Cooperativity among short amyloid stretches in long amyloidogenic sequences

PLoS ONE

Volumn 7, Issue 6, 2012, Pages

  Hu, Lele ^a   Cui, Weiren ^b   He, Zhisong ^b   Shi, Xiaohe ^c   Feng, Kaiyan ^d   Ma, Buyong ^e   Cai, Yu Dong ^a  

^a SHANGHAI UNIVERSITY   (China)

^b Shanghai Jiao Tong University Affiliated Sixth People s Hospital   (China)

^c SHANGHAI JIAO TONG UNIVERSITY SCHOOL OF MEDICINE   (China)

^d SHANGHAI CENTER FOR BIOINFORMATION TECHNOLOGY   (China)

^e NATIONAL CANCER INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMYLOID; ISOLEUCINE; LYSINE; THREONINE;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; COOPERATION; DEGENERATIVE DISEASE; HYDROPHOBICITY; K NEAREST NEIGHBOR; MACHINE LEARNING; NEUROFILAMENT; PEPTIDE SYNTHESIS; PREDICTION; PROTEIN AGGREGATION; PROTEIN MOTIF; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; RANDOM FOREST; SUPPORT VECTOR MACHINE;

ALGORITHMS; AMINO ACID SEQUENCE; AMYLOID; DATABASES, PROTEIN; HUMANS; PROTEIN STRUCTURE, TERTIARY;

EID: 84862676446     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0039369     Document Type: Article

References (59)

1. Dobson CM, (2001) The structural basis of protein folding and its links with human disease. Philos Trans R Soc Lond B Biol Sci 356: 133-145.
2. Toombs JA, McCarty BR, Ross ED Compositional determinants of prion formation in yeast, (2010) Mol Cell Biol 30: 319-332.
3. Trojanowski JQ, Mattson MP, (2003) Overview of protein aggregation in single, double, and triple neurodegenerative brain amyloidoses. Neuromolecular Med 4: 1-6.
4. Dobson CM, (2002) Getting out of shape. Nature 418: 729-730.
5. Chiti F, Dobson CM, (2006) Protein misfolding, functional amyloid, and human disease. Annu Rev Biochem 75: 333-366.
6. Cohen FE, (1999) Protein misfolding and prion diseases. J Mol Biol 293: 313-320.
7. Ecroyd H, Carver JA, (2009) Crystallin proteins and amyloid fibrils. Cell Mol Life Sci 66: 62-81.
8. Kelly JW, (2002) Towards an understanding of amyloidogenesis. Nat Struct Biol 9: 323-325.
9. Nelson R, Eisenberg D, (2006) Recent atomic models of amyloid fibril structure. Curr Opin Struct Biol 16: 260-265.
10. Pastor MT, Esteras-Chopo A, Serrano L, (2007) Hacking the code of amyloid formation: the amyloid stretch hypothesis. Prion 1: 9-14.
11. Esteras-Chopo A, Serrano L, Lopez de la Paz M, (2005) The amyloid stretch hypothesis: recruiting proteins toward the dark side. Proc Natl Acad Sci U S A 102: 16672-16677.
12. Tian J, Wu N, Guo J, Fan Y, (2009) Prediction of amyloid fibril-forming segments based on a support vector machine. BMC Bioinformatics 10: S45.
13. Zhang Z, Chen H, Lai L, (2007) Identification of amyloid fibril-forming segments based on structure and residue-based statistical potential. Bioinformatics 23: 2218-2225.
14. Maurer-Stroh S, Debulpaep M, Kuemmerer N, Lopez de la Paz M, Martins IC, et al. (2010) Exploring the sequence determinants of amyloid structure using position-specific scoring matrices. Nat Methods 7: 237-242.
15. 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: 3487-3492.
16. Ma B, Nussinov R, (2007) Trp/Met/Phe hot spots in protein-protein interactions: potential targets in drug design. Curr Top Med Chem 7: 999-1005.
17. Guo Z, Eisenberg D, (2008) The structure of a fibril-forming sequence, NNQQNY, in the context of a globular fold. Protein Sci 17: 1617-1623.
18. Buttstedt A, Winter R, Sackewitz M, Hause G, Schmid FX, et al. (2010) Influence of the stability of a fused protein and its distance to the amyloidogenic segment on fibril formation. PLoS One 5: e15436.
19. Murphy RM, Kendrick BS, (2007) Protein misfolding and aggregation. Biotechnol Prog 23: 548-552.
20. Xu S, (2007) Aggregation drives "misfolding" in protein amyloid fiber formation. Amyloid 14: 119-131.
21. Perczel A, Hudaky P, Palfi VK, (2007) Dead-end street of protein folding: thermodynamic rationale of amyloid fibril formation. J Am Chem Soc 129: 14959-14965.
22. Colombo G, Meli M, De Simone A, (2008) Computational studies of the structure, dynamics and native content of amyloid-like fibrils of ribonuclease A. Proteins 70: 863-872.
23. Sambashivan S, Liu Y, Sawaya MR, Gingery M, Eisenberg D, (2005) Amyloid-like fibrils of ribonuclease A with three-dimensional domain-swapped and native-like structure. Nature 437: 266-269.
24. Nelson R, Sawaya MR, Balbirnie M, Madsen AO, Riekel C, et al. (2005) Structure of the cross-beta spine of amyloid-like fibrils. Nature 435: 773-778.
25. Zheng J, Jang H, Ma B, Tsai CJ, Nussinov R, (2007) Modeling the Alzheimer Abeta17-42 fibril architecture: tight intermolecular sheet-sheet association and intramolecular hydrated cavities. Biophys J 93: 3046-3057.
26. Miller Y, Ma B, Nussinov R, (2010) Polymorphism in Alzheimer Abeta amyloid organization reflects conformational selection in a rugged energy landscape. Chem Rev 110: 4820-4838.
27. Ma B, Nussinov R, (2006) Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Curr Opin Chem Biol 10: 445-452.
28. Soldi G, Bemporad F, Torrassa S, Relini A, Ramazzotti M, et al. (2005) Amyloid formation of a protein in the absence of initial unfolding and destabilization of the native state. Biophys J 89: 4234-4244.
29. de Groot NS, Aviles FX, Vendrell J, Ventura S, (2006) Mutagenesis of the central hydrophobic cluster in Abeta42 Alzheimer's peptide. Side-chain properties correlate with aggregation propensities. FEBS J 273: 658-668.
30. Van Melckebeke H, Wasmer C, Lange A, Ab E, Loquet A, et al. (2010) Atomic-resolution three-dimensional structure of HET-s(218-289) amyloid fibrils by solid-state NMR spectroscopy. J Am Chem Soc 132: 13765-13775.
31. Wasmer C, Lange A, Van Melckebeke H, Siemer AB, Riek R, et al. (2008) Amyloid fibrils of the HET-s(218-289) prion form a beta solenoid with a triangular hydrophobic core. Science 319: 1523-1526.
32. Bahar I, Jernigan RL, (1997) Inter-residue potentials in globular proteins and the dominance of highly specific hydrophilic interactions at close separation. J Mol Biol 266: 195-214.
33. Breiman L, (2001) Random Forests. Mach Learn 45: 5-32.
34. Jia SC, Hu XZ, (2011) Using random forest algorithm to predict beta-hairpin motifs. Protein Pept Lett 18: 609-617.
35. Kandaswamy KK, Chou KC, Martinetz T, Moller S, Suganthan PN, et al. (2011) AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties. J Theor Biol 270: 56-62.
36. Lin WZ, Fang JA, Xiao X, Chou KC, (2011) iDNA-Prot: identification of DNA binding proteins using random forest with grey model. Plos One 6: e24756.
37. Tartaglia GG, Cavalli A, Pellarin R, Caflisch A, (2005) Prediction of aggregation rate and aggregation-prone segments in polypeptide sequences. Protein Sci 14: 2723-2734.
38. Tartaglia GG, Cavalli A, Pellarin R, Caflisch A, (2004) The role of aromaticity, exposed surface, and dipole moment in determining protein aggregation rates. Protein Sci 13: 1939-1941.
39. Fernandez-Escamilla AM, Rousseau F, Schymkowitz J, Serrano L, (2004) Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nat Biotechnol 22: 1302-1306.
40. Chiti F, Stefani M, Taddei N, Ramponi G, Dobson CM, (2003) Rationalization of the effects of mutations on peptide and protein aggregation rates. Nature 424: 805-808.
41. Frith MC, Spouge JL, Hansen U, Weng Z, (2002) Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences. Nucleic Acids Res 30: 3214-3224.
42. Jones DT, (1999) Protein secondary structure prediction based on position-specific scoring matrices. J Mol Biol 292: 195-202.
43. Kinjo AR, Nakamura H, (2008) Nature of protein family signatures: insights from singular value analysis of position-specific scoring matrices. PLoS One 3: e1963.
44. Benvenga S, Guarneri F, (2008) Additional evidence that the fibril amyloid-related proteins share local regions of amino acid sequence similarity. Amyloid 15: 269-271.
45. Padrick SB, Miranker AD, (2001) Islet amyloid polypeptide: identification of long-range contacts and local order on the fibrillogenesis pathway. J Mol Biol 308: 783-794.
46. Koo BW, Hebda JA, Miranker AD, (2008) Amide inequivalence in the fibrillar assembly of islet amyloid polypeptide. Protein Eng Des Sel 21: 147-154.
47. Maji SK, Ogorzalek Loo RR, Inayathullah M, Spring SM, Vollers SS, et al. (2009) Amino acid position-specific contributions to amyloid beta-protein oligomerization. J Biol Chem 284: 23580-23591.
48. Maurer-Stroh S, Debulpaep M, Kuemmerer N, Lopez de la Paz M, Martins IC, et al. (2010) Exploring the sequence determinants of amyloid structure using position-specific scoring matrices. Nat Methods 7: 237-242.
49. Peng K, Radivojac P, Vucetic S, Dunker AK, Obradovic Z, (2006) Length-dependent prediction of protein intrinsic disorder. BMC Bioinformatics 7: 208.
50. Cheng J, Randall AZ, Sweredoski MJ, Baldi P, (2005) SCRATCH: a protein structure and structural feature prediction server. Nucleic acids research 33: W72-76.
51. Jordan IK, Kondrashov FA, Adzhubei IA, Wolf YI, Koonin EV, et al. (2005) A universal trend of amino acid gain and loss in protein evolution. Nature 433: 633-638.
52. Ma B, Elkayam T, Wolfson H, Nussinov R, (2003) Protein-protein interactions: structurally conserved residues distinguish between binding sites and exposed protein surfaces. Proc Natl Acad Sci U S A 100: 5772-5777.
53. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389-3402.
54. Cai Y, He J, Li X, Lu L, Yang X, et al. (2009) A novel computational approach to predict transcription factor DNA binding preference. J Proteome Res 8: 999-1003.
55. Cai YD, Qian Z, Lu L, Feng KY, Meng X, et al. (2008) Prediction of compounds' biological function (metabolic pathways) based on functional group composition. Mol Divers 12: 131-137.
56. Tartaglia GG, Pawar AP, Campioni S, Dobson CM, Chiti F, et al. (2008) Prediction of aggregation-prone regions in structured proteins. J Mol Biol 380: 425-436.
57. Lu L, Shi XH, Li SJ, Xie ZQ, Feng YL, et al. (2009) Protein sumoylation sites prediction based on two-stage feature selection. Mol Divers.
58. Peng H, Long F, Ding C, (2005) Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell 27: 1226-1238.
59. Hamodrakas SJ, Liappa C, Iconomidou VA, (2007) Consensus prediction of amyloidogenic determinants in amyloid fibril-forming proteins. Int J Biol Macromol 41: 295-300.