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A Microscopic Study of Disorder-Order Transitions in Molecular Recognition of Unstructured Proteins: Hierarchy of Structural Loss and the Transition State Determination from Monte Carlo Simulations of P27KIP1 Protein Coupled Unfolding and Unbinding

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Book cover Supramolecular Structure and Function 8

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Conclusions

A microscopic characterization of the free energy barrier suggests an atomic picture of the binding mechanism that rationalizes and reconciles the hypothesized initiation binding event with the experimental data, indicating a kinetic advantage for the intrinsically unstructured α -helix in the unbound form. Despite considerable differences between individual trajectories, the analysis of independent simulations at T=600K shows a systematic trend in the hierarchy of structural loss for p 27 Kip1 during coupled unfolding and unbinding. The emerging structural polarization in the ensemble of unfolding/unbinding trajectories and in the computationally determined TSE are not determined by the folding topological preferences of p 27 Kip1, but is interpreted as a consequence of the topological requirements of the intermolecular interface to minimize free energy cost associated with ordering the β -hairpin and β -strand intermolecular contacts which are the last one to disintegrate in unfolding/unbinding and thereby could be important for nucleating rapid folding and binding. In agreement with the experimental data, it has been shown that the topology of the native intermolecular interface coupled with the localized, specific interactions formed by p 27 Kip1 with the complex in transition state overwhelms any local folding preferences for creating a stable α -helix prior to overcoming the major free energy barrier. These results provide a structural rationale for the experimental data revealing that preorganized native-like local secondary structure in p 27 Kip1 can result in slower binding. Hence, folding of unstructured proteins upon binding to a given template is largely determined by the requirements to form specific complex that ultimately dictates the folding mechanism. By using a protein engineering approach similar to the -value analysis developed to characterize the TS ensemble in protein folding, it should be possible to validate the predicted details of the binding mechanism by probing the kinetic consequences of mutations of every residue that makes appreciable interactions in the native state. Synergy of theoretical and experimental advances in the fields of protein folding and binding, based on the increasing amount of information in known structures and mechanisms may provide a fruitful direction for future research and allow to unify interdisciplinary efforts in resolving these key problems in molecular biology.

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References

  1. Wright, P.E., & Dyson, H.J., 1999, Coupling of folding and binding for unstructured proteins. J. Mol. Biol. 293: 321–331.

    Article  PubMed  CAS  Google Scholar 

  2. Dunker, A.K., Lawson, J.D., Brown, C.J., Williams, R.M., Romero, P., Oh, J.S., Oldfield, C.J., Campen, A.M., Ratliff, C.M., Hipps, K.W., Ausio, J., Nissen, M.S., Reeves, R., Kang, C., Kissinger, C,R., Bailey, R.W., Griswold, M.D., Chiu, W., Garner, E.C., & Obradovic, Z., 2001, Intrinsically disordered protein. J. Mol. Graph. Model. 19: 26–59.

    PubMed  CAS  Google Scholar 

  3. Dunker, A.K., & Obradovic, Z., 2001, The protein trinity-linking function and disorder. Nat. Biotechnol. 19: 805–806.

    Article  PubMed  CAS  Google Scholar 

  4. Dunker, A.K., Brown, C.J., & Obradovic, Z., 2002, Identification and functions of usefully disordered proteins. Adv. Protein. Chem. 62: 25–49.

    PubMed  CAS  Google Scholar 

  5. Dunker, A.K., Brown, C.J., Lawson, J.D., Iakoucheva, L.M., & Obradovic, Z., 2002, Intrinsic disorder and protein function. Biochemistry 41: 6573–6582.

    Article  PubMed  CAS  Google Scholar 

  6. Dyson, H.J., & Wright, P.E., 2002, Coupling of folding and binding for unstructured proteins. Curr. Opin. Struct. Biol. 12: 54–60.

    Article  PubMed  CAS  Google Scholar 

  7. Dyson, H.J., & Wright, P.E., 2002, Insights into the structure and dynamics of unfolded proteins from nuclear magnetic resonance. Adv. Protein Chem. 62: 311–314.

    PubMed  CAS  Google Scholar 

  8. Uversky, V.N., 2002, Natively.unfolded proteins: a point where biology waits for physics. Protein Sci. 11: 739–756.

    Article  PubMed  CAS  Google Scholar 

  9. Uversky, V.N., Gillespie, J.R., & Fink, A.L., 2000, Why are “natively unfolded” proteins unstructured under physiologic conditions. Proteins: Struct. Funct. Genet. 41: 415–427.

    CAS  Google Scholar 

  10. Uversky, V.N., 2002, What does it mean to be natively unfolded? Eur. J. Biochem. 269: 2–12.

    Article  PubMed  CAS  Google Scholar 

  11. Spolar, R.S., & Record, M.T., 1994, Coupling of local folding to sitespecific binding of proteins to DNA. Science 263: 777–784.

    PubMed  CAS  Google Scholar 

  12. Plaxco, K. W. & Gross, M. (1997) The importance of being unfolded. Nature 386: 657–659.

    Article  PubMed  CAS  Google Scholar 

  13. Kriwacki, R.W., Hengst, L., Tennant, L., Reed, S.I., & Wright, P.E., 1996, Structural studies of p21Waf1/Cip1/Sdi1 in the free and Cdk2-bound state: conformational disorder mediates binding diversity. Proc. Natl. Acad. Sci. USA 93: 11504–11509.

    Article  PubMed  CAS  Google Scholar 

  14. Hashimoto, Y,, Kohri, K., Kaneko, Y., Morisaki, H., Kato, T., Ikeda, K., & Nakanishi, M., 1998,. Critical role for the 310 helix region of p57(Kip2) in cyclin-dependent kinase 2 inhibition and growth suppression. J Biol Chem 273: 16544–16550.

    PubMed  CAS  Google Scholar 

  15. Adkins, J.N., Lumb, K., 2002, Intrinsic structural disorder and sequence features of the cell cycle inhibitor p57Kip2. Proteins: Struct. Funct. Genet. 46: 1–7.

    CAS  Google Scholar 

  16. Russo, A,A,, Jeffrey, P.D., Patten, A.K., Massague, J., & Pavletich, N.P., 1996, Crystal structure of the p27Kipl cyclin-dependent-kinase inhibitor bound to the cyclin A-Cdk2 complex. Nature 382: 325–331.

    Article  PubMed  CAS  Google Scholar 

  17. Flaugh, S.L., & Lumb, K.J., 2001, Effects of macromolecular crowding on the intrinsically disordered proteins c-Fos and p27(Kip1). Biomacromolecules 2: 538–540.

    Article  PubMed  CAS  Google Scholar 

  18. Bienkiewicz, E.A., Adkins, J.N., & Lumb, K., 2002, Functional consequences of preorganized helical structure in the intrinsically disordered cell-cycle inhibitor p27(Kip1). Biochemistry 41: 752–759.

    Article  PubMed  CAS  Google Scholar 

  19. Davis, A.M. & Teague, S.J., 1999, Hydrogen bonding, hydrophobic interactions, and failure of the rigid receptor hypothesis. Angew. Chem. Int. Ed. Engl. 39: 736–749.

    Google Scholar 

  20. Van Regenmortel, M.H., 1999, Molecular recognition in the postreductionistera. J. Mol. Recognit. 12: 1–2.

    PubMed  Google Scholar 

  21. Carlson, H.A. & McCammon J.A., 2000, Accommodating protein flexibility in computational drug design. Mol. Pharmacol. 57: 213–218.

    PubMed  CAS  Google Scholar 

  22. Ma, B., Wolfson, H.J., & Nussinov, R., 2001, Protein functional epitopes: hot spots, dynamics and combinatorial libraries. Curr. Opin. Struct. Biol. 11: 364–369.

    Article  PubMed  CAS  Google Scholar 

  23. Atwell, S., Ultsch, M., De Vos, A.M., & Wells, J.A., 1997, Structural plasticity in a remodeled protein-protein interface. Science 278: 1125–1128.

    Article  PubMed  CAS  Google Scholar 

  24. Sundberg, E.J., & Mariuzza, R.A., 2000, Luxury accommodations: the expanding role of structural plasticity in protein-protein interactions. Structure Fold. Des. 8: R137–142.

    CAS  PubMed  Google Scholar 

  25. Demchenko, A.P., 2001, Recognition between flexible protein molecules: induced and assisted folding. J. Mol. Recognit. 14: 42–61.

    Article  PubMed  CAS  Google Scholar 

  26. DeLano, W.L., Ultsch, M.H., de Vos, A.M., & Wells, J.A., 2000, Convergent solutions to binding at a protein-protein interface. Science 287: 1279–1283.

    Article  PubMed  CAS  Google Scholar 

  27. Luque, I., Leavitt, S.A., & Freire E., 2002, The linkage between protein folding and functional cooperativity: two sides of the same coin. Annu. Rev. Biophys. Biomol Struct. 31: 235–256.

    Article  PubMed  CAS  Google Scholar 

  28. Bryngelson, J. D., Onuchic, J. N., Socci, N. D. & Wolynes, P. G., 1995, Funnels, pathways, and the energy landscape of protein folding, a synthesis. Proteins: Struct. Funct. Genet.: Struct. Funct. Genet. 21: 167–195.

    CAS  Google Scholar 

  29. Dill, K. A., Bromberg, S., Yue, K., Fiebig, K.M., Yee, D.P., Thomas, P.D. & Chan, H.S., 1995, Principle of protein folding-a perspective from simple exact models. Protein Sci. 4: 561–602.

    PubMed  CAS  Google Scholar 

  30. Dill, K.A. & Chan, H.S., 1997, From Levinthal to pathways to funnels. Nat. Struct. Biol. 4: 10–19.

    Article  PubMed  CAS  Google Scholar 

  31. Onuchic, J.N., Luthey-Schulten, Z., & Wolynes, P.G., 1997, Theory of protein folding: the energy landscape perspective. Annu. Rev. Phys. Chem. 48: 545–560.

    Article  PubMed  CAS  Google Scholar 

  32. Onuchic, J.N., Nymeyer, H., Garcia, A.E., Chahine, J., & Socci, N.D., 2000, The energy landscape theory of protein folding: insights into folding mechanisms and scenarios. Adv. Protein. Chem. 53: 87–152.

    PubMed  CAS  Google Scholar 

  33. Plotkin, S.S., & Onuchic, J.N., 2002, Understanding protein folding with energy landscape theory. Part I: Basic concepts. Q. Rev. Biophys. 35: 111–167.

    PubMed  CAS  Google Scholar 

  34. Shakhnovich, E.I., 1997, Theoretical studies of protein-folding thermodynamics and kinetics. Curr. Opin. Struct. Biol. 7: 29–40.

    Article  PubMed  CAS  Google Scholar 

  35. Mirny, L., & Shakhnovich, E., 2001 Protein folding theory: from lattice to all-atom models. Annu. Rev. Biophys. Biomol. Struct. 30: 361–396.

    Article  PubMed  CAS  Google Scholar 

  36. Fersht, A.R., & Daggett, V., 2002, Protein folding and unfolding at atomic resolution Cell 108: 573–582.

    Article  PubMed  CAS  Google Scholar 

  37. Janin, J., 1996, Quantifying biological specificity: the statistical mechanics of molecular recognition. Proteins: Struct. Funct. Genet. 25: 438–445

    CAS  Google Scholar 

  38. Verkhivker, G.M. & Rejto, P.A., 1996, A mean field model of ligand-protein interactions, Implications for the structural assessment of human immunodeficiency virus type 1 protease complexes and receptor-specific binding. Proc. Natl. Acad. Sci. USA. 93: 60–64.

    Article  PubMed  CAS  Google Scholar 

  39. Rejto, P.A. & Verkhivker, G.M., 1996, Unraveling principles of lead discovery: from unfrustrated energy landscapes to novel molecular anchors. Proc. Natl. Acad. Sci. USA. 93: 8945–8950.

    Article  PubMed  CAS  Google Scholar 

  40. Tsai, C.-J., Xu, D., & Nussinov, R., 1998, Protein folding via binding and vice versa. Curr. Biol. 3: R71–R80.

    CAS  Google Scholar 

  41. Tsai, C.-J., Ma, B., & Nussinov, R., 1999, Folding and binding cascades: shifts in energy landscapes. Proc. Natl. Acad. Sci. USA. 96: 9970–9972.

    Article  PubMed  CAS  Google Scholar 

  42. Sinha, N., & Nussinov, R., 2001, Point mutations and sequence variability in proteins: Redistributions of preexisting populations. Proc. Natl. Acad. Sci. USA. 98: 3139–3144.

    PubMed  CAS  Google Scholar 

  43. Ma, B., Shatsky, M., Wolfson, H.J., & Nussinov, R., 2002, Multiple diverse ligands binding at a single protein site: a matter of pre-existing populations. Protein Sci. 11: 184–197.

    PubMed  CAS  Google Scholar 

  44. Verkhivker, G.M., Rejto, P,A., Bouzida, D., Arthurs, S., Colson, A.B., Freer, S.T., Gehlhaar, D.K., Larson, V., Luty, B.A., Marrone, T., & Rose, P.W., 1999, Towards understanding the mechanisms of molecular recognition by computer simulations of ligand-protein interactions J. Mol. Recognit. 12: 371–389.

    Article  PubMed  CAS  Google Scholar 

  45. Zhang, C., Chen, J., & DeLisi, C., 1999, Protein-protein recognition: exploring the energy funnels near the binding sites. Proteins: Struct. Funct. Genet. 34: 255–267.

    Google Scholar 

  46. Vakser, I.A., Matar, O.G., & Lam, C.F., 1999, A systematic study of lowresolution recognition in protein-protein complexes. Proc. Natl. Acad. Sci. USA. 96: 8477–8482.

    Article  PubMed  CAS  Google Scholar 

  47. Tovchigrechko, A. & Vakser, I.A., 2001, How common is the funnel-like energy landscape in protein-protein interactions? Protein Sci. 10, 1572–1583.

    Article  PubMed  CAS  Google Scholar 

  48. Camacho, C.J., Weng, Z., Vajda, S., & DeLisi, C. (1999) Free energy landscapes of encounter complexes in protein-protein association. Biophys. J. 76: 1166–1178.

    Article  PubMed  CAS  Google Scholar 

  49. Camacho, C.J., Vajda, S., 2001, Protein docking along smooth association pathways. Proc. Natl. Acad. Sci. USA. 98: 10636–10641.

    Article  PubMed  CAS  Google Scholar 

  50. Verkhivker, G.M., Bouzida, D., Gehlhaar, D.K., Rejto, P,A., Schaffer L, Arthurs, S., Colson, A.B., Freer, S.T., Larson, V., Luty, B.A., Marrone, T., & Rose, P.W., 2001, Hierarchy of simulation models in predicting molecular recognition mechanisms from the binding energy landscapes: structural analysis of the peptide complexes with SH2 domains. Proteins: Struct. Funct. Genet. 45: 456–470.

    CAS  Google Scholar 

  51. Verkhivker, G.M., Rejto, P,A., Bouzida, D., Arthurs, S., Colson, A.B., Freer, S.T., Gehlhaar, D.K., Larson, V., Luty, B.A., Marrone, T., & Rose, P.W., 2001, Navigating ligand-protein binding free energy landscapes: universality and diversity of protein folding and molecular recognition mechanisms. Chem. Phys. Lett. 336: 495–503.

    Article  CAS  Google Scholar 

  52. Verkhivker, G.M., Bouzida, D., Gehlhaar, D.K., Rejto, P.A., Freer, S.T., & Rose, P.W., 2002, Complexity and simplicity of ligand-macromolecule interactions: the energy landscape perspective. Curr. Opin. Struct. Biol. 12: 197–202.

    Article  PubMed  CAS  Google Scholar 

  53. Verkhivker, G.M., Bouzida, D., Gehlhaar, D.K., Rejto, P,A., Freer, S.T., & Rose, P.W., 2002, Monte Carlo simulations of the peptide recognition at the consensus binding site of the constant fragment of human immunoglobulin G: the energy landscape analysis of a hot spot at the intermolecular interface. Proteins: Struct. Funct. Genet. 48: 539–557.

    CAS  Google Scholar 

  54. Plaxco, K.W., Simons, K.T., & Baker, D., 1998, Contact order, transition state placement and the refolding rates of single domain protein. J. Mol. Biol. 277: 985–994.

    Article  PubMed  CAS  Google Scholar 

  55. Grantcharova, V.P., Riddle, D.S., Santiago, J.V., & Baker, D., 1998, Important role of hydrogen bonds in the structurally polarized transition state for folding of the src SH3 domain. Nat. Struct. Biol. 5, 714–720.

    Article  PubMed  CAS  Google Scholar 

  56. Riddle, D.S., Grantcharova, V.P., Santiago, J.V., Alm, E., Ruczinski, I., & Baker, D., 1999, Experiment and theory highlight role of native state topology in SH3 folding. Nat. Struct. Biol. 6:1016–1024.

    PubMed  CAS  Google Scholar 

  57. Martinez, J.C.,& Serrano, L., 1999, The folding transition state between SH3 domains is conformationally restricted and evolutionarily conserved. Nat. Struct. Biol. 6: 1010–1016.

    PubMed  CAS  Google Scholar 

  58. Plaxco, K.W., Larson, S., Ruczinski, I., Riddle, D.S., Thayer, E.C., Buchwitz, B., & Davidson, A.R., 2000, Evolutionary conservation in protein folding kinetics. J. Mol. Biol. 298: 303–312.

    Article  PubMed  CAS  Google Scholar 

  59. Baker, D., 2000, A surprising simplicity to protein folding. Nature 405: 39–42.

    Article  PubMed  CAS  Google Scholar 

  60. Plaxco, K.W., Simons, K.T., Ruczinski, I., & Baker, D., 2000, Topology, stability, sequence, and length: defining the determinants of two-state protein folding kinetics. Biochemistry 39: 11177–11183.

    Article  PubMed  CAS  Google Scholar 

  61. Larson, S,M,, Ruczinski, I., Davidson, A.R., Baker, D., & Plaxco, K.W. 2002, Residues participating in the protein folding nucleus do not exhibit preferential evolutionary conservation. J. Mol. Biol. 316:225–233.

    Article  PubMed  CAS  Google Scholar 

  62. Fersht, A.R., 2000, Transition-state structure as a unifying basis in proteinfolding mechanisms: contact order, chain topology, stability, and the extended nucleus mechanism. Proc. Natl. Acad. Sci. USA. 97: 1525–1529.

    PubMed  CAS  Google Scholar 

  63. Galzitskaya, O.V., & Finkelstein, A.V., 1999, Atheoretical search for folding/unfolding nuclei in three-dimensional protein structures. Proc. Natl. Acad. Sci. USA. 96: 11299–11304.

    Article  PubMed  CAS  Google Scholar 

  64. Alm, E., & Baker. D., 1999, Prediction of protein-folding mechanisms from free-energy landscapes derived from native structures. Proc. Natl. Acad. Sci. USA. 96: 11305–11310.

    Article  PubMed  CAS  Google Scholar 

  65. Munoz, V., & Eaton W.A., 1999, A simple model for calculating the kinetics of protein folding from three-dimensional structures. Proc. Natl. Acad. Sci. USA. 96: 11311–11316.

    Article  PubMed  CAS  Google Scholar 

  66. Tsai, J., Levitt, M., & Baker, D., 1999, Hierarchy of structure loss in MD simulations of src SH3 domain unfolding. J. Mol. Biol. 291:215–225.

    Article  PubMed  CAS  Google Scholar 

  67. Alm, E., & Baker D. (1999). Matching theory and experiment in protein folding. Curr. Opin. Struct. Biol. 9: 189–199.

    Article  PubMed  CAS  Google Scholar 

  68. Clementi, C., Nymeyer, H. & Onuchic, J., 2000, Topological and energetic factors: what determines the structural details of the transition state ensemble and en-route intermediates for protein folding? An investigation for small globular proteins. J. Mol. Biol. 298: 937–953.

    Article  PubMed  CAS  Google Scholar 

  69. Clementi, C., Jennings, P.A., & Onuchic, J.N., 2000, How native-state topology affects the folding of dihydrofolate reductase and interleukin-1beta. Proc. Natl. Acad. Sci. USA. 97:5871–5876.

    Article  PubMed  CAS  Google Scholar 

  70. Clementi, C., Jennings, P.A., & Onuchic, J.N., 2001, Prediction of folding mechanism for circular-permuted proteins. J. Mol. Biol. 311: 879–890.

    Article  PubMed  CAS  Google Scholar 

  71. Vendruscolo, M., Paci, E., Dobson, C.M., & Karplus, M., 2001, Three key residues form a critical contact network in a protein folding transition state. Nature 409: 641–645.

    Article  PubMed  CAS  Google Scholar 

  72. Ferrara, P., & Caflisch, A., 2001, Native topology or specific interactions: what is more important for protein folding? J. Mol. Biol. 306: 837–850.

    Article  PubMed  CAS  Google Scholar 

  73. Gsponer, J., & Caflisch, A., 2001, Role of native topology investigated by multiple unfolding simulations of four SH3 domains. J. Mol. Biol. 309: 285–298.

    Article  PubMed  CAS  Google Scholar 

  74. Gsponer, J., & Caflisch, A., 2002, Molecular dynamics simulations of protein folding from the transition state. Proc. Natl. Acad. Sci. USA. 99: 6719–6724.

    Article  PubMed  CAS  Google Scholar 

  75. Dokholyan, N.V., Li, L., Ding, F., & Shakhnovich, E.I., 2002, Topological determinants of protein folding. Proc. Natl. Acad. Sci. USA. 99: 8637–8644.

    PubMed  CAS  Google Scholar 

  76. Wolynes, P.G., 1997, Folding funnels and energy landscapes of larger proteins within the capillarity approximation. Proc. Natl. Acad. Sci. USA. 94: 6170–6715.

    Article  PubMed  CAS  Google Scholar 

  77. Shoemaker, B.A., & Wolynes, P.G., 1999, Exploring structures in protein folding funnels with free energy functionals: the denatured ensemble. J. Mol. Biol. 287: 657–674.

    PubMed  CAS  Google Scholar 

  78. Shoemaker, B.A., Wang, J., & Wolynes, P.G., 1999, Exploring structures in protein folding funnels with free energy functionals: the transition state ensemble. J. Mol. Biol. 287: 675–694.

    PubMed  CAS  Google Scholar 

  79. Portman, J., Takada, S. & Wolynes, P., 2001, Micro-scopic theory of protein folding rates. I. Fine structure of the free energy profile and folding routes from a variational approach. J. Chem. Phys. 114: 5069–5081.

    CAS  Google Scholar 

  80. Portman, J., Takada, S. & Wolynes, P., 2001, Microscopic theory of protein folding rates. II. Local reaction coordinates and chain dynamics. J. Chem. Phys. 114: 5082–5096.

    CAS  Google Scholar 

  81. Alm, E,., Morozov, A.V., Kortemme, T., & Baker, D., 2002, Simple physical models connect theory and experiment in protein folding kinetics. J. Mol. Biol. 322: 463–476.

    Article  PubMed  CAS  Google Scholar 

  82. McCallister, E.L., Alm, E., & Baker, D., 2000, Critical role of beta-hairpin formation in protein G folding. Nat. Struct. Biol. 7: 669–673.

    Article  PubMed  CAS  Google Scholar 

  83. Nauli, S., Kuhlman, B., & Baker, D., 2001, Computer-based redesign of a protein folding pathway. Nat. Struct. Biol. 8: 602–605.

    Article  PubMed  CAS  Google Scholar 

  84. Heidary, D.K., & Jennings, P.A., 2002, Three topologically equivalent core residues affect the transition state ensemble in a protein folding reaction. J. Mol. Biol. 316: 789–798.

    Article  PubMed  CAS  Google Scholar 

  85. Shoemaker, B.A., Portman, J.J., & Wolynes, P.G., 2000, Speeding molecular recognition by using the folding funnel: the fly-casting mechanism. Proc. Natl. Acad. Sci. USA. 97: 8868–8873.

    Article  PubMed  CAS  Google Scholar 

  86. Duan, Y. & Kollman, P.A., 1998, Pathways to a protein folding intermediate observed in a 1-microsecond simulation in aqueous solution. Science 282: 740–744.

    Article  PubMed  CAS  Google Scholar 

  87. Zagrovic, B., Snow, C.D., Shirts, M.R., & Pande, V.S., 2002, Simulation of folding of a small alpha-helical protein in atomistic detail using world wide distributed computing. J. Mol. Biol. 323: 927–929.

    PubMed  CAS  Google Scholar 

  88. Snow, C.D., Nguyen, H., Pande, V.S., & Gruebele, M., 2002, Absolute comparison of simulated and experimental protein-folding dynamics. Nature 420: 102–106.

    PubMed  CAS  Google Scholar 

  89. Boczko, E.M., & Brooks III, C.L., 1995, First-principles calculation of the folding free energy of a three-helix bundle protein. Science 269: 393–396.

    PubMed  CAS  Google Scholar 

  90. Guo, Z., & Brooks III, C.L. (1997) Thermodynamics of protein folding: a statistical mechanical study of a small all-protein. Biopolymers, 42: 745–757.

    Article  PubMed  CAS  Google Scholar 

  91. Guo, Z., Brooks III, C.L., & Boczko E.M., 1997, Exploring the folding free energy surface of a three-helix bundle protein. Proc. Natl. Acad. Sci. USA 94: 10161–10166.

    PubMed  CAS  Google Scholar 

  92. Sheinerman, F.B., & Brooks III, C.L., 1998, Molecular picture of folding of a small alpha/beta protein. Proc. Natl. Acad. Sci. USA 95: 1562–1567.

    Article  PubMed  CAS  Google Scholar 

  93. Shea, J.E., Onuchic, J.N., & Brooks III, C.L., 1999, Exploring the origins of topological frustration: design of a minimally frustrated model of fragment B of protein A. Proc. Natl. Acad. Sci. USA 96: 12512–12517.

    Article  PubMed  CAS  Google Scholar 

  94. Shea, J.E., & Brooks III, C.L., 2001, From folding theories to folding proteins: a review and assessment of simulation studies of protein folding and unfolding. Annu. Rev. Phys. Chem. 52: 499–535.

    Article  PubMed  CAS  Google Scholar 

  95. Lazaridis, T., and Karplus, M., 1997, “New view” of protein folding reconciles with the old through multiple unfolding simulations. Science 278: 1928–1931.

    Article  PubMed  CAS  Google Scholar 

  96. Sheinerman, F. & Brooks III, C.L., 1998, Calculations on folding of segment B1 of streptococcal protein G. J. Mol. Biol. 278:439–456.

    Article  PubMed  CAS  Google Scholar 

  97. Daggett, V., 2002, Molecular dynamics simulations of the protein unfolding/folding reaction. Acc. Chem. Res. 35:422–429.

    Article  PubMed  CAS  Google Scholar 

  98. De Jong, D., Riley, R., Alonso, D.O., & Daggett, V., 2002, Probing the energy landscape of protein folding/unfolding transition states. J. Mol. Biol. 319: 229–242.

    PubMed  Google Scholar 

  99. Day, R., Bennion, B.J., Ham, S., & Daggett, V., 2002, Increasing temperature accelerates protein unfolding without changing the pathway of unfolding. J. Mol. Biol. 322:189–203.

    Article  PubMed  CAS  Google Scholar 

  100. Mayor, U., Johnson, C.M., Daggett, V., & Fersht, A.R., 2000, Protein folding and unfolding in microseconds to nanoseconds by experiment and simulation. Proc. Natl. Acad. Sci. USA 97: 13518–13522.

    Article  PubMed  CAS  Google Scholar 

  101. Daggett, V., 2000, Long timescale simulations. Curr. Opin. Struct. Biol. 10:160–164.

    Article  PubMed  CAS  Google Scholar 

  102. Ladurner, A.G., Itzhaki, L.S., Daggett, V., & Fersht, A.R., 1998, Synergy between simulation and experiment in describing the energy landscape of protein folding. Proc. Natl. Acad. Sci. USA 95:8473–8478.

    Article  PubMed  CAS  Google Scholar 

  103. Brooks III, C.L,. 1998, Simulations of protein folding and unfolding. Curr. Opin. Struct. Biol. 8: 222–226.

    Article  PubMed  CAS  Google Scholar 

  104. Pande, V.S., & Rokhsar, D.S., 1999, Molecular dynamics simulations of unfolding and refolding of a beta-hairpin fragment of protein G. Proc. Natl. Acad. Sci. USA 96: 9062–9067.

    PubMed  CAS  Google Scholar 

  105. Nymeyer, H., Socci, N.D., & Onuchic, J.N., 2000, Landscape approaches for determining the ensemble of folding transition states: success and failure hinge on the degree of frustration. Proc. Natl. Acad. Sci. USA 97:634–639.

    Article  PubMed  CAS  Google Scholar 

  106. R. Du, V.S., Pande, A.Y., Grosberg, T., Tanaka, E.S., & Shakhnovich, 1998, On the transition coordinate for protein folding. J. Chem. Phys. 108: 334–350.

    Article  CAS  Google Scholar 

  107. Pande, V.S., & Rokshar, D., 1999, Folding pathway of a lattice model for proteins. Proc. Natl. Acad. Sci. USA. 96: 1273–1278.

    PubMed  CAS  Google Scholar 

  108. Verkhivker, G.M., Bouzida, D., Gehlhaar, D.K., Rejto, P,A., Freer, S.T., & Rose, P.W., 2003, Simulating disorder-order transitions in molecular recognition of unstructured proteins: where folding meets binding. Proc. Natl. Acad. Sci. USA 100: 5148–5153.

    Article  PubMed  CAS  Google Scholar 

  109. Mayo, S.L., Olafson, B.D., Goddard, W. A. III., 1990, DREIDING: a generic force field for molecular simulation. J. Phys. Chem. 94: 8897–8909.

    Article  CAS  Google Scholar 

  110. Bouzida, D., Kumar, S. and Swendsen, R.H., 1992, Efficient Monte Carlo methods for the computer simulation of biological molecules. Phys. Rev. A 45: 8894–8901.

    Article  PubMed  CAS  Google Scholar 

  111. Bouzida, D., Rejto, P.A., Arthurs, S., Colson, A.B., Freer, S.T., Gehlhaar, D.K., Larson, V., Luty, B.A., Rose, P.W. and Verkhivker, G.M., 1999, Computer simulations of ligand-protein binding with ensembles of protein conformations: A Monte Carlo study of HIV-1 protease binding energy landscapes. Int. J. Quantum Chem. 72: 73–84.

    Article  CAS  Google Scholar 

  112. Bouzida, D., Rejto, P.A. and Verkhivker, G.M., 1999, Monte Carlo simulations of ligand-protein binding energy landscapes with the weighted histogram analysis method. Int. J. Quantum Chem. 73: 113–121.

    Article  CAS  Google Scholar 

  113. Willet, P., & Winterman, V., 1986, A Comparison of some measures for the determination of intermolecular structural similarity. Quant. Struct.-Act. Relat. Pharmacol. Chem. Biol. 5: 18–25.

    Google Scholar 

  114. Willet, P., Winterman, V., & Bawden, D. (1986) Implementation of non-hierarchical cluster analysis methods in chemical information systems: selection of compounds for biological testing and clustering of substructure search output. J. Chem. Inf. Comput. Sci. 26: 109–118.

    Google Scholar 

  115. Bawden D., 1888, Browsing and clustering of chemical structures. In The international language of chemistry, (W.A. Warr, eds.) Springer-Verlag, Berlin, pp. 145–150.

    Google Scholar 

  116. Shakhnovich, E.I., 1998, Folding nucleus: specific or multiple ? Insights form lattice models and experiments. Fold. Des. 3: R108–R111.

    PubMed  CAS  Google Scholar 

  117. Thirumalai, D. & Klimov, D.K., 1998, Fishing for folding nuclei in lattice models and proteins. Fold. Des. 3: R111–R118.

    Article  Google Scholar 

  118. Li, L., Mirny, L.A., & Shakhnovich, E.I., 2000, Kinetics, thermodynamics and evolution oif non-native interactions in a protein folding nucleus. Nat. Struct. Biol. 7:336–342.

    PubMed  CAS  Google Scholar 

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  1. Pfizer Global Research and Development, La Jolla Laboratories, 10777 Science Center Drive, San Diego, CA, 921211111, USA

    Gennady M. Verkhivker

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  1. Gennady M. Verkhivker
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  1. Ruder Bošković Institute, Zagreb, Croatia

    Greta Pifat-Mrzljak

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Verkhivker, G.M. (2005). A Microscopic Study of Disorder-Order Transitions in Molecular Recognition of Unstructured Proteins: Hierarchy of Structural Loss and the Transition State Determination from Monte Carlo Simulations of P27KIP1 Protein Coupled Unfolding and Unbinding. In: Pifat-Mrzljak, G. (eds) Supramolecular Structure and Function 8. Springer, Boston, MA. https://doi.org/10.1007/0-306-48662-8_12

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  • DOI: https://doi.org/10.1007/0-306-48662-8_12

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