跳到主要內容

簡易檢索 / 詳目顯示

回結果列表
研究生： 朱文淵
Wen-yuan Chu
論文名稱： Alanine Scanning Mutagenesis of Aβ(17-42) Amyloid Fibril Stability by Molecular Dynamics Simulations
指導教授： 蔡惠旭
Hui-Hsu Gavin Tsai
口試委員:
學位類別： 碩士
Master
系所名稱： 理學院 - 化學學系
Department of Chemistry
論文出版年： 2015
畢業學年度： 103
語文別： 英文
論文頁數： 78
中文關鍵詞： 類澱粉蛋白 、分子動態模擬 、纖維 、穩定性 、丙胺酸
外文關鍵詞： amyloid, Molecular dynamics, Fibrillation, stability, alanine
相關次數： 點閱：21  下載：0 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 阿茲罕默症(Alzheimer’s disease)的主要特色是腦中有斑塊聚集沉澱，然後堆積在神經細胞膜上造成神經死亡。而這些斑塊聚集物主要是由乙型-類澱粉蛋白(Amyloid-)所組成。乙型-類澱粉蛋白纖維(Amyloid-fibril)因為錯誤折疊而自組裝聚集形成。由於目前並不完全清楚知道乙型-類澱粉蛋白聚集和穩定纖維的機制，所以找出穩定乙型-類澱粉蛋白纖維的因素是相當重要的議題。
    我們利用生物實驗上常用的丙氨酸突變掃描法去探討乙型-類澱粉蛋白纖維穩定要素並使用全原子分子動態模擬來達成此實驗。為了探討胜肽之間的作用力，我們把各個胺基酸有系統性的突變為丙氨酸並藉由分子動態模擬做此實驗。我們分析二級結構，鹽橋(D23-K28)維持傾向，還有跟固態NMR解出結構做偏差比較的RMSD和RMSF數值。
    我們模擬結果為野生型(wild type)和突變物(mutants)在C端都會翹起。普遍來說，變異物的strands 2 相較於strands 1是穩定的。甘氨酸是-sheet結構的破壞者，在甘氨酸突變為丙氨酸的試驗中發現，大部分結果顯示出丙氨酸會增加突變區域二級結構的穩定性。另外在我們胺基酸交換位於strands 1和strands 2配對的實驗中發現，其模擬結果顯示和野生型一樣是穩定，因此我們認為胺基酸位於strands 1和strands 2配對的作用力可能是穩定乙型-類澱粉蛋白纖維的關鍵因素之一。在本研究中，系統性調查每個胺基酸側鏈的作用力和乙型-類澱粉蛋白纖維穩定的關係。

    Alzheimer’s disease (AD) is characterized by the extracellular deposit of senile plaques in the brain. Senile plaques are mainly composed of the aggregated amyloid beta (Aβ) protein called amyloid. Amyloid fibrils are semi-ordered nanostructures as the result of self-assembly of proteins when they are misfolded under critical conditions. Due to the complexity of Aβ amyloids, the underlying biophysical mechanisms of formation and stability of amyloid fibril are still unclear. Therefore, it is crucial to determine the factors in stabilizing Aβ amyloid fibrils.
    Motivated by Ala mutagenesis in biochemical research, we employed all-atom molecular dynamics simulations to investigate the relative stability of Aβ-fibril like oligomer and its mutants by alanine mutagenesis. To investigate the intra-peptide interactions, we simulated the structures of Aβ-fibril like oligomer with one of its residue is systemically mutated to Alanine by MD simulations. The secondary structure, salt-bridge between D23 and K28, RMSF and RMSD deviated from the solid-state NMR determined structure are analyzed.
    Our results show wild type as well as most mutants have their C-terminal residues bent. In general, the strands 2 are less stable and strands 1 are relatively more stable. Gly residues are -sheet breaker. Ala mutagenesis of Gly residues generally enhances the -sheet propensity locally. Swapping the two packed residues on strands1 and 2 does not cause the instability of amyloid fibril indicating that the packing interactions are important in stabilizing amyloid fibril. Our study systemically investigates the roles of side chain of each residue on the stability of amyloid fibrils.

