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題 名 | 建立電腦虛擬中藥篩選系統及其相關應用研究=Establishment of Chinese Herbal Virtual Highthroughput Screening System and Its Application |
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作 者 | 曾宇鳳; | 書刊名 | 中醫藥年報 |
卷 期 | 3 2014.12[民103.12] |
頁 次 | 頁(21)1-(21)65 |
分類號 | 414.3 |
關鍵詞 | 中藥; 甲型葡萄糖水解酶; FK506結合蛋白12; DNP天然產物檢索資料庫; ZINC自然產物資料庫; TCMD傳統中藥資料庫; 高通量模擬篩選; 四維結構指紋; 四維定量構效模型; Chinese herbal medicine; α-Glucosidase; FKBP12; DNP; ZINC; TCMD; High throughput screening; 4D-Fingerpints; 4D-QSAR; |
語 文 | 中文(Chinese) |
中文摘要 | 有鑑於過去藥物開發過程須耗費大量的時間、物力以及財力,近年來有越來越多透過電腦模擬技術和演算能力的方法來加速藥物開發的流程。然而,由於此類化學合成的西藥常具有毒性與嚴重的副作用,使得人類對於服用化學藥品產生疑慮,尋找回歸自然具有療效的天然藥物將是目前藥物開發的重要研究趨向。中草藥在世界各國的使用已日趨廣泛,隨著有越來越多中草藥資料庫的建置,如何在種類眾多的中草藥裡進行電腦模擬找出先導化合物,並進一步執行結構優化開發原自於天然結構且具有更強抑制活性的分子已是一件刻不容緩的事情。本研究針對阿茲海默症與糖尿病兩大方向開發中草藥之抑制劑。 本研究針對可用來治療第二型糖尿病的甲型葡萄糖水解酶抑制物與可用於治療阿茲海默症之免疫親和素 FK506結合蛋白 12(FKBP12)為標靶來發展其抑制劑。藉由從文獻中蒐集的 80組具甲型葡萄糖酶有抑制力的自然有機化合物及由共同合作者所提供經實驗證實具抑制效果之九種樟科楨楠屬植物葉部萃取物作為訓練集合,以他們的四維結構指紋建立其定量構效關係模型,並使用該模型對天然產物檢索資料庫 (DNP)、ZINC自然產物資料庫以及 TCMD傳統中藥資料庫進行快速高通量模擬篩選,找出對於甲型葡萄糖水解酶有效之中草藥先導化合物,並利用其蛋白質結構進行模擬嵌合運算,了解其可能之藥物基團 (Pharmacophore)位置,最後利用分子動態模擬之結果,建立受體相關之四維定量構效模型進行結構優化以開發出新藥。就開發阿茲海默症藥物的部分,我們利用蛋白質嵌合和分子動態模擬的方法尋找 AICD在 FK506結合蛋白 12的結合位置,接著針對這個位置收集會結合上去的九個分子,其後的計算方法與開發甲型葡萄糖水解酶抑制物類似,並已篩選出可供後續實驗發展之候選中草藥結構。 |
英文摘要 | In the past, the drug development process costed a lot of time and expenditures. Recently, more and more computational modeling and calculation methods were applyed in the process of drug development and thus made it more efficiency. Because many chemical synthesized compounds have serious toxicity and side-effect, people are afraid to take these western medicines. Searching natural and therapeutic products is a significant trend for drug development. With more and more establishment of the natural product libries, exploring the lead compounds from the high-throughput herbal medicines by in-silico simulation methodology and lead optimization to highly increase inhibition activities of molecules is urgent need. In this study, we will focus on the development of inhibitors for Alzheimer's disease and Type II Diabetes mellitus. The target in our study focuses on α-Glucosidase in type II diabetes and FKBP12, an immunophilin, in Alzheimer's disease. From the literatures, there are 80 natural organic compounds with the inhibition of α-Glucosidase and the leaves of 9 Machilus philippinensis with the proven inhibition efficiency for training set. Furthermore, 9 compounds with inhibition of FKBP12 inhibitors were also collected. We have constructed their QSAR models using 4D fingerprints and random forest techniques. The features identified by the QSAR models were applied to perform high throughput screening for the DNP, ZINC, and TCMD database. We found out the lead compound candidates of Chinese herbs that work with α-Glucosidase, and simulate their docking with protein structures, and understand the possible position of the pharmacophore. And finally according to the results of molecular dynamic simulation, we built receptor-based 4D-QSAR models to perform lead optimization for new drug exploration. In the part of Alzheimer drug development, we found out the binding site of FKBP12 with AICD by protein docking and molecular dynamic simulation. The compounds which interact with the binding position were collected using the similar techniques applied to the α-Glucosidase. |
本系統中英文摘要資訊取自各篇刊載內容。