1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Biochemistry
  4. Volume 88, 2019
  5. Article

Annual Review of Biochemistry

Volume 88, 2019

Integrative Structure Modeling: Overview and Assessment

Abstract

Integrative structure modeling computationally combines data from multiple sources of information with the aim of obtaining structural insights that are not revealed by any single approach alone. In the first part of this review, we survey the commonly used sources of structural information and the computational aspects of model building. Throughout the past decade, integrative modeling was applied to various biological systems, with a focus on large protein complexes. Recent progress in the field of cryo–electron microscopy (cryo-EM) has resolved many of these complexes to near-atomic resolution. In the second part of this review, we compare a range of published integrative models with their higher-resolution counterparts with the aim of critically assessing their accuracy. This comparison gives a favorable view of integrative modeling and demonstrates its ability to yield accurate and informative results. We discuss possible roles of integrative modeling in the new era of cryo-EM and highlight future challenges and directions.

Keyword(s): cross-linking, cryo-EM, cryo–electron microscopy, integrative modeling, macromolecular assemblies, mass spectrometry, protein structure
Loading

Article metrics loading...

/content/journals/10.1146/annurev-biochem-013118-111429
2019-06-20
2024-04-25
Loading full text...

Full text loading...

/deliver/fulltext/biochem/88/1/annurev-biochem-013118-111429.html?itemId=/content/journals/10.1146/annurev-biochem-013118-111429&mimeType=html&fmt=ahah

