臺灣博碩士論文加值系統

人類身體內的基質金屬蛋白質酶是生長基因的的產物，至少已經有二十種以上的基質金屬蛋白質酶已被發現，這一系列的酵素通常需要鋅與鈣離子一起參與分解蛋白質反應，在細胞外母體翻轉的自我平衡的生理學過程中，這一系列的酵素扮演的重要的角色，例如胚胎的生長與型態的發生，細胞的在吸收與重組，神經的發育與再生長，毛囊的生長，血小板的聚集，巨噬細胞與嗜中性白血球的功能，細胞轉移與增生等方面。然而基質金屬蛋白質酶最重要的方面是在許多病理學的過程中扮演著重要的角色，例如類風濕關節炎、骨關節炎、惡性腫瘤的入侵與轉移、牙周病、纖維化疾病、動脈硬化與眾所皆知的大動脈腫瘤。
基質金屬蛋白質酶抑制劑tissue inhibitors of matrix metalloproteinases (TIMPs)，利用Tripos的軟件Sybly中的CoMFA （Comparative Molecular Field Analysis）與QSAR (Structure-Activity Relationship)2與來預測Metalloproteinase 1 inhibitors的活性並且利用統計的方法得知藥物結構上的區域分部情況。抑制劑3D立體結構的的建立，使用Spartan 中semi-imprical。在CoMFA/QSAR的分析中利用I當探針得到q square＝0.533，並且使用CoMSIA （Comparative Molecular Shape Indices Analysis）的Model分析Steric Field ，Electronic Field等等的分析，並且得到最好q2分別是0.514，0.503。

The human matrix metalloproteinases (MMPs) are the products of a
growing gene family of at least 20 members of structurally related Zn - and Ca -containing neutral endopeptidases。These enzymes play important roles in extracellular matrix turnover during homeostatic physiological processes such as embryonic development， morphogenesis, tissue resorption and remodelling，nerve growth, reproduction, hair follicle development，platelet aggregation， macrophage and neutrophil function，cell migration，and angiogenesis. Nevertheless，the important role of MMPs in many pathological processes such as rheumatoid arthritis，osteoarthritis，cancer invasion，cancer metastasis，ulcerations， periodontal diseases，fibrotic diseases，atherosclerosis，epidermolysis bullosa，and aortic aneurysm is also well known。
Using the sortware named “SpartanTM” to build Matrix metalloproteinases－1 inhibitors。 Using the descriptors，CoMFA （Comparative Molecular Field Analysis）and CoMSIA（Comparative Molecular Shape Indices Analysis），to research the QSAR (Structure-Activity Relationship) of MMP1’s inhibitors。The CoMFA model give q2＝0.533 when using the atom “I” as probe。The CoMSIA models had q2＝0.514，0.503 and include steric，electronic fields。

第一章 序論
1.1 研究動機………………………..4頁
1.2 研究目的………………………. 5頁
第二章 文獻探討
2.1 定量活性關係的簡介…………..6頁
2.2 量子力學半經驗式的簡介……11頁
2.3 CoMFA、CoMSIA、PLS
的簡介………………………….12頁
第三章 材料與方法
3.1 抑制劑結構的建立……………..15頁
3.2 抑制劑結構的推疊……………..15頁
3.3 CoMFA/PLS與CoMSIA/PLS
的分析………………………….16頁
3.4 利用SYBYL的ViewQSAR
與活性的預測………………….16頁
第四章 結果與討論
4.1 CoMFA計算結果………………17頁
4.2 CoMSIA分析結果……………..17頁
4.3 總結討論……………………….. 20頁
附錄（圖）…………………………..22頁
附錄（表）…………………………..33頁
參考資料 ……………………………46頁

1.Menyan Cheng；Biswanath De；Neil G. Almstead；Stanislaw Pikul； Martin E. Dowty；Charles R. Dietsch；C. Michelle Dunaway；Fei Gu；Lily C. Hsieh；Michael J. Janusz；Yetunde O. Taiwo；and Michael G. Natchus. Design, Synthesis and Biological Evaluation of Matrix Metalloproteinase Inhibitors Derived from a Modified Proline Scaffold. J. Med. Chem. 1999,42, 5426-5436.
2.SYBYL Molecular Model System(Version 6.7) from Tripos Associates Inc.
3.Gramar III；R. D.；Bunce；J. D.；D. E.；Frank.Crossvalidation, Bootstrapping,and Partial Least Squares Compared with Mutiple Regression in Conventional QSAR.Quant.Struct-at relat.1988,7,18-25.
4.Richard D. Gramer；III*；David E. Patterson；Jeffery D. Bune.Comparative Molecular Field Analysis(CoMFA).1. Effect of Shape on Binding of Steroids to Carrier Proteins.J. Med Chem soc,1988,110,5959-5967.
5.Gerhard Klebe,Comparative Molecular Similarity Indeuces Analysis:CoMSIA,Drug Discovery and Design,1998,87-104.
6.Molecular Mechanics Force Field from Merk Associates Inc
7.Chemistry Department ,Indiana university.
8.Rick Gussio；Nagarajan Pattabiraman；Daniel W.；K.Burt,All-Atom Models for the Non-Nucleoside Binding site oh HIV-1 Reverse Transcriptase Complexed with Inhibitors: A 3D QSAR Approach, J. Med. Chem.1996,39,1645-1650.
9.Mary Bradley,Polarizability Field for Use in Three-Demension QuantitativeStructure —ActivityRelationship(3DQSAR).J.Chem.Inf.Comput.sci.2001,41,1301-1307.
10.L. L. Zhu；T. J. Hou；L. R. Chen；X. J. Xu,3DQSAR Analyses of Novel Tyrosine Kinase Inhibitors Based on Pharacophore Alignment. J.Chem.Inf.Comput.sci.2001,41,1032-1040.
11.Ronan Bureau；Cyril Deveu；Isabelle Baglin；Jana Sopkova-De Olivera Santos；Jean-Charles Lancelot；Sylvain Rault. J.Chem.Inf.Comput.sci.2001,41,815-823.
12.Piere Ducrot；Michel Legraverend；David S.Grierson. J. Med. Chem.2000,43,4098-4108.
13.Molecular Model System from IBM Associates Inc
14.Inbal Halperin；Buyong Ma；Haim Wolfson and Ruth Nussinov.Principle of Docking ：An Overview of Search Algorithm and a Guide to Scoring Functions. PROTEINS.2002,47,409-443.
15.Janin J.Elusive affinity. PROTEINS.2002,21,30-39
16.Zhongmin Wang and Florante A. Quiocho.Complexes of Adenosine
Deamonase with Two Potent Inhibitors:X-ray Structures in Four
Independent Molecules at pH of Maximum Activity.Biochemistry.
1998,37,8314-8324.
17.Morris,G.M；Goodsell,D.S.；Halliday,R.S.；Huey,R.；Hart,W.E.；
Belew,R.K.and Olson,A.J.Automated Docking Using a Lamarckian
Genetic Algorithm and Empirical Binding Free Energy Function.
J. Comput. Chem.1988,19.1639-1662.
18.B. Kramer；M. Rarey and T. Lengauer . Evaluation of the FlexX Incremental Construction Algorithm for Protein-Ligand Docking.
PROTEINS.1999,37,228-241.