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蛋白质结构预测

邓海游 贾亚 张阳

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蛋白质结构预测

邓海游, 贾亚, 张阳

Protein structure prediction

Deng Hai-You, Jia Ya, Zhang Yang
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  • 从氨基酸序列出发预测蛋白质的三维结构是目前计算生物学和生物物理学领域最具挑战性和影响力的研究方向之一. 本文从结构预测的研究背景出发,简要介绍了它的理论意义、应用需求及基本现状;并根据结构预测的一般步骤,依次介绍了构象初始化、构象搜索、结构筛选、全原子结构重建、结构优化等基本预测过程;随后分基于模板和无模板两类,各列举了几种具有代表性的结构预测方法;最后对该领域的盛事国际蛋白质结构预测技术评估大赛(CASP)做了简单介绍.
    Predicting 3D structure of proteins from the amino acid sequences is one of the most important unsolved problems in computational biology and biophysics. This review article attempts to introduce the most recent effort and progress on this problem. After a brief introduction of the background and basic concepts involved in protein structure prediction, we went through the specific steps that have been taken by most typical structural modeling approaches, including fold recognition, model initialization, conformational search, model selection, and atomic-level structure refinement. Several representative structure prediction methods were introduced in detail, including those from both template-based modeling and ab initio folding approaches. Finally, we overview the results shown in the community-wide Critical Assessment of protein Structure Prediction (CASP) experiments that have been developed for benchmarking the state of the art of the field.
      通信作者: 张阳, zhng@umich.edu
    • 基金项目: 国家自然科学基金(批准号:11547255,11474117)、中央高校基本科研业务费专项资金(批准号:2662015BQ045)和美国国立卫生研究院(批准号:GM083107,GM116960)资助的课题.
      Corresponding author: Zhang Yang, zhng@umich.edu
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 11547255, 11474117), the Fundamental Research Funds for the Central Universities, China (Grant No. 2662015BQ045) and the National Institute of General Medical Sciences (GM083107, GM116960).
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  • [1]

    Kolata G 1986 Science 233 1037

    [2]

    Consortium U 2015 Nucleic Acids Res. 43 D204

    [3]

    Berman H M, Westbrook J, Feng Z, Gilliland G, Bhat T N, Weissig H, Shindyalov I N, Bourne P E 2000 Nucleic Acids Res. 28 235

    [4]

    Anfinsen C B 1973 Science 181 223

    [5]

    Bowie J U, Luthy R, Eisenberg D 1991 Science 253 164

    [6]

    Jones D, Thornton J 1993 J. Comput. Aided Mol. Des. 7 439

    [7]

    Jones D T, Taylor W R, Thornton J M 1992 Nature 358 86

    [8]

    Jones D T 1999 J. Mol. Biol. 287 797

    [9]

    Chothia C 1992 Nature. 357 543

    [10]

    Zhang Y, Skolnick J 2005 Nucleic Acids Res. 33 2302

    [11]

    Huang Y J P, Mao B C, Aramini J M, Montelione G T 2014 Proteins 82 43

    [12]

    Tai C H, Bai H J, Taylor T J, Lee B 2014 Proteins 82 57

    [13]

    Moult J 2005 Curr. Opin. Struct. Biol. 15 285

    [14]

    Kryshtafovych A, Fidelis K, Moult J 2010 Introduction to Protein Structure Prediction: Methods and Algorithms (Hoboken: John Wiley Sons, Inc.) pp15-32

    [15]

    Needleman S B, Wunsch C D 1970 J. Mol. Biol. 48 443

    [16]

    Smith T F, Waterman M S 1981 J. Mol. Biol. 147 195

    [17]

    Altschul S F, Madden T L, Schffer A A, Zhang J, Zhang Z, Miller W, Lipman D J 1997 Nucleic Acids Res. 25 3389

    [18]

    Rohl C A, Strauss C E, Misura K M, Baker D 2004 Methods Enzymol. 383 66

    [19]

    Xu D, Zhang Y 2012 Proteins 80 1715

    [20]

    Dill K A, MacCallum J L 2012 Science 338 1042

    [21]

    Pearlman D A, Case D A, Caldwell J W, Ross W S, Iii T E C, Debolt S, Ferguson D, Seibel G, Kollman P 1995 Comput. Phys. Commun. 91 1

    [22]

    Brooks B R, Bruccoleri R E, Olafson B D, States D J, Swaminathan S, Karplus M 1983 J. Comput. Chem. 4 187

    [23]

    Tanaka S, Scheraga H A 1976 Macromolecules. 9 945

    [24]

    Miyazawa S, Jernigan R L 1984 Macromolecules. 18 534

    [25]

    Sippl M J 1990 J. Mol. Biol. 213 859

    [26]

    Samudrala R, Moult J 1998 J. Mol. Biol. 275 895

    [27]

    Lu H, Skolnick J 2001 Proteins. 44 223

    [28]

    Zhou H, Zhou Y 2002 Protein Sci. 11 2714

    [29]

    Rykunov D, Fiser A 2010 BMC Bioinformatics 11 1

    [30]

    Deng H, Jia Y, Wei Y, Zhang Y 2012 Proteins 80 2311

    [31]

    Van Gunsteren W F, Bakowies D, Baron R, Chandrasekhar I, Christen M, Daura X, Gee P, Geerke D P, Gltli A, Hnenberger P H 2006 Angew. Chem. Int. Edit 45 4064

    [32]

    Sugita Y, Okamoto Y 1999 Chem. Phys. Lett. 314 141

    [33]

    Hansmann U H E, Okamoto Y 1999 Curr. Opin. Struct. Biol. 9 177

    [34]

    Li Z, Scheraga H A 1987 Proc. Natl. Acad. Sci. 84 6611

    [35]

    Kirkpatrick S C, Gelatt C D, Vecchi M P 1983 Science. 220 671

    [36]

    Swendsen R H, Wang J S 1986 Phys. Rev. Lett. 57 2607

    [37]

    Kihara D, Lu H, Kolinski A, Skolnick J 2001 Proc. Natl. Acad. Sci. 98 10125

    [38]

    Kryshtafovych A, Barbato A, Fidelis K, Monastyrskyy B, Schwede T, Tramontano A 2014 Proteins. 82 112

    [39]

    Samudrala R, Levitt M 2000 Protein Sci. 9 1399

    [40]

    Tsai J, Bonneau R, Morozov A V, Kuhlman B, Rohl C A, Baker D 2003 Proteins. 53 76

    [41]

    Deng H, Jia Y, Zhang Y 2016 Bioinformatics. 32 378

    [42]

    Shortle D, Simons K T, Baker D 1998 Proc. Natl. Acad. Sci. 95 11158

    [43]

    Zhang Y, Skolnick J 2004 J. Comput. Chem. 25 865

    [44]

    Kozakov D, Clodfelter K H, Vajda S, Camacho C J 2005 Biophys. J. 89 867

    [45]

    Maupetit J, Gautier R, Tuffery P 2006 Nucleic Acids Res. 34 W147

    [46]

    Gront D, Kmiecik S, Kolinski A 2007 J. Comput. Chem. 28 1593

    [47]

    Rotkiewicz P, Skolnick J 2008 J. Comput. Chem. 29 1460

    [48]

    Li Y Q, Zhang Y 2009 Proteins. 76 665

    [49]

    Dunbrack R L, Karplus M 1993 J. Mol. Biol. 230 543

    [50]

    Krivov G G, Shapovalov M V, Dunbrack R L 2009 Proteins. 77778

    [51]

    Canutescu A A, Shelenkov A A, Dunbrack R L 2003 Protein Sci. 12 2001

    [52]

    Xu J 2005 Research in computational molecular biology Cambridge May 14-18 423

    [53]

    Miao Z, Cao Y, Jiang T 2011 Bioinformatics. 27 3117

    [54]

    Wu S, Skolnick J, Zhang Y 2007 BMC Biol. 5 17

    [55]

    Xu D, Zhang Y 2011 Biophys. J. 101 2525

    [56]

    Zhang J, Liang Y, Zhang Y 2011 Structure. 19 1784

    [57]

    MacCallum J L, Prez A, Schnieders M J, Hua L, Jacobson M P, Dill K A 2011 Proteins 79 74

    [58]

    Nugent T, Cozzetto D, Jones D T 2014 Proteins. 82 98

    [59]

    Modi V, Xu Q, Sam A, Roland L, Dunbrack J 2016 Proteins. 0 00

    [60]

    Moult J, Fidelis K, Kryshtafovych A, Schwede T, Tramontano A 2014 Proteins. 82 1

    [61]

    Moult J, Fidelis K, Kryshtafovych A, Schwede T, Tramontano A 2016 Proteins 0

    [62]

    Guex N, Peitsch M C 1997 Electrophoresis. 18 2714

    [63]

    Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, Kiefer F, Cassarino T G, Bertoni M, Bordoli L 2014 Nucleic Acids Res. 42 252

    [64]

    Altschul S F, Madden T L, Schffer A A, Zhang J, Zhang Z, Miller W, Lipman D J 1997 Nucleic Acids Res. 25 3389

    [65]

    Remmert M, Biegert A, Hauser A, Sding J 2011 Nature Methods. 9 173

    [66]

    Benkert P, Knzli M, Schwede T 2009 Nucleic Acids Res. 37 W510

    [67]

    Haas J, Roth S, Arnold K, Kiefer F, Schmidt T, Bordoli L, Schwede T 2013 Databsae Oxford. 2013 bat031

    [68]

    Sali A, Blundell T L 1993 J. Mol. Biol. 234 779

    [69]

    Fiser A, Do R K, Sali A 2000 Protein Sci. 9 1753

    [70]

    Shen M y, Sali A 2006 Protein Sci. 15 2507

    [71]

    Kuntal B K, Aparoy P, Reddanna P 2009 BMC Res. Notes. 3 1

    [72]

    Roy A, Kucukural A, Zhang Y 2010 Nat. Protoc. 5 725

    [73]

    Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y 2014 Nature Methods. 12 127

    [74]

    Wu S, Zhang Y 2007 Nucleic Acids Res. 35 3375

    [75]

    Simons K T, Kooperberg C, Huang E, Baker D 1997 J. Mol. Biol. 268 209

    [76]

    Cheng J, Randall A Z, Sweredoski M J, Baldi P 2005 Nucleic Acids Res. 33 72

    [77]

    Lee J, Kim S Y, Joo K, Kim I, Lee J 2004 Proteins. 56 704

    [78]

    Jones, David T 2001 Proteins. Suppl 5 127

    [79]

    Kryshtafovych A, Monastyrskyy B, Fidelis K 2014 Proteins. 82 7

    [80]

    Monastyrskyy B, D'Andrea D, Fidelis K, Tramontano A, Kryshtafovych A 2014 Proteins. 82 138

    [81]

    Monastyrskyy B, Kryshtafovych A, Moult J, Tramontano A, Fidelis K 2014 Proteins. 82 127

    [82]

    Zhang Y 2009 Curr. Opin. Struct. Biol. 19 145

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出版历程
  • 收稿日期:  2016-06-22
  • 修回日期:  2016-07-21
  • 刊出日期:  2016-09-05

蛋白质结构预测

  • 1. 华中农业大学理学院, 武汉 430070;
  • 2. 华中师范大学物理科学与技术学院, 武汉 430079;
  • 3. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 45108, USA
  • 通信作者: 张阳, zhng@umich.edu
    基金项目: 国家自然科学基金(批准号:11547255,11474117)、中央高校基本科研业务费专项资金(批准号:2662015BQ045)和美国国立卫生研究院(批准号:GM083107,GM116960)资助的课题.

摘要: 从氨基酸序列出发预测蛋白质的三维结构是目前计算生物学和生物物理学领域最具挑战性和影响力的研究方向之一. 本文从结构预测的研究背景出发,简要介绍了它的理论意义、应用需求及基本现状;并根据结构预测的一般步骤,依次介绍了构象初始化、构象搜索、结构筛选、全原子结构重建、结构优化等基本预测过程;随后分基于模板和无模板两类,各列举了几种具有代表性的结构预测方法;最后对该领域的盛事国际蛋白质结构预测技术评估大赛(CASP)做了简单介绍.

English Abstract

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