Literature Cited

  1. 1. 
    Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN et al. 2000. The Protein Data Bank. Nucleic Acids Res 28:235–42
     [Google Scholar]
  2. 2. 
    Kühlbrandt W. 2014. The resolution revolution. Science 343:1443–44
     [Google Scholar]
  3. 3. 
    Rappsilber J. 2011. The beginning of a beautiful friendship: cross-linking/mass spectrometry and modelling of proteins and multi-protein complexes. J. Struct. Biol. 173:530–40
     [Google Scholar]
  4. 4. 
    Kochert BA, Iacob RE, Wales TE, Makriyannis A, Engen JR 2018. Hydrogen-deuterium exchange mass spectrometry to study protein complexes. Methods Mol. Biol. 1764:153–71
     [Google Scholar]
  5. 5. 
    Petoukhov MV, Svergun DI. 2013. Applications of small-angle X-ray scattering to biomacromolecular solutions. Int. J. Biochem. Cell Biol. 45:429–37
     [Google Scholar]
  6. 6. 
    Jares-Erijman EA, Jovin TM. 2003. FRET imaging. Nat. Biotechnol. 21:1387–95
     [Google Scholar]
  7. 7. 
    Marks DS, Colwell LJ, Sheridan R, Hopf TA, Pagnani A et al. 2011. Protein 3D structure computed from evolutionary sequence variation. PLOS ONE 6:e28766
     [Google Scholar]
  8. 8. 
    Alber F, Dokudovskaya S, Veenhoff LM, Zhang W, Kipper J et al. 2007. Determining the architectures of macromolecular assemblies. Nature 450:683–94
     [Google Scholar]
  9. 9. 
    Robinson CV, Sali A, Baumeister W 2007. The molecular sociology of the cell. Nature 450:973–82
     [Google Scholar]
  10. 10. 
    Russel D, Lasker K, Webb B, Velazquez-Muriel J, Tjioe E et al. 2012. Putting the pieces together: integrative modeling platform software for structure determination of macromolecular assemblies. PLOS Biol 10:e1001244
     [Google Scholar]
  11. 11. 
    Sali A, Blundell TL. 1993. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol. 234:779–815
     [Google Scholar]
  12. 12. 
    Dunbrack RL Jr 2006. Sequence comparison and protein structure prediction. Curr. Opin. Struct. Biol. 16:374–84
     [Google Scholar]
  13. 13. 
    Bienert S, Waterhouse A, de Beer TA, Tauriello G, Studer G et al. 2017. The SWISS-MODEL Repository—new features and functionality. Nucleic Acids Res 45:D313–19
     [Google Scholar]
  14. 14. 
    Khafizov K, Madrid-Aliste C, Almo SC, Fiser A 2014. Trends in structural coverage of the protein universe and the impact of the Protein Structure Initiative. PNAS 111:3733–38
     [Google Scholar]
  15. 15. 
    Ovchinnikov S, Park H, Varghese N, Huang P-S, Pavlopoulos GA et al. 2017. Protein structure determination using metagenome sequence data. Science 355:294–98
     [Google Scholar]
  16. 16. 
    Fernandez-Leiro R, Scheres SH. 2016. Unravelling biological macromolecules with cryo-electron microscopy. Nature 537:339–46
     [Google Scholar]
  17. 17. 
    Lawson CL, Patwardhan A, Baker ML, Hryc C, Garcia ES et al. 2016. EMDataBank unified data resource for 3DEM. Nucleic Acids Res 44:D396–403
     [Google Scholar]
  18. 18. 
    Scheres SH. 2012. RELION: implementation of a Bayesian approach to cryo-EM structure determination. J. Struct. Biol. 180:519–30
     [Google Scholar]
  19. 19. 
    Punjani A, Rubinstein JL, Fleet DJ, Brubaker MA 2017. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14:290–96
     [Google Scholar]
  20. 20. 
    Li X, Mooney P, Zheng S, Booth CR, Braunfeld MB et al. 2013. Electron counting and beam-induced motion correction enable near-atomic-resolution single-particle cryo-EM. Nat. Methods 10:584–90
     [Google Scholar]
  21. 21. 
    Patwardhan A. 2017. Trends in the Electron Microscopy Data Bank (EMDB). Acta Crystallogr. Sect. D 73:503–8
     [Google Scholar]
  22. 22. 
    Alber F, Dokudovskaya S, Veenhoff LM, Zhang W, Kipper J et al. 2007. The molecular architecture of the nuclear pore complex. Nature 450:695–701
     [Google Scholar]
  23. 23. 
    Patla I, Volberg T, Elad N, Hirschfeld-Warneken V, Grashoff C et al. 2010. Dissecting the molecular architecture of integrin adhesion sites by cryo-electron tomography. Nat. Cell Biol. 12:909–15
