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研究生:陳翊庭
研究生(外文):Yi-Ting Chen
論文名稱:針對酪胺酸酶抑制劑利用分子對接和Catalyst軟體進行3D-QSAR藥效基團研究
論文名稱(外文):3D-QSAR Pharmacophore Identification for Tyrosinase Inhibitors using Molecular Docking and Catalyst
指導教授:蕭乃文蕭乃文引用關係
指導教授(外文):Nai-Wan Hsiao
學位類別:碩士
校院名稱:國立彰化師範大學
系所名稱:生物技術研究所
學門:生命科學學門
學類:生物科技學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:78
中文關鍵詞:酪胺酸酶藥效基團假說特徵構形互補官能基分子對接標靶QSARDockingCatalystGOLD
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中文摘要
定量結構和活性關係 (QSAR, Quantitative Structure-Activity Relationship) 為最早發展出來的分析藥物與活性關係的方法,並且已由平面性 (2D) 進展至三度立體空間 (3D) 模式。經由電腦分析一系列結構不同,與蛋白質或酵素有不同程度結合能力的化學分子,將這些化學分子透過產生出各種不同的構形,利用其共通性與特異性,決定化學分子與蛋白質或酵素結合的藥效基團 (pharmacophore) 模型,如此即可以決定化學分子在三度空間中與標靶 (Target) 蛋白質結合重要作用力的絕對位置。本實驗針對酪胺酸酶 (Tyrosinase) 抑制劑依據其作用機制不同分類,其中有50個抑制劑屬與同一種作用機制,並透過 GOLD (Genetic Optimisation for Ligand Docking) 將酪胺酸酶抑制劑和標靶蛋白質酪胺酸酶進行 分子對接 (Docking),使抑制劑產生不同的構形之後,匯入 Catalyst 程式執行 QSAR 分析產生藥效基團模型。結果 : 最佳假說所建立出來的藥效基團模型所具有化學特徵分別為氫鍵給體,氫鍵受體,以及疏水性基團。這個最佳的藥效基團模型其訓練組 RMSD 值為 0.676,correlation coefficient = 0.973,Δ cost = 81.241。而測試組的 correlation coefficient = 0.729。本次實驗所建立出來的藥效基團模型可以用來鑑別酪胺酸酶抑制劑具有不同的結構骨架,但是對酪胺酸酶都具有抑制作用,是因為這群化合物都具有相同的藥效基團特徵。
目錄
英文摘要 6
中文摘要 7

第一章 序論 9
1-1 研究動機與目的 9

第二章 文獻探討 10
第一節 酪胺酸酶 (Tyrosinase) 介紹
2-1-1 酪胺酸酶 (Tyrosinase) 簡介 10
2-1-2 黑色素生合成途徑 (Biosynthesis of Melanin) 12
第二節 藥效基團 (Pharmacophore) 介紹
2-2-1 藥效基團簡介 15
2-2-2 藥效基團模型 16
2-2-3 藥效基團模型的表達 17

第三章 軟體介紹 23
第一節 Catalyst 簡介
3-1-1 Catalyst 介紹 23
3-1-2 利用 Catalyst 產生不同的構形 25
3-1-3 特徵 (Feature) 26
3-1-4 HypoGen 理論 28
3-1-5 Catalyst 操作方法 32
3-1-6 統計驗證 36
第二節 GOLD 介紹
3-2-1 GOLD 起源 37
3-2-2 簡介 37
3-2-3 理論 38
3-2-4 GOLD 參數 39

第四章 材料方法與策略 41
4-1 實驗材料 41
4-2 策略 42
4-3 Catalyst、GOLD 操作方法 42
4-3-1 化合物繪圖 42
4-3-2 Catalyst 操作方法 45
4-3-3 GOLD 操作方法 46

第五章 結果與討論 48
5-1 利用 Poling 產生構形所建立的假說的結果 48
5-2 利用分子對接產生構形所建立假說的結果 58
5-3 討論 67

第六章 結論與未來展望 71

第七章 參考文獻 72

第八章 附錄圖表 76
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