庫 (Traditional Chinese Medicine, TCM)……………....12
7. 蛋白質及結構分析軟體(Discovery Studio, DS)………………..13
8. ADMET及其預測軟體…………………………………………..…14
參、研究方法與設備…………………………………………………………………...17
1. 研究儀器設備……………………………………………………………….17
2. 研究方法…………………………………………………………………….18
A. 蛋白質與小分子資料庫之結構處理……………………...…………..18
B. 以Discovery Studio 3.5軟體進行分子對接……………………….….19
C. Docking結果之再處理.……………………..………………….20
D. ADMET descriptor程序.…………………………….……………….21
E. 追溯篩選出小分子之植物來源與相關藥效功能…………22
F. 分析Ligand小分子與DPP4 binding site之相互作用………………..23
肆、結果……………………………………………………………………………..….25
1. 挑選DPP-4之3D結構作為Docking標靶…………………………...……..25
2. DS虛擬篩選結果-初步與精確篩選結果….…...……….…………..25
3. 選出小分子之簡要說明……………………………………………………26
4. 選出小分子之植物根源及相關藥效與功用之詳細說明………………….27
5. 候選抑制分子之ADMET預測……………………………………….…….29
6. 候選抑制分子與DPP4之交互作用分析…………………………………...35
伍、討論與未來展望…………………………………………………………………...37
陸、參考文獻……………...……………………………………………………………38
柒、圖表………………………………………………………………………………..40

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