    摘要 i Abstract iii 致謝 v Table of contents vi List of Figures vi List of Tables ix Chapter 1 – Introduction 1 Chapter 2 – Computational Methods 7 Chapter 3 – Results and Discussion 11 3.1 Wild Type 15 3.2 Ala Mutagenesis of Odd-numbered Residues of Strands β1 18 3.3 Ala Mutagenesis of Even-numbered Residues of Strands β1 25 3.4 Ala Mutagenesis of Residues of Turn 30 3.5 Ala Mutagenesis of Even-numbered Residues of Strand β2 36 3.6 Ala Mutagenesis of Odd-numbered Residues of Strand β2 41 3.7 Mutants F19G/G38F and A21V/V36A: Swap the packed residues within β-sheet 48 Chapter 4 – Conclusion and Summary 54 References 56 Appendix A 62 Appendix B 63

    References
    [1] C.B. Anfinsen, The formation and stabilization of protein structure, Biochemical Journal, 128 (1972) 737-749.
    [2] M. Stefani, C. Dobson, Protein aggregation and aggregate toxicity: new insights into protein folding, misfolding diseases and biological evolution, Journal of Molecular Medicine, 81 (2003) 678-699.
    [3] R. Tycko, Progress towards a molecular-level structural understanding of amyloid fibrils, Current Opinion in Structural Biology, 14 (2004) 96-103.
    [4] M.F. Mendez, Early-onset Alzheimer’s Disease: Nonamnestic Subtypes and Type 2 AD, Archives of medical research, 43 (2012) 677-685.
    [5] G. McKhann, D. Drachman, M. Folstein, R. Katzman, D. Price, E.M. Stadlan, Clinical diagnosis of Alzheimer's disease: Report of the NINCDS‐ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease, Neurology, 34 (1984) 939.
    [6] R. Jakob-Roetne, H. Jacobsen, Alzheimer's Disease: From Pathology to Therapeutic Approaches, Angewandte Chemie International Edition, 48 (2009) 3030-3059.
    [7] J. Hardy, D.J. Selkoe, The Amyloid Hypothesis of Alzheimer's Disease: Progress and Problems on the Road to Therapeutics, Science, 297 (2002) 353-356.
    [8] C. Haass, D.J. Selkoe, Soluble protein oligomers in neurodegeneration: lessons from the Alzheimer's amyloid [beta]-peptide, Nature Reviews Molecular Cell Biology, 8 (2007) 101-112.
    [9] D.J. Selkoe, Cell biology of protein misfolding: The examples of Alzheimer's and Parkinson's diseases, Nature Cell Biology, 6 (2004) 1054-1061.
    [10] R. Vassar, M. Citron, Aβ-Generating Enzymes: Recent Advances in β- and γ-Secretase Research, Neuron, 27 (2000) 419-422.
    [11] T.J. Erb, P. Kiefer, B. Hattendorf, D. Günther, J.A. Vorholt, GFAJ-1 Is an Arsenate-Resistant, Phosphate-Dependent Organism, Science, 337 (2012) 467-470.
    [12] J.B. Paulson, M. Ramsden, C. Forster, M.A. Sherman, E. McGowan, K.H. Ashe, Amyloid Plaque and Neurofibrillary Tangle Pathology in a Regulatable Mouse Model of Alzheimer’s Disease, The American Journal of Pathology, 173 (2008) 762-772.
    [13] Y. Miller, B. Ma, R. Nussinov, Polymorphism of Alzheimer's Aβ(17-42) (p3) Oligomers: The Importance of the Turn Location and Its Conformation, Biophysical Journal, 97 (2009) 1168-1177.
    [14] T. Luhrs, C. Ritter, M. Adrian, D. Riek-Loher, B. Bohrmann, H. Dobeli, D. Schubert, R. Riek, 3D structure of Alzheimer's amyloid-beta(1-42) fibrils, Proceedings of the National Academy of Sciences. U S A, 102 (2005) 17342-17347.
    [15] B. Tarus, J.E. Straub, D. Thirumalai, Dynamics of Asp23−Lys28 Salt-Bridge Formation in Aβ10-35 Monomers, Journal of the American Chemical Society, 128 (2006) 16159-16168.
    [16] R. Tycko, Molecular structure of amyloid fibrils: insights from solid-state NMR, Quarterly Reviews of Biophysics, 39 (2006) 1-55.
    [17] O.S. Makin, E. Atkins, P. Sikorski, J. Johansson, L.C. Serpell, Molecular basis for amyloid fibril formation and stability, Proc. Proceedings of the National Academy of Sciences. U S A, 102 (2005) 315-320.
    [18] W.L. Jorgensen, J. Chandrasekhar, J.D. Madura, R.W. Impey, M.L. Klein, Comparison of simple potential functions for simulating liquid water, The Journal of Chemical Physics, 79 (1983) 926-935.
    [19] W. Humphrey, A. Dalke, K. Schulten, VMD: Visual molecular dynamics, Journal of Molecular Graphics, 14 (1996) 33-38.
    [20] L. Kalé, R. Skeel, M. Bhandarkar, R. Brunner, A. Gursoy, N. Krawetz, J. Phillips, A. Shinozaki, K. Varadarajan, K. Schulten, NAMD2: Greater Scalability for Parallel Molecular Dynamics, Journal of Computational Physics, 151 (1999) 283-312.
    [21] A.D. MacKerell, D. Bashford, M. Bellott, R.L. Dunbrack, J.D. Evanseck, M.J. Field, S. Fischer, J. Gao, H. Guo, S. Ha, D. Joseph-McCarthy, L. Kuchnir, K. Kuczera, F.T.K. Lau, C. Mattos, S. Michnick, T. Ngo, D.T. Nguyen, B. Prodhom, W.E. Reiher, B. Roux, M. Schlenkrich, J.C. Smith, R. Stote, J. Straub, M. Watanabe, J. Wiórkiewicz-Kuczera, D. Yin, M. Karplus, All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins, The Journal of Physical Chemistry B, 102 (1998) 3586-3616.
    [22] J.-P. Ryckaert, G. Ciccotti, H.J.C. Berendsen, Numerical integration of the cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes, Journal of Computational Physics, 23 (1977) 327-341.
    [23] S.E. Feller, Y. Zhang, R.W. Pastor, B.R. Brooks, Constant pressure molecular dynamics simulation: The Langevin piston method, The Journal of Chemical Physics, 103 (1995) 4613-4621.
    [24] P.J. Steinbach, B.R. Brooks, New spherical-cutoff methods for long-range forces in macromolecular simulation, Journal of Computational Chemistry, 15 (1994) 667-683.
    [25] W. Kabsch, C. Sander, Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features, Biopolymers, 22 (1983) 2577-2637.
    [26] S. Kumar, R. Nussinov, Close-Range Electrostatic Interactions in Proteins, ChemBioChem, 3 (2002) 604-617.
    [27] G. Reddy, J.E. Straub, D. Thirumalai, Influence of Preformed Asp23−Lys28 Salt Bridge on the Conformational Fluctuations of Monomers and Dimers of Aβ Peptides with Implications for Rates of Fibril Formation, The Journal of Physical Chemistry B, 113 (2009) 1162-1172.
    [28] A.H.C. Horn, H. Sticht, Amyloid-β42 Oligomer Structures from Fibrils: A Systematic Molecular Dynamics Study, The Journal of Physical Chemistry B, 114 (2010) 2219-2226.
    [29] A. Kahler, H. Sticht, A.H.C. Horn, Conformational Stability of Fibrillar Amyloid-Beta Oligomers via Protofilament Pair Formation – A Systematic Computational Study, PLoS ONE, 8 (2013) e70521.
    [30] T. Takeda, D.K. Klimov, Replica Exchange Simulations of the Thermodynamics of Aβ Fibril Growth, Biophys. J., 96 (2009) 442-452.
    [31] W.M. Berhanu, U.H.E. Hansmann, Side-chain hydrophobicity and the stability of Aβ(16–22) aggregates, Protein Science : A Publication of the Protein Society, 21 (2012) 1837-1848.
    [32] J.A. Lemkul, D.R. Bevan, Assessing the Stability of Alzheimer’s Amyloid Protofibrils Using Molecular Dynamics, The Journal of Physical Chemistry B, 114 (2010) 1652-1660.
    [33] D. Boyd-Kimball, H. Mohmmad Abdul, T. Reed, R. Sultana, D.A. Butterfield, Role of Phenylalanine 20 in Alzheimer's Amyloid β-Peptide (1-42)-Induced Oxidative Stress and Neurotoxicity, Chemical Research in Toxicology, 17 (2004) 1743-1749.
    [34] N.S. de Groot, F.X. Aviles, J. Vendrell, S. Ventura, Mutagenesis of the central hydrophobic cluster in Aβ42 Alzheimer's peptide, FEBS Journal, 273 (2006) 658-668.

    QR CODE
    :::