Skip to main content

Combination of Theoretical and Experimental Approaches for the Design and Study of Fibril-Forming Peptides

  • Protocol
  • First Online:

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1216))

Abstract

Self-assembling peptides that can form supramolecular structures such as fibrils, ribbons, and nanotubes are of particular interest to modern bionanotechnology and materials science. Their ability to form biocompatible nanostructures under mild conditions through non-covalent interactions offers a big biofabrication advantage. Structural motifs extracted from natural proteins are an important source of inspiration for the rational design of such peptides. Examples include designer self-assembling peptides that correspond to natural coiled-coil motifs, amyloid-forming proteins, and natural fibrous proteins. In this chapter, we focus on the exploitation of structural information from beta-structured natural fibers. We review a case study of short peptides that correspond to sequences from the adenovirus fiber shaft. We describe both theoretical methods for the study of their self-assembly potential and basic experimental protocols for the assessment of fibril-forming assembly.

This is a preview of subscription content, log in via an institution.

Buying options

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

References

  1. Cohen C (1998) Why fibrous proteins are romantic. J Struct Biol 122:3–16

    Article  PubMed  CAS  Google Scholar 

  2. Iconomidou VA, Chryssikos GD, Gionis V, Vriend G, Hoenger A, Hamodrakas S (2001) Amyloid-like fibrils from an 18-residue peptide analogue of a part of the central domain of the B-family of silkmoth chorion proteins. FEBS Lett 499:268–273

    Article  PubMed  CAS  Google Scholar 

  3. Papanikolopoulou K, Schoehn G, Forge V, Forsyth VT, Riekel C, Hernandez JF et al (2005) Amyloid fibril formation from sequences of a natural beta-structured fibrous protein, the adenovirus fiber. J Biol Chem 280:2481–2490

    Article  PubMed  CAS  Google Scholar 

  4. Spiess K, Lammel A, Scheibel T (2010) Recombinant spider silk proteins for applications in biomaterials. Macromol Biosci 10:998–1007

    Article  PubMed  CAS  Google Scholar 

  5. Ryadnov MG, Woolfson DN (2007) Self-assembled templates for polypeptide synthesis. J Am Chem Soc 129:14074–14081

    Article  PubMed  CAS  Google Scholar 

  6. Girotti A, Fernandez-Colino A, Lopez IM, Rodriguez-Cabello JC, Arias FJ (2011) Elastin-like recombinamers: biosynthetic strategies and biotechnological applications. Biotechnol J 6: 1174–1186

    Article  PubMed  CAS  Google Scholar 

  7. Reches M, Gazit E (2006) Molecular self-assembly of peptide nanostructures: mechanism of association and potential uses. Curr Nanosci 2:105–111

    Article  CAS  Google Scholar 

  8. Zhang SG (2003) Fabrication of novel biomaterials through molecular self-assembly. Nat Biotechnol 21:1171–1178

    Article  PubMed  CAS  Google Scholar 

  9. Mitraki A, Miller S, van Raaij MJ (2002) Review: conformation and folding of novel Beta-structural elements in viral fiber proteins—the triple Beta-spiral and triple Beta-helix. J Struct Biol 137:236–247

    Article  PubMed  CAS  Google Scholar 

  10. Mitraki A, Papanikolopoulou K, van Raaij MJ (2006) Natural triple beta-stranded fibrous folds. Adv Protein Chem 74:97–124

    Article  Google Scholar 

  11. van Raaij MJ, Mitraki A, Lavigne G, Cusack S (1999) A triple beta-spiral in the adenovirus fibre shaft reveals a new structural motif for a fibrous protein. Nature 401:935–938

    Article  PubMed  Google Scholar 

  12. Kasotakis E, Mossou E, Adler-Abramovich L, Mitchell EP, Forsyth VT, Gazit E et al (2009) Design of metal-binding sites onto self-assembled peptide fibrils. Biopolymers 92: 164–172

    Article  PubMed  CAS  Google Scholar 

  13. Tamamis P, Kasotakis E, Mitraki A, Archontis G (2009) Amyloid-like self-assembly of peptide sequences from the adenovirus fiber shaft: insights from replica exchange MD simulations. J Phys Chem B 113:15639–15647

    Article  PubMed  CAS  Google Scholar 

  14. Tamamis P, Archontis G (2011) Amyloid-like self-assembly of a dodecapeptide sequence from the adenovirus fiber shaft: perspectives from molecular dynamics simulations. J Non-Cryst Solids 357:717–722

    Article  CAS  Google Scholar 

  15. van Gunsteren WF, Dolenc J (2008) Biomolecular simulation: historical picture and future perspectives. Biochem Soc Trans 36:11–15

