臺灣博碩士論文加值系統

正常振動型分析（NMA）是預測一個指定的大分子的可能的運動的一個強有力的工具。並且能秀出目前已知一半以上的蛋白質運動；分析並使用最多兩種低頻率正常振動模式。正常振動型分析的應用包括結構生物廣闊領域，譬如蛋白質結構變動的研究，膜通道的開啟和關閉、核糖體的潛在運動、和病毒粒子外核成熟性。這裡我們利用一個網路「EIN’emo」連接提供一個快速和簡單的工具計算，分析大分子低頻率正常振動型；從50種模式中獲得頻率和集體程度運動數據及分子中的αC的b-factor。本研究使用包括從狂牛症（BSE）及從SCOP databases中取得all α 及 all β的蛋白質，再從PDB databases取得這些蛋白質序列，接著上傳到EIN’emo 分析他的50種低頻率模式並且產生一套綜合的描述參數。而得到集體程度運動和b-factor的相關數據，並利用二維座標分析其結構差異性。

Normal Mode Analysis (NMA) is forecast for a macro-molecule possible movement powerful tool,and can display the present known above half protein movement, analyzing and using most two kind of low frequency normal vibration pattern. Normal Mode Analysis can be used in a variety of application including structure biology with broad domain, for example protein structure change research, membrane channel's opening and closure, ribosome latent movement, and outside viral granule nuclear maturation. Here we use a network “EIN' emo” the web to provide fast and the simple tool for computation, and an analysis of macro-molecule of low frequency Normal Mode. Frequency and in the collectivity movement data for the member from 50 kinds of patterns αC b-factor can be obtained. The data for this research including (Bovine Spongiform Encephalopathy,BSE) obtain from the mad cow disease and from all Alpha and all Beta proteins in SCOP databases, and then uploads EIN' emo to analyze 50 kinds of low frequency patterns, and has a set of comprehensive description parameter. we obtains the collective degree movement and the B-factor correlation data, and analyze their structure difference using the two-dimensional coordinates

第一章 緒論-1
1.1 文獻回顧-2
1.1.1 EIN’emo: a normal mode web server for protein movement analysis and the generation of templates for molecular replacement-2
1.1.2 結構分類數據庫介紹-4
1.1.3 SCOP: a Structural Classification of Proteins database -10
1.1.4 Classical Normal Mode Analysis: Harmonic Approximation-12
1.1.5狂牛症的兇手 ~ 普里昂蛋白質 普里昂 (Prion) 的相關疾病-13
1.2 研究動機-15
1.3 研究目的-16
第二章 材料與方法---理論基礎 -17
2.1 材 料-17
2.1.1 Class: All alpha proteins-18
2.1.2 Class: All beta proteins -22
2.2 方 法-29
第三章 結果與討論-34
3.1 結 果-34
3.1.1 在頻率（frequency）集體程度（collectivity）方面 -34
3.1.2 在B-因素（B-factor）方面 -48
第四章 結論 -58
一．all α及all β 蛋白質頻率（frequency）比對結果-58
二．all α及all β 蛋白質集體程度（collectivity）比對結果 -59
三．all α及all β 蛋白質B因素（B-factor）比對結果-61
4.1 總 結-64
4.2 未來展望 -65
參考文獻 -66

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