Coarse-grained models for protein folding and aggregation

Methods in Molecular Biology

Volumn 924, Issue , 2013, Pages 585-600

  Derreumaux, Philippe ^a  

^a NONE

Author keywords

Aggregation; Coarse grained models; Dynamics; Kinetics; Misfolding; Proteins; Simulations; Structures; Thermodynamics

Indexed keywords

AMINO ACID; AMYLOID PROTEIN; PROTEIN; PROTEIN SH3;

ARTICLE; ATOM; COARSE GRAINED MODEL; DEGENERATIVE DISEASE; ENERGY; MOLECULAR DYNAMICS; MOLECULAR MODEL; NEUROLOGIC DISEASE; PRIORITY JOURNAL; PROTEIN AGGREGATION; PROTEIN CONFORMATION; PROTEIN FOLDING; THERMODYNAMICS; TRANSITION TEMPERATURE;

EID: 84934442761     PISSN: 10643745     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-1-62703-17-5_22     Document Type: Article

References (85)

1. Anfinsen CB (1973) Principles that govern the folding of proteins. Science 181:223-230
2. Andreeva A, Howorth D, Chandonia JM, Brenner SE, Hubbard TJ, Chothia C, Murzin A (2008) Data growth and its impact on the SCOP database: new developments. Nucleic Acids Res 36:D419-D425, Database issue
3. Wright PE, Dyson HJ (2009) Linking binding and folding. Curr Opin Struct Biol 19:31-38
4. Goldschmidt L, Teng PK, Riek R, Eisenberg D (2010) Identifying the amylome, proteins capable of forming amyloid-like fibrils. Proc Natl Acad Sci U S A 107(8):3487-3492
5. Kim SJ, Born B, Havenith M, Gruebele M (2008) Real-time detection of protein-water dynamics upon protein folding by Terahertz absorption. Angew Chem Int Ed Engl 47 :6486-6489
6. Karplus M, McCammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 9(9):646-652
7. Sugita Y, Okamoto Y (1999) Replica exchange molecular dynamics method for protein folding. Chem Phys Lett 329:261-270
8. Berg BA, Neuhaus T (1992) Multicanonical ensemble: a new approach to simulate firstorder phase transitions. Phys Rev Lett 68:9-12
9. Born M, Oppenheimer R (1927) Zur quantentheorie der molekeln. Ann Phys Leipzig 84:457
10. Duan Y, Kollman PA (1998) Pathways to a protein folding intermediate observed in a 1-microsecond simulation in aqueous solution. Science 282:740-744
11. Jayachandran G, Vishal V, Pande VS (2006) Using massively parallel simulation and Markovian models to study protein folding: examining the dynamics of the villin headpiece. J Chem Phys 124:164902
12. Wriggers W, Stafford KA, Shan Y, Piana S, Maragakis P, Lindorff-Larsen K, Miller PJ, Gullingsrud J, Rendleman CA, Eastwood MP, Dror RO, Shaw DE (2009) Automated event detection and activity monitoring in long molecular dynamics simulations. J Chem Theory Comput 5:2595-2605
13. Fukunishi H, Watanabe O, Takada S (2002) On the Hamiltonian replica exchange method for efficient sampling of biomolecular systems: application to protein structure. J Chem Phys 116(20):9058-9067
14. Sgourakis NG, Yan Y, McCallum SA, Wang C, Garcia AE (2007) The Alzheimer's peptides Abeta40 and 42 adopt distinct conformations in water: a combined MD/NMR study. J Mol Biol 368(5):1448-1457
15. De Simone A, Derreumaux P (2010) Low molecular weight oligomers of amyloid peptides display beta-barrel conformations: a replica exchange molecular dynamics study in explicit solvent. J Chem Phys 132(16): 165103
16. Mucke L (2009) Neuroscience: Alzheimer's disease. Nature 461(7266):895-897
17. Levitt M, Warshel A (1975) Computer simulation of protein folding. Nature 253:694-698
18. Chebaro Y, Dong X, Laghaei R, Derreumaux P, Mousseau N (2009) Replica exchange molecular dynamics simulations of coarsegrained proteins in implicit solvent. J Phys Chem B 113(1):267-274
19. Clementi C (2007) Coarse-grained models of protein folding: toy models or predictive tools? Curr Opin Struct Biol 17:1-6
20. Tozzini V (2005) Coarse-grained models for proteins. Curr Opin Struct Biol 15:144-150
21. Chu J-W, Voth GA (2007) Coarse-grained free energy functions for studying protein conformational changes: a double-well network model. Biophys J 93:3860-3871
22. Khalid S, Bond PJ, Holyoake J, Hawtin RW, Sansom MS (2008) DNA and lipid bilayers: self-Assembly and insertion. J R Soc Interface 5(Suppl 3):S241-S250
23. Pasquali S, Derreumaux P (2010) HiRE-RNA: a high-resolution coarse-grained energy model for RNA. J Phys Chem B 114(37):11957-66
24. Ueda Y, Taketomi H, Go N (1978) Studies on protein folding, unfolding and fluctuations by computer simulation II. A three-dimensional lattice model of lysozyme. Biopolymers 17:1531-1548
25. Dill KA, Chan HS (1997) From Levinthal to pathways to funnels. Nat Struct Biol 4:10-19
26. Bryngelson JD, Onuchic JN, Socci ND, Wolynes JD (1995) Funnels, pathways, and the energy landscape of protein folding: a synthesis. Proteins 21:167-195
27. Shakhnovich E (2006) Protein folding thermodynamics and dynamics: where physics, chemistry, and biology meet. Chem Rev 106:1559-1588
28. De Sancho D, Doshi U, Munoz V (2009) Protein folding rates and stability: how much is there beyond size? J Am Chem Soc 131:2074-2075
29. Qi Y, Huang Y, Liang H, Liu Z, Lai L (2010) Folding simulations of a de novo designed protein with a betaalphabeta fold. Biophys J 98 321-329
30. Cheung MS, Garcia AE, Onuchic JE (2002) Protein folding mediated by solvation: water expulsion and formation of the hydrophobic core occur after the structural collapse. Proc Natl Acad Sci U S A 99:685-690
31. Ferguson A, Liu Z, Chan HS (2009) Desolvation barrier effects are a likely contributor to the remarkable diversity in the folding rates of small proteins. J Mol Biol 389(3):619-636
32. Liu Z, Chan HS (2005) Solvation and desolvation effects in protein folding: native flexibility, kinetic cooperativity and enthalpic barriers under isostability conditions. Phys Biol 2(4): S75-S85
33. Honeycutt JD, Thirumalai D (1990) Metastability of the folded states of globular proteins. Proc Natl Acad Sci U S A 87:3526-3529
34. Jewett AI, Baumketner A, Shea JE (2004) Accelerated folding in the weak hydrophobic environment of a chaperonin cavity: creation of an alternate fast folding pathway. Proc Natl Acad Sci U S A 101(36):13192-13197
35. Cheung MS, Klimov D, Thirumalai D (2005) Molecular crowding enhances native state stability and refolding rates. Proc Natl Acad Sci U S A 102:4753-4758
36. Cheung MS, Thirumalai D (2007) Effects of crowding and confinement on the structures of the transition state ensemble in proteins. J Phys Chem B 11:8250-8257
37. Das P, Matysiak S, Clementi C (2005) Balancing energy and entropy: a minimalist model for the characterization of protein folding landscapes. Proc Natl Acad Sci U S A 102:10141-10146
38. Bellesia G, Jewett AI, Shea J-E (2010) Sequence periodicity and secondary structure propensity in model proteins. Protein Sci 19:141-154
39. Yap E-H, Fawzi NL, Head-Gordon T (2008) A coarse-grained a-carbon protein model with anisotropic hydrogen-bonding. Proteins 70:626-638
40. Miyazawa S, Jernigan RL (1999) Selfconsistent estimation of inter-residue protein contact energies based on an equilibrium mixture approximation of residues. Proteins 34:49-68
41. Hagai T, Levy Y (2008) Folding of elongated proteins: conventional or anomalous? J Am Chem Soc 130:14253-14262
42. Moritsugu K, Smith JC (2008) REACH Coarse-grained biomolecular simulation: transferability between different protein structural classes. Biophys J 95:1639-1648
43. Alemani D, Collu F, Cascella M, Dal Peraro M (2010) A nonradial coarse-grained potential for proteins produces naturally stable secondary structure elements. J Chem Theory Comput 6:315-324
44. Sasaki TN, Cetin H, Sasai M (2008) A coarsegrained Langevin molecular dynamics approach to de novo protein structure prediction. Biochem Biophys Res Commun 369 500-506
45. Han W, Wan C, Wu Y (2008) Toward a coarsegrained protein model coupled with a coarsegrained solvent model: solvation free energies of amino acid side chains. J Chem Theory Comput 4:1891-1901
46. Thorpe IF, Zhou J, Voth GA (2008) Peptide folding using multiscale coarse-grained models. J Phys Chem B 112:13079-13090
47. Basdevant N, Borgis D, Ha-Duong T (2007) A coarse-grained protein-protein potential derived from an all-Atom force field. J Phys Chem B 111:9390-9399
48. Zacharias M (2003) Protein-protein docking with a reduced protein model accounting for side-chain flexibility. Protein Sci 12:1271-1282
49. Ha-Duong T (2010) Protein backbone dynamics simulations using coarse-grained bonded potentials and simplified hydrogen bonds. J Chem Theory Comput 6:761-773
50. Majek P, Elber R (2009) A coarse-grained potential for fold recognition and molecular dynamics simulations of proteins. Proteins 76:822-836
51. De Mori G, Colombo G, Micheletti C (2005) Study of the villin headpiece folding dynamics by combining coarse-grained Monte Carlo evolution and all-Atom molecular dynamics. Proteins 58:459-471
52. Maisuradze GG, Senet P, Czaplewski C, Liwo A, Scheraga HA (2010) Investigation of protein folding by coarse-grained molecular dynamics with the UNRES force field. J Phys Chem A 114:4471-4485
53. Czaplewski C, Kalinowski S, Liwo A, Scheraga HA (2009) Application of multiplexed replica exchange molecular dynamics to the UNRES force field: tests with a and a + b proteins. J Chem Theory Comput 5:627-640
54. Cossio P, Marinelli F, Laio A, Pietrucci F (2010) Optimizing the performance of biasexchange metadynamics: folding a 48-residue LysM domain using a coarse-grained model. J Phys Chem B 114:3259-3265
55. DeVane R, Shinoda W, Moore PB, Klein ML (2009) Transferable coarse grain non-bonded interaction model for amino acids. J Chem Theory Comput 5:2115-2124
56. Monticelli L, Kandasamy SK, Periole X, Larson RG, Tieleman DP, Marrink S (2008) The MARTINI coarse-grained force field: extension to proteins. J Chem Theory Comput 4:819-834
57. Fujitsuka Y, Takada S, Luthey-Schulten ZA, Wolynes PG (2004) Optimizing physical energy functions for protein folding. Proteins 54:88-103
58. Chikenji G, Fujitsuka Y, Takada S (2006) Shaping up the protein folding funnel by local interaction: lesson from a structure prediction study. Proc Natl Acad Sci U S A 103:3141-3146
59. Rohl CA, Strauss CE, Chivian D, Baker D (2004) Protein structure prediction using Rosetta. Methods Enzymol 383:66-93
60. Bradley P,Misura KM, Baker D (2005) Towards high-resolution de novo structure prediction for small proteins. Science 309:1868-1871
61. Bowman GR, Pande VS (2009) Simulated tempering yields insight into the low resolution Rosetta scoring functions. Proteins 74:777-788
62. Shmygelska A, Levitt M (2009) Generalized ensemble methods for de novo structure prediction. Proc Natl Acad Sci U S A 106:1415-1420
63. Das R, Andre I, Shen Y,Wu Y, Lemak A, Bansal S, Arrowsmith CH, Szyperski T, Baker D (2009) Simultaneous prediction of protein folding and docking at high resolution. Proc Natl Acad Sci U S A 106:18978-18983
64. Irback A, Sjunnesson F,Wallin S (2000) Threehelix-bundle protein in a Ramachandran model. Proc Natl Acad Sci U S A 97:13614-13618
65. Ding F, Buldyrev SV, Dokholyan NV (2005) Folding Trp-cage to NMR resolution native structure using a coarse-grained protein model. Biophys J 88:147-155
66. Smith AV, Hall CK (2001) a-Helix formation: discontinuous molecular dynamics on an intermediate-resolution protein model. Proteins 44:344-360
67. Sharma S, Ding F, Nie H,Watson D, Unnithan A, Lopp J, Pozefsky D, Dokholyan NV (2006) iFold: a platform for interactive folding simulations of proteins. Bioinformatics 22 2693-2694
68. Ding F, LaRocque JJ, Dokholyan NV (2005) Direct observation of protein folding, aggregation, and a prion-like conformational conversion. J Biol Chem 280(48):40235-40240
69. Walsh DM, Klyubin I, Fadeeva JV, Cullen WK, Anwyl R, Wolfe MS, Rowan MJ, Selkoe DJ (2002) Naturally secreted oligomers of amyloid beta protein potently inhibit hippocampal longterm potentiation in vivo. Nature 416:483-484
70. Lesne S, Teng Koh M, Kotilinek L, Kayed R, Glabe CG, Yang A, Gallaher M, Ashe K (2006) A specific amyloid-b protein assembly in the brain impairs memory. Nature 440:352-357
71. Urbanc B, Cruz L, Yun S, Buldyrev SV, Bitan G, Teplow DB, Stanley HE (2004) In silico study of amyloid beta-protein folding and oligomerization. Proc Natl Acad Sci U S A 101:17345-17350
72. Urbanc B, Betnel M, Cruz L, Bitan G, Teplow DB (2010) Elucidation of amyloid betaprotein oligomerization mechanisms: discrete molecular dynamics study. J Am Chem Soc 132:4266-4280
73. Derreumaux P (2000) Generating ensemble averages for small proteins from extended conformations by Monte Carlo simulations. Phys Rev Lett 85:206-209
74. Maupetit J, Tuffery P, Derreumaux P (2007) A coarse-grained protein force field for folding and structure prediction. Proteins 69 :394-408
75. Santini S, Mousseau N, Derreumaux P (2004) In silico assembly of Alzheimer's Ab16-22 peptide into b-sheets. J Am Chem Soc 126:11509-11516
76. Derreumaux P, Mousseau N (2007) Coarsegrained protein molecular dynamics simulations. J Chem Phys 126:025101-025106
77. Mousseau N, Derreumaux P (2005) Exploring the early steps of amyloid peptide aggregation by computers. Acc Chem Res 38:885-891
78. Lu Y, Derreumaux P, Guo Z, Mousseau N,Wei G (2009) Thermodynamics and dynamics of amyloid peptide oligomerisation is sequencedependent. Proteins 5(4):954-963
79. Melquiond A, Dong X, Mousseau N, Derreumaux P (2008) Role of the region 23-28 in Ab fibril formation: insights from simulations of the monomers and dimers of Alzheimer's peptides Ab40 and Ab42. Curr Alzheimer Res 5 :244-250
80. Chebaro Y, Mousseau N, Derreumaux P (2009) Structures and thermodynamics of Alzheimer's amyloid-b Ab(16-35) monomer and dimer by replica exchange molecular dynamics simulations: implication for full-length Ab fibrillation. J Phys Chem B 113:7668-7675
81. Maupetit J, Derreumaux P, Tuffery P (2009) PEP-FOLD: an online resource for de novo peptide structure prediction. Nucleic Acids Res 37:W498-W503, Web Server issue
82. Maupetit J, Derreumaux P, Tuffery P (2010) A fast method for large-scale de novo peptide and miniprotein structure prediction. J Comput Chem 31(4):726-738
83. Audie J, Boyd C (2010) The synergistic use of computation, chemistry and biology to discover novel peptide-based drugs: the time is right. Curr Pharm Des 16(5):567-582
84. Chiti F, Dobson CM (2006) Protein misfolding, functional amyloid, and human disease. Annu Rev Biochem 75:333-366
85. De Beer SB, Vermeulen NP, Oostenbrick C (2010) The role of water molecules in computational drug design. Curr Top Med Chem 10 55-66