    Article  PubMed  Google Scholar 

  16. Karplus M, McCammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 9:646–652

    Article  PubMed  CAS  Google Scholar 

  17. Karplus M, Kuriyan J (2005) Molecular dynamics and protein function. Proc Natl Acad Sci U S A 102:6679–6685

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  18. Adcock SA, McCammon JA (2006) Molecular dynamics: survey of methods for simulating the activity of proteins. Chem Rev 106: 1589–1615

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  19. Brooks BR, Brooks CL III, Mackerell AD Jr, Nilsson L, Petrella RJ, Roux B et al (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30:1545–1614

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  20. Tamamis P, Adler-Abramovich L, Reches M, Marshall K, Sikorski P, Serpell L et al (2009) Self-assembly of phenylalanine oligopeptides: insights from experiments and simulations. Biophys J 96:5020–5029

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  21. Cecchini M, Rao F, Seeber M, Caflisch A (2004) Replica exchange molecular dynamics simulations of amyloid peptide aggregation. J Chem Phys 121:10748–10756

    Article  PubMed  CAS  Google Scholar 

  22. Paci E, Gsponer J, Salvatella X, Vendruscolo M (2004) Molecular dynamics studies of the process of amyloid aggregation of peptide fragments of transthyretin. J Mol Biol 340: 555–569

    Article  PubMed  CAS  Google Scholar 

  23. Mousseau N, Derreumaux P (2005) Exploring the early steps of amyloid peptide aggregation by computers. Acc Chem Res 38:885–891

    Article  PubMed  CAS  Google Scholar 

  24. Ma BY, Nussinov R (2006) Simulations as analytical tools to understand protein aggregation and predict amyloid conformation. Curr Opin Chem Biol 10:445–452

    Article  PubMed  CAS  Google Scholar 

  25. Baumketner A, Shea JE (2007) The structure of the Alzheimer amyloid â 10–35 peptide, probed through replica-exchange molecular dynamics simulations in explicit solvent. J Mol Biol 366:275–285

    Article  PubMed  CAS  Google Scholar 

  26. Hall CK, Wagoner VA (2007) Computational approaches to fibril structure and formation. Methods Enzymol 412:338–365

    Article  Google Scholar 

  27. Hills RD, Brooks CL III (2007) Hydrophobic cooperativity as a mechanism for amyloid nucleation. J Mol Biol 368:894–901

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  28. Knowles TP, Fitzpatrick AW, Meehan S, Mott HR, Vendruscolo M, Dobson CM et al (2007) Role of intermolecular forces in defining material properties of protein nanofibrils. Science 318:1900–1903

    Article  PubMed  CAS  Google Scholar 

  29. Nguyen PH, Li MS, Stock G, Straub JE, Thirumalai D (2007) Monomer adds to preformed structured oligomers of Aâ peptides by a two-stage dock-lock mechanism. Proc Natl Acad Sci U S A 104:111–116

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  30. Song W, Wei G, Mousseau N, Derreumaux P (2008) Self-assembly of the b2-microglobulin NHVTLSQ peptide using a coarse-grained protein model reveals a b-barrel species. J Phys Chem B 112:4410–4418

    Article  PubMed  CAS  Google Scholar 

  31. Tarus B, Straub JE, Thirumalai D (2008) Structures and free energy landscapes of the wild type and mutants of the Abeta (21–30) peptide are determined by an interplay between intrapeptide electrostatic and hydrophobic interactions. J Mol Biol 379:815–829

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  32. Kollman PA (1993) Free energy calculations: applications to chemical and biochemical phenomena. Chem Rev 93:2395–2417

    Article  CAS  Google Scholar 

  33. Massova I, Kollman PA (2000) Combined molecular mechanical and continuum solvent approach (MM-PBSA/GBSA) to predict ligand binding. Perspect Drug Discov Des 18:113–135

    Article  CAS  Google Scholar 

  34. Archontis G, Simonson T, Moras D, Karplus M (1998) Specific amino acid recognition by aspartyl-tRNA synthetase studied by free energy simulations. J Mol Biol 275:823–846

    Article  PubMed  CAS  Google Scholar 

  35. Archontis G, Simonson T, Karplus M (2001) Binding free energies and free energy components from molecular dynamics and Poisson-Boltzmann calculations. Application to amino acid recognition by aspartyl-tRNA synthetase. J Mol Biol 306:307–327

    Article  PubMed  CAS  Google Scholar 

  36. Archontis G, Watson KÁ, Xie Q, Andreou G, Chrysina E, Zographos SE et al (2005) Molecular recognition and relative binding of glucopyranose spirohydantoin analogues to glycogen phosphorylase: a free energy perturbation study. Proteins 61:984–998