     [Google Scholar]
  24. 24. 
    Wu S, Avila-Sakar A, Kim J, Booth DS, Greenberg CH et al. 2012. Fabs enable single particle cryoEM studies of small proteins. Structure 20:582–92
     [Google Scholar]
  25. 25. 
    Velázquez-Muriel J, Lasker K, Russel D, Phillips J, Webb BM et al. 2012. Assembly of macromolecular complexes by satisfaction of spatial restraints from electron microscopy images. PNAS 109:18821–26
     [Google Scholar]
  26. 26. 
    Schneidman-Duhovny D, Rossi A, Avila-Sakar A, Kim SJ, Velazquez-Muriel J et al. 2012. A method for integrative structure determination of protein-protein complexes. Bioinformatics 28:3282–89
     [Google Scholar]
  27. 27. 
    Shi Y, Fernandez-Martinez J, Tjioe E, Pellarin R, Kim SJ et al. 2014. Structural characterization by cross-linking reveals the detailed architecture of a coatomer-related heptameric module from the nuclear pore complex. Mol. Cell. Proteom. 13:2927–43
     [Google Scholar]
  28. 28. 
    Sinz A. 2014. The advancement of chemical cross-linking and mass spectrometry for structural proteomics: from single proteins to protein interaction networks. Expert Rev. Proteom. 11:733–43
     [Google Scholar]
  29. 29. 
    Leitner A, Faini M, Stengel F, Aebersold R 2016. Crosslinking and mass spectrometry: an integrated technology to understand the structure and function of molecular machines. Trends Biochem. Sci. 41:20–32
     [Google Scholar]
  30. 30. 
    Leitner A, Joachimiak LA, Unverdorben P, Walzthoeni T, Frydman J et al. 2014. Chemical cross-linking/mass spectrometry targeting acidic residues in proteins and protein complexes. PNAS 111:9455–60
     [Google Scholar]
  31. 31. 
    Greber BJ, Bieri P, Leibundgut M, Leitner A, Aebersold R et al. 2015. The complete structure of the 55S mammalian mitochondrial ribosome. Science 348:303–8
     [Google Scholar]
  32. 32. 
    Robinson PJ, Trnka MJ, Bushnell DA, Davis RE, Mattei PJ et al. 2016. Structure of a complete Mediator-RNA polymerase II pre-initiation complex. Cell 166:1411–22.e16
     [Google Scholar]
  33. 33. 
    Wu X, Chavez JD, Schweppe DK, Zheng C, Weisbrod CR et al. 2016. In vivo protein interaction network analysis reveals porin-localized antibiotic inactivation in Acinetobacterbaumannii strain AB5075. Nat. Commun. 7:13414
     [Google Scholar]
  34. 34. 
    Schweppe DK, Chavez JD, Lee CF, Caudal A, Kruse SE et al. 2017. Mitochondrial protein interactome elucidated by chemical cross-linking mass spectrometry. PNAS 114:1732–37
     [Google Scholar]
  35. 35. 
    Debelyy MO, Waridel P, Quadroni M, Schneiter R, Conzelmann A 2017. Chemical crosslinking and mass spectrometry to elucidate the topology of integral membrane proteins. PLOS ONE 12:e0186840
     [Google Scholar]
  36. 36. 
    Molnar KS, Bonomi M, Pellarin R, Clinthorne GD, Gonzalez G et al. 2014. Cys-scanning disulfide crosslinking and Bayesian modeling probe the transmembrane signaling mechanism of the histidine kinase, PhoQ. Structure 22:1239–51
     [Google Scholar]
  37. 37. 
    Street TO, Zeng X, Pellarin R, Bonomi M, Sali A et al. 2014. Elucidating the mechanism of substrate recognition by the bacterial Hsp90 molecular chaperone. J. Mol. Biol. 426:2393–404
     [Google Scholar]
  38. 38. 
    Walzthoeni T, Joachimiak LA, Rosenberger G, Rost HL, Malmstrom L et al. 2015. xTract: software for characterizing conformational changes of protein complexes by quantitative cross-linking mass spectrometry. Nat. Methods 12:1185–90
     [Google Scholar]
  39. 39. 
    Yu C, Mao H, Novitsky EJ, Tang X, Rychnovsky SD et al. 2015. Gln40 deamidation blocks structural reconfiguration and activation of SCF ubiquitin ligase complex by Nedd8. Nat. Commun. 6:10053
     [Google Scholar]
  40. 40. 
    Slavin M, Kalisman N. 2018. Structural analysis of protein complexes by cross-linking and mass spectrometry. Methods Mol. Biol. 1764:173–83
     [Google Scholar]
  41. 41. 
    Putnam CD, Hammel M, Hura GL, Tainer JA 2007. X-ray solution scattering (SAXS) combined with crystallography and computation: defining accurate macromolecular structures, conformations and assemblies in solution. Q. Rev. Biophys. 40:191–285
     [Google Scholar]
  42. 42. 
    Hura GL, Menon AL, Hammel M, Rambo RP, Poole FL 2nd et al. 2009. Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS). Nat. Methods 6:606–12
     [Google Scholar]
  43. 43. 
    Tiede DM, Mardis KL, Zuo X 2009. X-ray scattering combined with coordinate-based analyses for applications in natural and artificial photosynthesis. Photosynth. Res. 102:267–79
     [Google Scholar]
  44. 44. 
    Whitten AE, Trewhella J. 2009. Small-angle scattering and neutron contrast variation for studying bio-molecular complexes. Methods Mol. Biol. 544:307–23
     [Google Scholar]
  45. 45. 
    Rambo RP, Tainer JA. 2013. Accurate assessment of mass, models and resolution by small-angle scattering. Nature 496:477–81
     [Google Scholar]
  46. 46. 
    Rambo RP, Tainer JA. 2013. Super-resolution in solution X-ray scattering and its applications to structural systems biology. Annu. Rev. Biophys. 42:415–41
     [Google Scholar]
  47. 47. 
    Trewhella J. 2016. Small-angle scattering and 3D structure interpretation. Curr. Opin. Struct. Biol. 40:1–7
     [Google Scholar]
  48. 48. 
    Bernado P, Mylonas E, Petoukhov MV, Blackledge M, Svergun DI 2007. Structural characterization of flexible proteins using small-angle X-ray scattering. J. Am. Chem. Soc. 129:5656–64
     [Google Scholar]
  49. 49. 
    Rambo RP, Tainer JA. 2011. Characterizing flexible and intrinsically unstructured biological macromolecules by SAS using the Porod-Debye law. Biopolymers 95:559–71
     [Google Scholar]
  50. 50. 
    Hura GL, Budworth H, Dyer KN, Rambo RP, Hammel M et al. 2013. Comprehensive macromolecular conformations mapped by quantitative SAXS analyses. Nat. Methods 10:453–54
     [Google Scholar]
  51. 51. 
    Pelikan M, Hura GL, Hammel M 2009. Structure and flexibility within proteins as identified through small angle X-ray scattering. Gen. Physiol. Biophys. 28:174–89
     [Google Scholar]
  52. 52. 
    Schneidman-Duhovny D, Hammel M, Tainer JA, Sali A 2016. FoXS, FoXSDock and MultiFoXS: single-state and multi-state structural modeling of proteins and their complexes based on SAXS profiles. Nucleic Acids Res 44:W424–29
     [Google Scholar]
  53. 53. 
    Koboldt DC, Steinberg KM, Larson DE, Wilson RK, Mardis ER 2013. The next-generation sequencing revolution and its impact on genomics. Cell 155:27–38
     [Google Scholar]
  54. 54. 
    Glaser F, Pupko T, Paz I, Bell RE, Bechor-Shental D et al. 2003. ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information. Bioinformatics 19:163–64
     [Google Scholar]
  55. 55. 
    Marks DS, Hopf TA, Sander C 2012. Protein structure prediction from sequence variation. Nat. Biotechnol. 30:1072–80
     [Google Scholar]
  56. 56. 
    Hopf TA, Colwell LJ, Sheridan R, Rost B, Sander C, Marks DS 2012. Three-dimensional structures of membrane proteins from genomic sequencing. Cell 149:1607–21
     [Google Scholar]
  57. 57. 
    Wang S, Sun S, Li Z, Zhang R, Xu J 2017. Accurate de novo prediction of protein contact map by ultra-deep learning model. PLOS Comput. Biol. 13:e1005324
     [Google Scholar]
  58. 58. 
    Hopf TA, Scharfe CP, Rodrigues JP, Green AG, Kohlbacher O et al. 2014. Sequence co-evolution gives 3D contacts and structures of protein complexes. eLife 3:e03430
     [Google Scholar]
  59. 59. 
    Hopf TA, Marks DS. 2017. Protein structures, interactions and function from evolutionary couplings. From Protein Structure to Function with Bioinformatics DJ Rigden 37–58 Dordrecht, Neth: Springer. , 2nd ed..
     [Google Scholar]
  60. 60. 
    Selvin PR. 2000. The renaissance of fluorescence resonance energy transfer. Nat. Struct. Biol. 7:730–34
     [Google Scholar]
  61. 61. 
    Forster T. 1948. Intermolecular energy transfer and fluorescence. Ann. Phys. 2:55–75
     [Google Scholar]
  62. 62. 
    Brunger AT, Strop P, Vrljic M, Chu S, Weninger KR 2011. Three-dimensional molecular modeling with single molecule FRET. J. Struct. Biol. 173:497–505
     [Google Scholar]
  63. 63. 
    Bonomi M, Pellarin R, Kim SJ, Russel D, Sundin BA et al. 2014. Determining protein complex structures based on a Bayesian model of in vivo Förster resonance energy transfer (FRET) data. Mol. Cell. Proteom. 13:2812–23
     [Google Scholar]
  64. 64. 
    Lerner E, Cordes T, Ingargiola A, Alhadid Y, Chung S et al. 2018. Toward dynamic structural biology: Two decades of single-molecule Förster resonance energy transfer. Science 359:eaan1133
     [Google Scholar]
  65. 65. 
    Gray JJ, Moughon S, Wang C, Schueler-Furman O, Kuhlman B et al. 2003. Protein–protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. J. Mol. Biol. 331:281–99
     [Google Scholar]
  66. 66. 
    Katchalski-Katzir E, Shariv I, Eisenstein M, Friesem AA, Aflalo C, Vakser IA 1992. Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques. PNAS 89:2195–99
     [Google Scholar]
  67. 67. 
    Ritchie DW, Kemp GJ. 2000. Protein docking using spherical polar Fourier correlations. Proteins 39:178–94
     [Google Scholar]
  68. 68. 
    Moal IH, Moretti R, Baker D, Fernandez-Recio J 2013. Scoring functions for protein–protein interactions. Curr. Opin. Struct. Biol. 23:862–67
     [Google Scholar]
  69. 69. 
    Dong GQ, Fan H, Schneidman-Duhovny D, Webb B, Sali A 2013. Optimized atomic statistical potentials: assessment of protein interfaces and loops. Bioinformatics 29:3158–66
     [Google Scholar]
  70. 70. 
    Lasker K, Phillips JL, Russel D, Velazquez-Muriel J, Schneidman-Duhovny D et al. 2010. Integrative structure modeling of macromolecular assemblies from proteomics data. Mol. Cell. Proteom. 9:1689–702
     [Google Scholar]
  71. 71. 
    Kalisman N, Adams CM, Levitt M 2012. Subunit order of eukaryotic TRiC/CCT chaperonin by cross-linking, mass spectrometry, and combinatorial homology modeling. PNAS 109:2884–89
     [Google Scholar]
  72. 72. 
    Belsom A, Schneider M, Fischer L, Brock O, Rappsilber J 2016. Serum albumin domain structures in human blood serum by mass spectrometry and computational biology. Mol. Cell. Proteom. 15:1105–16
     [Google Scholar]
  73. 73. 
    Rieping W, Habeck M, Nilges M 2005. Inferential structure determination. Science 309:303–6
     [Google Scholar]
  74. 74. 
    Chacon P, Wriggers W. 2002. Multi-resolution contour-based fitting of macromolecular structures. J. Mol. Biol. 317:375–84
     [Google Scholar]
  75. 75. 
    Garzon JI, Kovacs J, Abagyan R, Chacon P 2007. ADP_EM: fast exhaustive multi-resolution docking for high-throughput coverage. Bioinformatics 23:427–33
     [Google Scholar]
  76. 76. 
    Svergun D, Barberato C, Koch MHJ 1995. CRYSOL—a program to evaluate X-ray solution scattering of biological macromolecules from atomic coordinates. J. Appl. Crystallogr. 28:768–73
     [Google Scholar]
  77. 77. 
    Schneidman-Duhovny D, Hammel M, Sali A 2010. FoXS: a web server for rapid computation and fitting of SAXS profiles. Nucleic Acids Res 38:SupplW540–44
     [Google Scholar]
  78. 78. 
    Schneidman-Duhovny D, Kim SJ, Sali A 2012. Integrative structural modeling with small angle X-ray scattering profiles. BMC Struct. Biol. 12:17
     [Google Scholar]
  79. 79. 
    Schneidman-Duhovny D, Hammel M, Tainer JA, Sali A 2013. Accurate SAXS profile computation and its assessment by contrast variation experiments. Biophys. J. 105:962–74
     [Google Scholar]
  80. 80. 
    Viswanath S, Chemmama IE, Cimermancic P, Sali A 2017. Assessing exhaustiveness of stochastic sampling for integrative modeling of macromolecular structures. Biophys. J. 113:2344–53
     [Google Scholar]
  81. 81. 
    Lasker K, Topf M, Sali A, Wolfson HJ 2009. Inferential optimization for simultaneous fitting of multiple components into a cryoEM map of their assembly. J. Mol. Biol. 388:180–94
     [Google Scholar]
  82. 82. 
    Inbar Y, Benyamini H, Nussinov R, Wolfson HJ 2005. Combinatorial docking approach for structure prediction of large proteins and multi-molecular assemblies. Phys. Biol. 2:S156–65
     [Google Scholar]
  83. 83. 
    Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ 2005. Geometry-based flexible and symmetric protein docking. Proteins 60:224–31
     [Google Scholar]
  84. 84. 
    Andre I, Bradley P, Wang C, Baker D 2007. Prediction of the structure of symmetrical protein assemblies. PNAS 104:17656–61
     [Google Scholar]
  85. 85. 
    Carter L, Kim SJ, Schneidman-Duhovny D, Stohr J, Poncet-Montange G et al. 2015. Prion protein—antibody complexes characterized by chromatography-coupled small-angle X-ray scattering. Biophys. J. 109:793–805
     [Google Scholar]
  86. 86. 
    Dominguez C, Boelens R, Bonvin AM 2003. HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. J. Am. Chem. Soc. 125:1731–37
     [Google Scholar]
  87. 87. 
    Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ 2005. PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Res 33:W363–67
     [Google Scholar]
  88. 88. 
    Soding J. 2005. Protein homology detection by HMM–HMM comparison. Bioinformatics 21:951–60
     [Google Scholar]
  89. 89. 
    Simons KT, Kooperberg C, Huang E, Baker D 1997. Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. J. Mol. Biol. 268:209–25
     [Google Scholar]
  90. 90. 
    Zhang Y. 2008. I-TASSER server for protein 3D structure prediction. BMC Bioinform 9:40
     [Google Scholar]
  91. 91. 
    Orban-Nemeth Z, Beveridge R, Hollenstein DM, Rampler E, Stranzl T et al. 2018. Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data. Nat. Protoc. 13:478–94
     [Google Scholar]
  92. 92. 
    van Dijk AD, Boelens R, Bonvin AM 2005. Data-driven docking for the study of biomolecular complexes. FEBS J 272:293–312
     [Google Scholar]
  93. 93. 
    Lyskov S, Gray JJ. 2008. The RosettaDock server for local protein-protein docking. Nucleic Acids Res 36:W233–38
     [Google Scholar]
  94. 94. 
    Miled N, Yan Y, Hon WC, Perisic O, Zvelebil M et al. 2007. Mechanism of two classes of cancer mutations in the phosphoinositide 3-kinase catalytic subunit. Science 317:239–42
     [Google Scholar]
  95. 95. 
    Huang CH, Mandelker D, Schmidt-Kittler O, Samuels Y, Velculescu VE et al. 2007. The structure of a human p110α/p85α complex elucidates the effects of oncogenic PI3Kα mutations. Science 318:1744–48
     [Google Scholar]
  96. 96. 
    Letts JA, Fiedorczuk K, Sazanov LA 2016. The architecture of respiratory supercomplexes. Nature 537:644–48
     [Google Scholar]
  97. 97. 
    Dimova K, Kalkhof S, Pottratz I, Ihling C, Rodriguez-Castaneda F et al. 2009. Structural insights into the calmodulin–Munc13 interaction obtained by cross-linking and mass spectrometry. Biochemistry 48:5908–21
     [Google Scholar]
  98. 98. 
    Rodriguez-Castaneda F, Maestre-Martinez M, Coudevylle N, Dimova K, Junge H et al. 2010. Modular architecture of Munc13/calmodulin complexes: dual regulation by Ca2+ and possible function in short-term synaptic plasticity. EMBO J 29:680–91
     [Google Scholar]
  99. 99. 
    Murakami K, Elmlund H, Kalisman N, Bushnell DA, Adams CM et al. 2013. Architecture of an RNA polymerase II transcription pre-initiation complex. Science 342:1238724
     [Google Scholar]
  100. 100. 
    Schilbach S, Hantsche M, Tegunov D, Dienemann C, Wigge C et al. 2017. Structures of transcription pre-initiation complex with TFIIH and Mediator. Nature 551:204–9
     [Google Scholar]
  101. 101. 
    Leitner A, Joachimiak LA, Bracher A, Monkemeyer L, Walzthoeni T et al. 2012. The molecular architecture of the eukaryotic chaperonin TRiC/CCT. Structure 20:814–25
     [Google Scholar]
  102. 102. 
    Kalisman N, Schroder GF, Levitt M 2013. The crystal structures of the eukaryotic chaperonin CCT reveal its functional partitioning. Structure 21:540–49
     [Google Scholar]
  103. 103. 
    Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM et al. 2004. UCSF Chimera–a visualization system for exploratory research and analysis. J. Comput. Chem. 25:1605–12
     [Google Scholar]
  104. 104. 
    van Zundert GCP, Melquiond ASJ, Bonvin A 2015. Integrative modeling of biomolecular complexes: HADDOCKing with cryo-electron microscopy data. Structure 23:949–60
     [Google Scholar]
  105. 105. 
    Ciferri C, Lander GC, Maiolica A, Herzog F, Aebersold R, Nogales E 2012. Molecular architecture of human polycomb repressive complex 2. eLife 1:e00005
     [Google Scholar]
  106. 106. 
    Murakami K, Tsai KL, Kalisman N, Bushnell DA, Asturias FJ, Kornberg RD 2015. Structure of an RNA polymerase II preinitiation complex. PNAS 112:13543–48
     [Google Scholar]
  107. 107. 
    Lasker K, Forster F, Bohn S, Walzthoeni T, Villa E et al. 2012. Molecular architecture of the 26S proteasome holocomplex determined by an integrative approach. PNAS 109:1380–87
     [Google Scholar]
  108. 108. 
    Kasinath V, Faini M, Poepsel S, Reif D, Feng XA et al. 2018. Structures of human PRC2 with its cofactors AEBP2 and JARID2. Science 359:940–44
     [Google Scholar]
  109. 109. 
    Lander GC, Estrin E, Matyskiela ME, Bashore C, Nogales E, Martin A 2012. Complete subunit architecture of the proteasome regulatory particle. Nature 482:186–91
     [Google Scholar]
  110. 110. 
    Luan B, Huang X, Wu J, Mei Z, Wang Y et al. 2016. Structure of an endogenous yeast 26S proteasome reveals two major conformational states. PNAS 113:2642–47
     [Google Scholar]
  111. 111. 
    Luo J, Cimermancic P, Viswanath S, Ebmeier CC, Kim B et al. 2015. Architecture of the human and yeast general transcription and DNA repair factor TFIIH. Mol. Cell 59:794–806
     [Google Scholar]
  112. 112. 
    Greber BJ, Nguyen THD, Fang J, Afonine PV, Adams PD, Nogales E 2017. The cryo-electron microscopy structure of human transcription factor IIH. Nature 549:414–17
     [Google Scholar]
  113. 113. 
    Stuwe T, Correia AR, Lin DH, Paduch M, Lu VT et al. 2015. Architecture of the nuclear pore complex coat. Science 347:1148–52
     [Google Scholar]
  114. 114. 
    von Appen A, Kosinski J, Sparks L, Ori A, DiGuilio AL et al. 2015. In situ structural analysis of the human nuclear pore complex. Nature 526:140–43
     [Google Scholar]
  115. 115. 
    Kosinski J, Mosalaganti S, von Appen A, Teimer R, DiGuilio AL et al. 2016. Molecular architecture of the inner ring scaffold of the human nuclear pore complex. Science 352:363–65
     [Google Scholar]
  116. 116. 
    Kim SJ, Fernandez-Martinez J, Nudelman I, Shi Y, Zhang W et al. 2018. Integrative structure and functional anatomy of a nuclear pore complex. Nature 555:475–82
     [Google Scholar]
  117. 117. 
    Sali A, Berman HM, Schwede T, Trewhella J, Kleywegt G et al. 2015. Outcome of the first wwPDB Hybrid/Integrative Methods Task Force Workshop. Structure 23:1156–67
     [Google Scholar]
  118. 118. 
    Vallat B, Webb B, Westbrook JD, Sali A, Berman HM 2018. Development of a prototype system for archiving integrative/hybrid structure models of biological macromolecules. Structure 26:894–904.e2
     [Google Scholar]
  119. 119. 
    Schneider M, Belsom A, Rappsilber J 2018. Protein tertiary structure by crosslinking/mass spectrometry. Trends Biochem. Sci. 43:157–69
     [Google Scholar]
/content/journals/10.1146/annurev-biochem-013118-111429
Loading
Integrative Structure Modeling: Overview and Assessment
Annual Review of Biochemistry 88, 113 (2019); https://doi.org/10.1146/annurev-biochem-013118-111429
/content/journals/10.1146/annurev-biochem-013118-111429
/content/journals/10.1146/annurev-biochem-013118-111429
Loading

Data & Media loading...

Supplemental Material

Supplementary Data

  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error