帳號:guest(18.116.21.152)          離開系統
字體大小: 字級放大   字級縮小   預設字形  

詳目顯示

以作者查詢圖書館館藏以作者查詢臺灣博碩士論文系統以作者查詢全國書目
作者(中文):何沅達
作者(外文):Ho, Yuan-Ta
論文名稱(中文):高效且具有鳥嘌呤結合專一性的RNA結合蛋白可演化為不需ATP的dsDNA解旋酶
論文名稱(外文):ATP-Independent dsDNA Helicases Could be Evolved from Potent RNA-Recognition Motifs Leveraging a Guanine-Binding Specificity
指導教授(中文):楊立威
指導教授(外文):Yang, Lee-Wei
口試委員(中文):蔡惠旭
黃人則
口試委員(外文):Tsai, Hui-Hsu
Huang, Jen-Tse
學位類別:碩士
校院名稱:國立清華大學
系所名稱:生物資訊與結構生物研究所
學號:104080597
出版年(民國):107
畢業學年度:106
語文別:中文
論文頁數:75
中文關鍵詞:TAR去氧核糖核酸結合酶-43RNA結合蛋白RNA識別基序DNA解旋酶單股DNA結合分子動力學模擬演化雙股DNA結合位高斯加速分子動力學富含TG基序富含UG基序力場分子力學泊松-玻爾茲曼表面積伴隨蛋白傅立葉轉換分子對接固有動態結構域
外文關鍵詞:TDP-43RNA-binding proteinRNA recognition motifDNA helicasessDNA bindingmolecular dynamics simulationevolutiondsDNA binding siteGaussian accelerated MDTG-rich motifUG-rich motifAMBERMM/PBSAchaperoneFTDOCKintrinsic dynamics domain
相關次數:
  • 推薦推薦:0
  • 點閱點閱:30
  • 評分評分:*****
  • 下載下載:0
  • 收藏收藏:0
RNA binding motifs 扮演多功能角色,如參與RNA splicing, 解旋RNA hairpins和抑制dsDNA轉錄等,對於細胞內的平衡與轉譯的控制扮演重要的角色。然而,他們彼此間的關係為何?是否這些功能有著共同的物理性質以致於一個功能可以經透過演化和稍許的化學修飾被修改成另一個? 在本文中,我們演示了兩個結構上一樣但序列間不同的RNA Recognition Motifs (RRM1和RRM2),兩者對於結合RNA和ssDNA具有不同的親和力 (差了約百倍左右)。RRM1對RNA有更強的結合力且被發現在沒有ATPs的情況下能解旋ds(TG)6,而對RNA有較弱結合力的RRM2則無法解旋dsDNA。經由一系列的實驗與模擬分析,包含fluorescence anisotropy、F-EMSA、FRET、生物資訊 (保守程度)、蛋白質-蛋白質對接、Gaussian-accelerated (Ga-) MD simulations及X-ray與NMR的證據支持,我們認為對於RNA骨幹和鳥嘌呤 (Guanine)有專一結合力RNA結合蛋白較強的結合者可以演化成不需要ATPs的dsDNA解旋酶。在這過程中,部分ssDNA的結合位點也可作為dsDNA的結合位點,結合住dsDNA的major grooves,並在dsDNA間歇性地打開時快速地抓著一股ssDNA以幫助解旋。因為實驗和計算兩者都發現一個RRM1結合ssDNA後,兩個RRM1將更容易結合ssDNA,所以RRM1解旋dsDNA被認為有偕同性。因此,我們主張與ssDNA/dsDNA相關的蛋白質的功能可以從RNA chaperone藉由修改極少數量的氨基酸組成而得到,這支持了一個從只有RNA跟蛋白質的世界衍生到有RNA、蛋白質與DNA共存的世界。本研究也提供了對於在未來設計基因編輯相關的解旋酶和及設計抑制專一dsDNA序列的轉錄抑制劑的一個重要參考。
RNA binding motifs serve multiple functions, including RNA splicing, unwinding of RNA hairpins and suppression of (ds)DNA transcription, and play important roles in intracellular homeostasis and translational control. However, it is not clear whether these functions share a physical origin and are related evolutionarily? In this study, we showcase two RNA Recognition Motifs (RRM1 and RRM2) that share a similar structural fold but differ in primary sequences (~25% sequence identity). The two RRMs differ in their RNA and ssDNA binding affinity by >100 fold. RRM1 that has a stronger RNA binding affinity is found to be able to unwind ds(TG)6 in the absence of ATPs while RRM2 cannot. After a series of experiments and molecular dynamics simulations analyses including fluorescence anisotropy, FRET, F-EMSA, residue conservation, protein-protein docking, Gaussian- accelerated molecular dynamic (GaMD) simulations and structural evidence from x-ray/NMR, we propose that RRMs that can favorably bind backbone of RNA and have specificity in guanine can be evolved into energy-independent dsDNA helicase. In this process, part of ssDNA binding site in RRM1 can also serve as part of the dsDNA binding site that anchors the major grooves of dsDNA. Multiple RRM1s could cooperatively bind transiently opened dsDNA to unwind the double strands, which is supported by both experi-mental and computational evidence demonstrating when one RRM1 binds ssDNA, the second one can bind the same ssDNA more favorably. Our analyses suggest a RNA chaperone could be evolved to bind relevant ssDNA and/or unwind specific dsDNA by modifying less than a handful residues. This argument supports the hypothesis that life is evolved from a RNA+ protein world to a RNA+ protein + DNA world. This study also offers an important reference for the design of gene editing-associated helicases and transcriptional inhibitors that bind specific sequences of dsDNA.
摘要 i
Abstract ii
致謝 iii
目錄 iv
圖目錄 vi
表目錄 vii
1. 緒論 1
2. 方法 4
2.1 分子動力學模擬 4
2.1.1 創建分子動力模擬的起始結構 5
2.1.2 加水與離子 9
2.1.3 分子動力模擬的相關參數設置: 9
2.2 Gaussian Accelerated Molecular Dynamics simulations (GaMD) 12
2.3 用FTDock來進行Protein-dsDNA Docking 13
2.4 高斯網絡模型 (Gaussian Network Model; GNM) 15
2.5 用Intrinsic Dynamics Domains (IDDs)來過濾FTDOCK結果,並且將docking 複合體結構叢集化 (clustering),再照叢集大小來排序docking複合體 16
2.6 方均根差 (Root-Mean Square Deviation; RMSD) 16
2.7 接觸分析 (Contact Analysis) 17
2.8 分子力學泊松-玻爾茲曼表面積 (Molecular Mechanics Poisson–Boltzmann Surface Area; MM-PBSA) 18
2.9 保守分數 (Conservation score) 19
2.10 Flexible Structure Alignment by Chaining Aligned fragment pairs allowing Twists (FATCAT) Pairwise Alignment 19
2.11 用螢光非等向性 (Fluorescence Anisotropy)來量測Kd 20
2.12 用螢光電泳遷移率分析化學當量 (stoichiometry) 21
3.結果 22
3.1 蛋白-核酸結合力的實驗與模擬結果之對照 22
3.2 RRM1/RRM2結合(UG)6的能量的相同處以及相異處比較 23
3.3 RRM1/RRM2結合ss(TG)6的能量的相同處以及相異處比較 31
3.4 RRM1與ss(TG)6/(UG)6結合時在殘基結合上的相同處以及相異處比較 39
3.5 RRM2與ss(TG)6/(UG)6結合時在殘基結合上的相同處以及相異處比較 43
3.6 蛋白質殘基與核酸鹼基的親和力解析 47
3.6.1 RRM1結合核糖核酸比去氧核醣核酸更好的原因主要是因為核糖上的二號碳中的氧比胸腺嘧啶的甲基團更重要 47
3.6.2 鳥嘌呤比胸腺嘧啶/尿嘧啶更重要 49
3.6.3 RRM2上的點突變E200W與I253R佐證殘基能量分析的正確性: 50
3.7 以FRET實驗證明RRM1可解旋ds(TG)6 51
3.8 殘基接觸核酸的機率分析 52
3.9 用Gaussian Accelerated (Ga-) MD解旋dsDNA的結果 55
3.10 RRMs與核甘酸的化學計量數 (stoichiometry) 58
3.11 模擬2:1與1:1的能量比較 (蛋白質:核甘酸) 59
3.12 RRM1可彎曲ss(TG)6,但 RBD不能彎曲ss(TG)6 60
4. 討論 62
4.1 各模擬系統中前20名殘基二級結構分布: 62
4.2 RRM1/2 結合ssDNA/RNA能量結果與點突變實驗對照 63
4.3 Thymine /Uracil 與Guanine的重要性比較 65
4.4 RRM1的演化推論 67
5. 結論 69
參考文獻 71

Ashkenazy, Haim et al. 2016. “ConSurf 2016 : An Improved Methodology to Estimate and Visualize Evolutionary Conservation in Macromolecules.” 44(May): 344–50.
Haim, Ashkenazy et al. 2018. “ConSurf 2010 : Calculating Evolutionary Conservation in Sequence and Structure of Proteins and Nucleic Acids.” 38(January): 529–33.
Bahar, Ivet, Ali RanaAtilgan, &BurakErman. 1997. “Direct Evaluation of Thermal Fluctuations in Proteins Using a Single-Parameter Harmonic Potential.” Folding and Design 2(3): 173–81.
Barreau, Carine, LucPaillard, &H. BeverleyOsborne. 2005. “AU-Rich Elements and Associated Factors: Are There Unifying Principles?” Nucleic Acids Research 33(22): 7138–50.
Belly, Agnès, FrançoiseMoreau-Gachelin, RémySadoul, &YvesGoldberg. 2005. “Delocalization of the Multifunctional RNA Splicing Factor TLS/FUS in Hippocampal Neurones: Exclusion from the Nucleus and Accumulation in Dendritic Granules and Spine Heads.” Neuroscience Letters 379(3): 152–57.
Buratti, Emanuele, &Francisco E.Baralle. 2001. “Characterization and Functional Implications of the RNA Binding Properties of Nuclear Factor TDP-43, a Novel Splicing Regulator of CFTR Exon 9.” Journal of Biological Chemistry 276(39): 36337–43.
Celniker, Gershon et al. 2013. “ConSurf : Using Evolutionary Data to Raise Testable Hypotheses about Protein Function.” : 199–206.
Chang, Chung ke et al. 2012. “The N-Terminus of TDP-43 Promotes Its Oligomerization and Enhances DNA Binding Affinity.” Biochemical and Biophysical Research Communications 425(2): 219–24. http://dx.doi.org/10.1016/j.bbrc.2012.07.071.
Deschênes-Furry, Julie, NoraPerrone-Bizzozero, &Bernard J.Jasmin. 2006. “The RNA-Binding Protein HuD: A Regulator of Neuronal Differentiation, Maintenance and Plasticity.” BioEssays 28(8): 822–33.
Dever, Thomas E. 2002. “Gene-Specific Regulation by General Translation Factors.” Cell 108(4): 545–56.
Dieci, Giorgio et al. 2009. “Positive Modulation of RNA Polymerase III Transcription by Ribosomal Proteins.” Biochemical and Biophysical Research Communications 379(2): 489–93. http://dx.doi.org/10.1016/j.bbrc.2008.12.097.
Elvira, George et al. 2006. “Characterization of an RNA Granule from Developing Brain.” Molecular & Cellular Proteomics 5(4): 635–51. http://www.mcponline.org/lookup/doi/10.1074/mcp.M500255-MCP200.
Gabb, H A, R MJackson, &M J ESternberg. 1997. “Modelling Protein Docking Using Shape Complimentarity, Electrostatics and Biochemical Information.” J. Mol. Biol. 272: 106–20.
Gebauer, Fátima, &Matthias W.Hentze. 2004. “Molecular Mechanisms of Translational Control.” Nature Reviews Molecular Cell Biology 5(10): 827–35.
Guseva, Elizaveta, Ronald N.Zuckermann, &Ken A.Dill. 2017. “Foldamer Hypothesis for the Growth and Sequence Differentiation of Prebiotic Polymers.” Proceedings of the National Academy of Sciences 114(36): E7460–68. http://www.pnas.org/lookup/doi/10.1073/pnas.1620179114.
Holt, Christine E, &Simon LBullock. 2013. “Europe PMC Funders Group Subcellular mRNA Localization in Animal Cells and Why It Matters Mechanisms of mRNA Localization : Illuminating a Multi-Step Process.” 326(5957): 1212–16.
Iii, Billy R Miller et al. 2012. “MMPBSA . Py : An Efficient Program for End-State Free Energy Calculations.”
Isken, Olaf, &Lynne E.Maquat. 2008. “The Multiple Lives of NMD Factors: Balancing Roles in Gene and Genome Regulation.” Nature Reviews Genetics 9(9): 699–712.
Kanai, Yoshimitsu, NaoshiDohmae, &NobutakaHirokawa. 2004. “Kinesin Transports RNA: Isolation and Characterization of an RNA-Transporting Granule.” Neuron 43(4): 513–25.
Kuo, Pan Hsien et al. 2009. “Structural Insights into TDP-43 in Nucleic-Acid Binding and Domain Interactions.” Nucleic Acids Research 37(6): 1799–1808.
Kuo, Pan Hsien et al. 2014. “The Crystal Structure of TDP-43 RRM1-DNA Complex Reveals the Specific Recognition for UG- and TG-Rich Nucleic Acids.” Nucleic Acids Research 42(7): 4712–22.
Lalmansingh, Avin S., Craig J.Urekar, &Prabhakara P.Reddi. 2011. “TDP-43 Is a Transcriptional Repressor: The Testis-Specific Mouse acrv1 Gene Is a TDP-43 Target in Vivo.” Journal of Biological Chemistry 286(13): 10970–82.
Lareau, Liana F. et al. 2007. “Unproductive Splicing of SR Genes Associated with Highly Conserved and Ultraconserved DNA Elements.” Nature 446(7138): 926–29.
Li, Hongchun, ShunSakuraba, AravindChandrasekaran, &Lee WeiYang. 2014. “Molecular Binding Sites Are Located near the Interface of Intrinsic Dynamics Domains (IDDs).” Journal of Chemical Information and Modeling 54(8): 2275–85.
Lukong, Kiven E., Kai-weiChang, Edouard W.Khandjian, &StéphaneRichard. 2008. “RNA-Binding Proteins in Human Genetic Disease.” Trends in Genetics 24(8): 416–25. http://linkinghub.elsevier.com/retrieve/pii/S016895250800173X.
Lunde, B M, CMoore, &GVarani. 2007. “RNA-Binding Proteins: Modular Design for Efficient Function.” Nature reviews. Molecular cell biology 8(6): 479–90. http://www.ncbi.nlm.nih.gov/pubmed/17473849.
Mackness, Brian C. et al. 2014. “Folding of the RNA Recognition Motif (RRM) Domains of the Amyotrophic Lateral Sclerosis (ALS)-Linked Protein TDP-43 Reveals an Intermediate State.” Journal of Biological Chemistry 289(12): 8264–76.
Miao, Yinglong, Victoria A.Feher, &J. AndrewMcCammon. 2015. “Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation.” Journal of Chemical Theory and Computation 11(8): 3584–95.
Reed, Robin, &EdHurt. 2002. “A Conserved mRNA Export Machinery Coupled to Pre-mRNA Splicing.” Cell 108(4): 523–31.
Sengoku, Toru et al. 2006. “Structural Basis for RNA Unwinding by the DEAD-Box Protein Drosophila Vasa.” Cell 125(2): 287–300.
Sephton, Chantelle F. et al. 2011. “Identification of Neuronal RNA Targets of TDP-43-Containing Ribonucleoprotein Complexes.” Journal of Biological Chemistry 286(2): 1204–15.
Steimer, Lenz, &DagmarKlostermeier. 2012. “RNA Helicases in Infection and Disease.” RNA Biology 9(6): 751–71.
Universit, Angela Re, &AngelaRe. 2014. “RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods.” 1097(March 2014). http://link.springer.com/10.1007/978-1-62703-709-9.
Wan, Fengyi et al. 2007. “Ribosomal Protein S3: A KH Domain Subunit in NF-κB Complexes That Mediates Selective Gene Regulation.” Cell 131(5): 927–39.
Wang, I-Fan, Lien-SzuWu, &C-K. JamesShen. 2008. “TDP-43: An Emerging New Player in Neurodegenerative Diseases.” Trends in Molecular Medicine 14(11): 479–85. http://linkinghub.elsevier.com/retrieve/pii/S147149140800186X.
Ye, Yuzhen, &AdamGodzik. 2003. “Flexible Structure Alignment by Chaining Aligned Fragment Pairs Allowing Twists.” 19.

 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
* *