    Article  PubMed  CAS  Google Scholar 

  37. Tamamis P, Morikis D, Floudas CA, Archontis G (2010) Species specificity of the complement inhibitor compstatin investigated by all-atom molecular dynamics simulations. Proteins 78: 2655–2667

    PubMed  CAS  PubMed Central  Google Scholar 

  38. Tamamis P, Pierou P, Mytidou S, Floudas CA, Morikis D, Archontis G (2011) Design of a modified mouse protein with ligand binding properties of its human analog by molecular dynamics simulations: the case of C3 inhibition by compstatin. Proteins 79:3166–3179

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  39. Kieslich C, Tamamis P, Gorham RD Jr, López de Victoria A, Sausman N, Archontis G et al (2012) Exploring protein-protein and protein-ligand interactions in the immune system using molecular dynamics and continuum electrostatics. Curr Phys Chem 2:324–343

    Article  CAS  Google Scholar 

  40. Tamamis P, López de Victoria A, Gorham RD Jr, Bellows ML, Pierou P, Floudas CA et al (2012) Molecular dynamics simulations in drug design: new generations of compstatin analogs. Chem Biol Drug Des 79:703–718

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  41. López de Victoria A, Tamamis P, Kieslich CA, Morikis D (2012) Insights into the structure, correlated motions, and electrostatic properties of two HIV-1 gp120 V3 loops. PLoS One 7:e49925

    Article  PubMed  PubMed Central  Google Scholar 

  42. Derreumaux P, Mousseau N (2007) Coarse-grained protein molecular dynamics simulations. J Chem Phys 126:025101

    Article  PubMed  Google Scholar 

  43. Melquiond A, Dong X, Mousseau N, Derreumaux P (2008) Role of the region 23–28 in Abeta fibril formation: insights from simulations of the monomers and dimers of Alzheimer’s peptides Abeta 40 and Abeta 42. Curr Alzheimer Res 5:244–250

    Article  PubMed  CAS  Google Scholar 

  44. Han W, Schulten K (2012) Further optimization of a hybrid united-atom and coarse-grained force field for folding simulations: improved backbone hydration and interactions between charged side chains. J Chem Theory Comput 8:4413–4424

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  45. Still WC, Tempczyk A, Hawley RC, Hendrickson T (1990) Semianalytical treatment of solvation for molecular mechanics and dynamics. J Am Chem Soc 112:6127–6129

    Article  CAS  Google Scholar 

  46. Bashford D, Case DA (2000) Generalized born models of macromolecular solvation effects. Annu Rev Phys Chem 51:129–152

    Article  PubMed  CAS  Google Scholar 

  47. Im W, Lee MS, Brooks CL III (2003) Generalized born model with a simple smoothing function. J Comput Chem 24:1691–1702

    Article  PubMed  CAS  Google Scholar 

  48. Feig M, Im W, Brooks CL III (2004) Implicit solvation based on generalized born theory in different dielectric environments. J Chem Phys 190:903

    Article  Google Scholar 

  49. Chen J, Im W, Brooks CL III (2006) Balancing solvation and intramolecular interactions: towards a self-consistent generalized born force field. J Am Chem Soc 128:3728–3736

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  50. Chen J, Brooks CL III, Khandogin J (2008) Recent advances in implicit solvent-based methods for biomolecular simulations. Curr Opin Struct Biol 2:140–148

    Article  Google Scholar 

  51. Haberthür U, Caflisch AJ (2008) FACTS: fast analytical continuum treatment of solvation. Comput Chem 29:701–715

    Article  Google Scholar 

  52. MacKerell AD Jr, Bashford D, Bellott M, Dunbrack RL Jr, Evanseck JD, Field MJ et al (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102:3586–3616

    Article  PubMed  CAS  Google Scholar 

  53. Neria E, Fischer S, Karplus M (1996) Simulation of activation free energies in molecular systems. J Chem Phys 105:1902–1921

    Article  CAS  Google Scholar 

  54. Buck M, Bouguet-Bonnet S, Pastor RW, MacKerell AD (2005) Importance of the CMAP correction to the CHARMM22 protein force field: dynamics of Hen Lysozyme. Biophys J 90:L36–L38

    Article  PubMed  PubMed Central  Google Scholar 

  55. Pieridou G, Avgousti-Menelaou C, Tamamis P, Archontis G, Hayes SC (2011) UV resonance Raman study of TTR (105–115) structural evolution as a function of temperature. J Phys Chem B 115:4088–4098

    Article  PubMed  CAS  Google Scholar 

  56. Swendsen R, Wang J (1987) Non-universal critical dynamics in Monte Carlo simulations. Phys Rev Lett 57:2607–2609

    Article  Google Scholar 

  57. Hukushima K, Nemoto K (1996) Exchange Monte Carlo method and application to spin glass simulation. J Phys Soc Jpn 65:1604–1608

    Article  CAS  Google Scholar 

  58. Hansmann U (1997) Parallel tempering algorithm for conformational studies of biological molecules. Chem Phys Lett 281:140–150

    Article  CAS  Google Scholar 

  59. Sugita Y, Okamoto Y (1999) Replica-exchange molecular dynamics method for protein folding. Chem Phys Lett 314:141–151

    Article  CAS  Google Scholar 

  60. Sanbonmatsu KY, Garcia AE (2002) Structure of Met-enkephalin in explicit aqueous solution using replica exchange molecular dynamics. Proteins 46:225–234

    Article  PubMed  CAS  Google Scholar 

  61. Nymeyer H, Gnanakaran S, Garcia A (2004) Atomic simulations of protein folding, using the replica exchange algorithm. Methods Enzymol 30:119–149

    Article  Google Scholar 

  62. Rao F, Caflisch A (2003) Replica exchange molecular dynamics simulations of reversible folding. J Chem Phys 119:4035

    Article  CAS  Google Scholar 

  63. Rosta E, Buchete N-V, Hummer G (2009) Thermostat artifacts in replica exchange molecular dynamics simulations. J Chem Theory Comput 5:1393–1399

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  64. Kim J, Keyes T, Straub J (2010) Generalized replica exchange method. J Chem Phys 132: 224107

    Article  PubMed  PubMed Central  Google Scholar 

  65. Lee MS, Olson MA (2011) Comparison of two adaptive temperature-based replica exchange methods applied to a sharp phase transition of protein unfolding-folding. J Chem Phys 134: 244111

    Article  PubMed  Google Scholar 

  66. Frishman D, Argos P (1995) Knowledge-based secondary structure assignment. Proteins 23: 566–579

    Article  PubMed  CAS  Google Scholar 

  67. Kabsch W, Sander C (1983) Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22:2577–2637

    Article  PubMed  CAS  Google Scholar 

  68. Karpen ME, Tobias DT, Brooks CL III (1993) Statistical clustering techniques for analysis of long molecular dynamics trajectories. I: analysis of 2.2 ns trajectories of YPGDV. Biochemistry 32:412–420

    Article  PubMed  CAS  Google Scholar 

  69. Chandrasekhar S (1992) Liquid crystals. Cambridge University Press, Cambridge

    Book  Google Scholar 

  70. de Gennes PG, Prost J (1993) The physics of liquid crystals, 2nd edn. Oxford University Press, Oxford

    Google Scholar 

  71. Berardi R, Muccioli L, Zannoni C (2004) Can nematic transitions be predicted by atomistic simulations? A computational study of the odd-even effect. Chem Phys Chem 5: 104–111

    PubMed  CAS  Google Scholar 

  72. Seeber M, Cecchini M, Rao F, Settanni G, Caflisch A (2007) WORDOM: a program for efficient analysis of molecular dynamics simulations. Bioinformatics 23:2625–2627

    Article  PubMed  CAS  Google Scholar 

  73. Tamamis P, Terzaki K, Kassinopoulos M, Mastrogiannis L, Mossou E, Forsyth VT et al (2014) Self-assembly of an aspartate-rich sequence from the adenovirus fibre shaft: insights from molecular dynamics simulations and experiments. J Phys Chem B 118:1765–1774

    Google Scholar 

Download references

Acknowledgments

GA and PhT acknowledge financial support from the University of Cyprus program “Computational Investigation of Peptide Sequences from the Adenovirus and Reovirus Fiber Shaft: Insights on the Self-assembly of Peptide-based Nanostructures and the Stability of the Triple-beta Spiral Fold,” and the program UPGRADE/0609/11, “Self-Assembly and Folding of Biologically-inspired Peptide Sequences From Natural Fibrous Proteins: Insights From Highly-Intensive Computational Studies” that is co-funded by Desmi 2009–2010 of the Cyprus Research Promotion Foundation, the Republic of Cyprus, and the European Regional Development Fund. Simulations were conducted in Linux clusters of the Biophysics group, partly financed through program UPGRADE/0609/11. E.K. and A.M. acknowledge funding form the European Union (STREP NMP-CT-2006-033256, “BeNatural”).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anna Mitraki .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this protocol

Cite this protocol

Tamamis, P., Kasotakis, E., Archontis, G., Mitraki, A. (2014). Combination of Theoretical and Experimental Approaches for the Design and Study of Fibril-Forming Peptides. In: Köhler, V. (eds) Protein Design. Methods in Molecular Biology, vol 1216. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1486-9_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-1486-9_3

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1485-2

  • Online ISBN: 978-1-4939-1486-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics