Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Exploring the sequence determinants of amyloid structure using position-specific scoring matrices

A Corrigendum to this article was published on 29 September 2010

An Addendum to this article was published on 29 September 2010

This article has been updated

Abstract

Protein aggregation results in β-sheet–like assemblies that adopt either a variety of amorphous morphologies or ordered amyloid-like structures. These differences in structure also reflect biological differences; amyloid and amorphous β-sheet aggregates have different chaperone affinities, accumulate in different cellular locations and are degraded by different mechanisms. Further, amyloid function depends entirely on a high intrinsic degree of order. Here we experimentally explored the sequence space of amyloid hexapeptides and used the derived data to build Waltz, a web-based tool that uses a position-specific scoring matrix to determine amyloid-forming sequences. Waltz allows users to identify and better distinguish between amyloid sequences and amorphous β-sheet aggregates and allowed us to identify amyloid-forming regions in functional amyloids.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Figure 1: Confirmation of cross-β structure.
Figure 2: Amino acid preference per position of the amyloid hexapeptide motif.
Figure 3: Specificity analysis of Waltz and Tango for amorphous aggregation and amyloid formation.
Figure 4: Cross-β-sheet diffraction pattern and structure.

Accession codes

Accessions

Protein Data Bank

Change history

  • 29 September 2010

    In the original version of this Article published online, we had inadvertently neglected to provide a proper comparison to a tool that should have been shown in Table 1. We apologize for this oversight.

  • 29 September 2010

    In the version of this article initially published, the name of and reference to the algorithm in the right column of Table 1 was incorrect. The correct reference (ref. 40) has been added in the paper. The error has been corrected in the PDF and HTML versions of the article.

References

  1. Chiti, F. et al. Kinetic partitioning of protein folding and aggregation. Nat. Struct. Biol. 9, 137–143 (2002).

    Article  CAS  Google Scholar 

  2. Ventura, S. et al. Short amino acid stretches can mediate amyloid formation in globular proteins: the Src homology 3 (SH3) case. Proc. Natl. Acad. Sci. USA 101, 7258–7263 (2004).

    Article  CAS  Google Scholar 

  3. Carrio, M., Gonzalez-Montalban, N., Vera, A., Villaverde, A. & Ventura, S. Amyloid-like properties of bacterial inclusion bodies. J. Mol. Biol. 347, 1025–1037 (2005).

    Article  CAS  Google Scholar 

  4. Marshall, K.E. & Serpell, L.C. Structural integrity of beta-sheet assembly. Biochem. Soc. Trans. 37, 671–676 (2009).

    Article  CAS  Google Scholar 

  5. Rousseau, F., Schymkowitz, J. & Serrano, L. Protein aggregation and amyloidosis: confusion of the kinds? Curr. Opin. Struct. Biol. 16, 118–126 (2006).

    Article  CAS  Google Scholar 

  6. Chiti, F. & Dobson, C.M. Protein misfolding, functional amyloid, and human disease. Annu. Rev. Biochem. 75, 333–366 (2006).

    Article  CAS  Google Scholar 

  7. Matsumoto, G., Kim, S. & Morimoto, R.I. Huntingtin and mutant SOD1 form aggregate structures with distinct molecular properties in human cells. J. Biol. Chem. 281, 4477–4485 (2006).

    Article  CAS  Google Scholar 

  8. Kopito, R.R. Aggresomes, inclusion bodies and protein aggregation. Trends Cell Biol. 10, 524–530 (2000).

    Article  CAS  Google Scholar 

  9. Huyer, G. et al. A striking quality control subcompartment in Saccharomyces cerevisiae: the endoplasmic reticulum-associated compartment. Mol. Biol. Cell 15, 908–921 (2004).

    Article  CAS  Google Scholar 

  10. Kaganovich, D., Kopito, R. & Frydman, J. Misfolded proteins partition between two distinct quality control compartments. Nature 454, 1088–1095 (2008).

    Article  CAS  Google Scholar 

  11. Arrasate, M., Mitra, S., Schweitzer, E.S., Segal, M.R. & Finkbeiner, S. Inclusion body formation reduces levels of mutant huntingtin and the risk of neuronal death. Nature 431, 805–810 (2004).

    Article  CAS  Google Scholar 

  12. McClellan, A.J., Tam, S., Kaganovich, D. & Frydman, J. Protein quality control: chaperones culling corrupt conformations. Nat. Cell Biol. 7, 736–741 (2005).

    Article  CAS  Google Scholar 

  13. Fowler, D.M., Koulov, A.V., Balch, W.E. & Kelly, J.W. Functional amyloid–from bacteria to humans. Trends Biochem. Sci. 32, 217–224 (2007).

    Article  CAS  Google Scholar 

  14. Wang, X. & Chapman, M.R. Sequence determinants of bacterial amyloid formation. J. Mol. Biol. 380, 570–580 (2008).

    Article  CAS  Google Scholar 

  15. Lopez de la Paz, M. & Serrano, L. Sequence determinants of amyloid fibril formation. Proc. Natl. Acad. Sci. USA 101, 87–92 (2004).

    Article  CAS  Google Scholar 

  16. Makin, O.S., Atkins, E., Sikorski, P., Johansson, J. & Serpell, L.C. Molecular basis for amyloid fibril formation and stability. Proc. Natl. Acad. Sci. USA 102, 315–320 (2005).

    Article  CAS  Google Scholar 

  17. Nelson, R. et al. Structure of the cross-beta spine of amyloid-like fibrils. Nature 435, 773–778 (2005).

    Article  CAS  Google Scholar 

  18. Chiti, F., Stefani, M., Taddei, N., Ramponi, G. & Dobson, C.M. Rationalization of the effects of mutations on peptide and protein aggregation rates. Nature 424, 805–808 (2003).

    Article  CAS  Google Scholar 

  19. Fernandez-Escamilla, A.M., Rousseau, F., Schymkowitz, J. & Serrano, L. Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nat. Biotechnol. 22, 1302–1306 (2004).

    Article  CAS  Google Scholar 

  20. Pawar, A.P. et al. Prediction of “aggregation-prone” and “aggregation-susceptible” regions in proteins associated with neurodegenerative diseases. J. Mol. Biol. 350, 379–392 (2005).

    Article  CAS  Google Scholar 

  21. Sanchez de Groot, N., Pallares, I., Aviles, F.X., Vendrell, J. & Ventura, S. Prediction of “hot spots” of aggregation in disease-linked polypeptides. BMC Struct. Biol. 5, 18 (2005).

    Article  Google Scholar 

  22. Tartaglia, G.G., Cavalli, A., Pellarin, R. & Caflisch, A. Prediction of aggregation rate and aggregation-prone segments in polypeptide sequences. Protein Sci. 14, 2723–2734 (2005).

    Article  CAS  Google Scholar 

  23. Galzitskaya, O.V., Garbuzynskiy, S.O. & Lobanov, M.Y. Prediction of amyloidogenic and disordered regions in protein chains. PLOS Comput. Biol. 2, e177 (2006).

    Article  Google Scholar 

  24. Saiki, M., Konakahara, T. & Morii, H. Interaction-based evaluation of the propensity for amyloid formation with cross-beta structure. Biochem. Biophys. Res. Commun. 343, 1262–1271 (2006).

    Article  CAS  Google Scholar 

  25. Thompson, M.J. et al. The 3D profile method for identifying fibril-forming segments of proteins. Proc. Natl. Acad. Sci. USA 103, 4074–4078 (2006).

    Article  CAS  Google Scholar 

  26. Hamodrakas, S.J., Liappa, C. & Iconomidou, V.A. Consensus prediction of amyloidogenic determinants in amyloid fibril-forming proteins. Int. J. Biol. Macromol. 41, 295–300 (2007).

    Article  CAS  Google Scholar 

  27. Zibaee, S., Makin, O.S., Goedert, M. & Serpell, L.C. A simple algorithm locates beta-strands in the amyloid fibril core of alpha-synuclein, Abeta, and tau using the amino acid sequence alone. Protein Sci. 16, 906–918 (2007).

    Article  CAS  Google Scholar 

  28. Sawaya, M.R. et al. Atomic structures of amyloid cross-beta spines reveal varied steric zippers. Nature 447, 453–457 (2007).

    Article  CAS  Google Scholar 

  29. Osherovich, L.Z., Cox, B.S., Tuite, M.F. & Weissman, J.S. Dissection and design of yeast prions. PLoS Biol. 2, E86 (2004).

    Article  Google Scholar 

  30. Tartaglia, G.G. et al. Prediction of aggregation-prone regions in structured proteins. J. Mol. Biol. 380, 425–436 (2008).

    Article  CAS  Google Scholar 

  31. Hulo, N. et al. The PROSITE database. Nucleic Acids Res. 34, D227–D230 (2006).

    Article  CAS  Google Scholar 

  32. Makin, O.S. & Serpell, L. X-ray diffraction studies of amyloid structure. In Amyloid Proteins: Methods and Protocols (ed. Sigurdsson, E.M.) vol. 299, 67–80 (Humana Press, 2005).

    Article  Google Scholar 

  33. Makin, O.S., Sikorski, P. & Serpell, L. CLEARER: a new tool for the analysis of X-ray fibre diffraction patterns and diffraction simulation from atomic structural models. Appl. Cryst. 40, 966–972 (2007).

    Article  Google Scholar 

  34. Schymkowitz, J. et al. The FoldX web server: an online force field. Nucleic Acids Res. 33, W382–388 (2005).

    Article  CAS  Google Scholar 

  35. Maurer-Stroh, S. & Eisenhaber, F. Refinement and prediction of protein prenylation motifs. Genome Biol. 6, R55 (2005).

    Article  Google Scholar 

  36. Mirny, L. & Shakhnovich, E. Evolutionary conservation of the folding nucleus. J. Mol. Biol. 308, 123–129 (2001).

    Article  CAS  Google Scholar 

  37. Eisenhaber, B., Bork, P. & Eisenhaber, F. Sequence properties of GPI-anchored proteins near the omega-site: constraints for the polypeptide binding site of the putative transamidase. Protein Eng. 11, 1155–1161 (1998).

    Article  CAS  Google Scholar 

  38. Tomii, K. & Kanehisa, M. Analysis of amino acid indices and mutation matrices for sequence comparison and structure prediction of proteins. Protein Eng. 9, 27–36 (1996).

    Article  CAS  Google Scholar 

  39. Eisenhaber, B., Eisenhaber, F., Maurer-Stroh, S. & Neuberger, G. Prediction of sequence signals for lipid post-translational modifications: insights from case studies. Proteomics 4, 1614–1625 (2004).

    Article  CAS  Google Scholar 

  40. Zhang, Z.Q., Chen, H. & Lai, L.H. Identification of amyloid fibril-forming segments based on structure and residue-based statistical potential. Bioinformatics 23, 2218–2225 (2007).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

S.M.-S. was supported by a Marie Curie Intraeuropean fellowship. I.C.M. was supported by a doctorate scholarship from the Boerhinger Ingelheim Fonds, Foundation for Basic Research in Biomedicine and then the Fundação para a Ciência e Tecnologia. L. Serpell acknowledges the grant support from the Alzheimer's Research Trust and the Biotechnology and Biological Sciences Research Council. L. Serrano was partly supported by the EC grant Apopis. J.W.H.S. and F.R. acknowledge grant support from the Federal Office for Scientific Affairs, Belgium (Interuniversity Attraction Pole P6/43), the Fund for Scientific Research, Flanders, the Institute for Innovation by Science & Technology Flanders, the Stichting Alzheimer Onderzoek and the Alzheimer's Research Trust.

Author information

Authors and Affiliations

Authors

Contributions

S.M.-S., F.R., L. Serrano and J.S. devised the methods. S.M.-S. implemented software. J.R., S.M.-S., J.W.H.S. and F.R. performed analysis. M.D., N.K., M.L.d.I.P., I.C.M., K.L.M., A.C. and L. Serpell performed experiments. S.M.-S., J.S. and F.R. wrote the manuscript.

Corresponding authors

Correspondence to Luis Serrano, Joost W H Schymkowitz or Frederic Rousseau.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3, Supplementary Tables 1–3 and Supplementary Notes 1–4 (PDF 1206 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Maurer-Stroh, S., Debulpaep, M., Kuemmerer, N. et al. Exploring the sequence determinants of amyloid structure using position-specific scoring matrices. Nat Methods 7, 237–242 (2010). https://doi.org/10.1038/nmeth.1432

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.1432

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing