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Annual Review of Physical Chemistry

Volume 69, 2018

Chemical Kinetics for Bridging Molecular Mechanisms and Macroscopic Measurements of Amyloid Fibril Formation

Abstract

Understanding how normally soluble peptides and proteins aggregate to form amyloid fibrils is central to many areas of modern biomolecular science, ranging from the development of functional biomaterials to the design of rational therapeutic strategies against increasingly prevalent medical conditions such as Alzheimer's and Parkinson's diseases. As such, there is a great need to develop models to mechanistically describe how amyloid fibrils are formed from precursor peptides and proteins. Here we review and discuss how ideas and concepts from chemical reaction kinetics can help to achieve this objective. In particular, we show how a combination of theory, experiments, and computer simulations, based on chemical kinetics, provides a general formalism for uncovering, at the molecular level, the mechanistic steps that underlie the phenomenon of amyloid fibril formation.

Keyword(s): Alzheimer's disease, coarse-grained simulations, computer simulations, drug discovery, global fit, inhibition, master equation, neurodegenerative diseases, oligomers, protein aggregation, protein misfolding, rate law, reaction order, scaling exponent, secondary nucleation, self-assembly
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2018-04-20
2024-04-18
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Literature Cited

  1. Dobson CM. 1.  1999. Protein misfolding, evolution and disease. Trends Biochem. Sci. 24:329–32 [Google Scholar]
  2. Baldwin AJ, Knowles TPJ, Tartaglia GG, Fitzpatrick AW, Devlin GL. 2.  et al. 2011. Metastability of native proteins and the phenomenon of amyloid formation. J. Am. Chem. Soc. 133:14160–63 [Google Scholar]
  3. Fitzpatrick AWP, Debelouchina GT, Bayro MJ, Clare DK, Caporini MA. 3.  et al. 2013. Atomic structure and hierarchical assembly of a cross-β amyloid fibril. PNAS 110:5468–73 [Google Scholar]
  4. Arosio P, Knowles TPJ, Linse S. 4.  2015. On the lag phase in amyloid fibril formation. Phys. Chem. Chem. Phys. 17:7606–18 [Google Scholar]
  5. Jiménez JL, Nettleton EJ, Bouchard M, Robinson CV, Dobson CM, Saibil HR. 5.  2001. The protofilament structure of insulin amyloid fibrils. PNAS 99:9196–201 [Google Scholar]
  6. Fändrich M. 6.  2007. On the structural definition of amyloid fibrils and other polypeptide aggregates. CMLS 64:2066–78 [Google Scholar]
  7. Eisenberg D, Jucker M. 7.  2012. The amyloid state of proteins in human diseases. Cell 148:1188–203 [Google Scholar]
  8. Lührs T, Ritter C, Adrian M, Riek-Loher D, Bohrmann B. 8.  et al. 2005. 3D structure of Alzheimer's amyloid-β (1–42) fibrils. PNAS 102:17342–47 [Google Scholar]
  9. Sawaya MR, Sambashivan S, Nelson R, Ivanova MI, Sievers SA. 9.  et al. 2007. Atomic structures of amyloid cross-β spines reveal varied steric zippers. Nature 447:453–57 [Google Scholar]
  10. Wasmer C, Lange A, Van Melckebeke H Siemer AB, Riek R, Meier BH. 10.  2008. Amyloid fibrils of the HET-s(218–289) prion form a β solenoid with a triangular hydrophobic core. Science 319:1523–26 [Google Scholar]
  11. Jaroniec CP, MacPhee CE, Bajaj VS, McMahon MT, Dobson CM, Griffin RG. 11.  2004. High-resolution molecular structure of a peptide in an amyloid fibril determined by magic angle spinning NMR spectroscopy. PNAS 101:711–16 [Google Scholar]
  12. Kodali R, Wetzel R. 12.  2007. Polymorphism in the intermediates and products of amyloid assembly. Curr. Opin. Struct. Biol. 17:48–57 [Google Scholar]
  13. Makin OS, Serpell LC. 13.  2005. Structures for amyloid fibrils. FEBS J 272:5950–61 [Google Scholar]
  14. Knowles TPJ, Fitzpatrick AW, Meehan S, Mott HR, Vendruscolo M. 14.  et al. 2007. Role of intermolecular forces in defining material properties of protein nanofibrils. Science 318:1900–3 [Google Scholar]
  15. Gazit E. 15.  2002. The “correctly folded” state of proteins: is it a metastable state?. Angew. Chem. Int. Ed. 41:257–59 [Google Scholar]
  16. Chiti F, Dobson CM. 16.  2006. Protein misfolding, functional amyloid, and human disease. Annu. Rev. Biochem. 75:333–66 [Google Scholar]
  17. Chiti F, Dobson CM. 17.  2017. Protein misfolding, functional amyloid, and human disease: a summary of progress over the last decade. Annu. Rev. Biochem. 86:27–68 [Google Scholar]
  18. Dobson CM. 18.  2017. The amyloid phenomenon and its links with human disease. Cold Spring Harb. Perspect. Biol. 9:a023648 [Google Scholar]
  19. Knowles TPJ, Vendruscolo M, Dobson CM. 19.  2014. The amyloid state and its association with protein misfolding diseases. Nat. Rev. Mol. Cell Biol. 15:384–96 [Google Scholar]
  20. Walsh DM, Selkoe DJ. 20.  2007. Aβ oligomers—a decade of discovery. J. Neurochem. 101:1172–84 [Google Scholar]
  21. Selkoe DJ, Hardy J. 21.  2016. The amyloid hypothesis of Alzheimer's disease at 25 years. EMBO Mol. Med. 8:595–608 [Google Scholar]
  22. Hardy JA, Higgins GA. 22.  1992. Alzheimer's disease: the amyloid cascade hypothesis. Science 256:184–85 [Google Scholar]
  23. Selkoe DJ. 23.  2003. Folding proteins in fatal ways. Nature 426:900–4 [Google Scholar]
  24. Hardy J, Selkoe DJ. 24.  2002. The amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics. Science 297:353–56 [Google Scholar]
  25. 25. Alzheimer's Assoc. 2014. Alzheimer's disease facts and figures. Alzheimer's Dement 10:e47–e92 [Google Scholar]
  26. Dauer W, Przedborski S. 26.  2003. Parkinson's disease: mechanisms and models. Neuron 39:889–909 [Google Scholar]
  27. DiFiglia M, Sapp E, Chase KO, Davies SW, Bates GP. 27.  1997. Aggregation of huntingtin in neuronal intranuclear inclusions and dystrophic neurites in brain. Science 277:1990–93 [Google Scholar]
  28. Ferrone FA, Hofrichter J, Eaton WA. 28.  1985. Kinetics of sickle hemoglobin polymerization. II. A double nucleation mechanism. J. Mol. Biol. 183:611–31 [Google Scholar]
  29. Rhoades E, Agarwal J, Gafni A. 29.  2000. Aggregation of an amyloidogenic fragment of human islet amyloid polypeptide. Biochim. Biophys. Acta 1476:230–38 [Google Scholar]
  30. Cohen FE, Kelly JW. 30.  2003. Therapeutic approaches to protein-misfolding diseases. Nature 426:905–9 [Google Scholar]
  31. Arosio P, Vendruscolo M, Dobson CM, Knowles TPJ. 31.  2014. Chemical kinetics for drug discovery to combat protein aggregation diseases. Trends Pharmacol. Sci. 35:127–35 [Google Scholar]
  32. Cremades N, Dobson CM. 32.  2017. The contribution of biophysical and structural studies of protein self-assembly to the design of therapeutic strategies for amyloid diseases. Neurobiol. Dis. 109:B178–90 [Google Scholar]
  33. Fowler DM, Koulov AV, Balch WE, Kelly JW. 33.  2007. Functional amyloid—from bacteria to humans. Trends Biochem. Sci. 32:217–24 [Google Scholar]
  34. Maji SK, Perrin MH, Sawaya MR, Jessberger S, Vadodaria K. 34.  et al. 2009. Functional amyloids as natural storage of peptide hormones in pituitary secretory granules. Science 325:328–32 [Google Scholar]
  35. McGlinchey RP, Shewmaker F, McPhie P, Monterroso B, Thurber K, Wickner RB. 35.  2009. The repeat domain of the melanosome fibril protein Pmel17 forms the amyloid core promoting melanin synthesis. PNAS 106:13731–36 [Google Scholar]
  36. Romero D. 36. Aguilar C, Losick R, Kolter R. 2010. Amyloid fibers provide structural integrity to Bacillus subtilis biofilms. PNAS 107:2230–34 [Google Scholar]
  37. Oh J, Kim JG, Jeon E, Yoo CH, Moon JS. 37.  et al. 2007. Amyloidogenesis of type III–dependent harpins from plant pathogenic bacteria. J. Biol. Chem. 282:13601–9 [Google Scholar]
  38. Collinson SK, Emödy L, Müller KH, Trust TJ, Kay WW. 38.  1991. Purification and characterization of thin, aggregative fimbriae from Salmonella enteritidis. . J. Bacteriol. 173:4773–81 [Google Scholar]
  39. Barnhart MM, Chapman MR. 39.  2006. Curli biogenesis and function. Annu. Rev. Microbiol. 60:131–47 [Google Scholar]
  40. Sunde M, Kwan AH, Templeton MD, Beever RE, MacKay JP. 40.  2008. Structural analysis of hydrophobins. Micron 39:773–84 [Google Scholar]
  41. Iconomidou VA, Vriend G, Hamodrakas SJ. 41.  2000. Amyloids protect the silkmoth oocyte and embryo. FEBS Lett 479:141–45 [Google Scholar]
  42. Podrabsky JE, Carpenter JF, Hand SC. 42.  2001. Survival of water stress in annual fish embryos: dehydration avoidance and egg amyloid fibers. Am. J. Physiol. Regul. Integr. Comp. Physiol. 280:R123–31 [Google Scholar]
  43. Knowles TPJ, Buehler MJ. 43.  2011. Nanomechanics of functional and pathological amyloid materials. Nat. Nanotechnol. 6:469–79 [Google Scholar]
  44. Gazit E. 44.  2007. Self-assembled peptide nanostructures: the design of molecular building blocks and their technological utilization. Chem. Soc. Rev. 36:1263–69 [Google Scholar]
  45. Knowles TPJ, Oppenheim TW, Buell AK, Chirgadze DY, Welland ME. 45.  2010. Nanostructured films from hierarchical self-assembly of amyloidogenic proteins. Nat. Nanotechnol. 5:204–7 [Google Scholar]
  46. Li C, Adamcik J, Mezzenga R. 46.  2012. Biodegradable nanocomposites of amyloid fibrils and graphene with shape-memory and enzyme-sensing properties. Nat. Nanotechnol. 7:421–27 [Google Scholar]
  47. Li C, Bolisetty S, Mezzenga R. 47.  2013. Hybrid nanocomposites of gold single-crystal platelets and amyloid fibrils with tunable fluorescence, conductivity, and sensing properties. Adv. Mater. 25:3694–700 [Google Scholar]
  48. Li C, Alam MM, Bolisetty S, Adamcik J, Mezzenga R. 48.  2011. New biocompatible thermo-reversible hydrogels from PNiPAM-decorated amyloid fibrils. Chem. Commun. 47:2913–15 [Google Scholar]
  49. Wei G, Su Z, Reynolds NP, Arosio P, Hamley IW. 49.  et al. 2017. Self-assembling peptide and protein amyloids: from structure to tailored function in nanotechnology. Chem. Soc. Rev. 46:4661–708 [Google Scholar]
  50. Ouberai MM, Gomes dos Santos AL, Kinna S, Madalli S, Hornigold DC. 50.  et al. 2017. Controlling the bioactivity of a peptide hormone in vivo by reversible self-assembly. Nat. Commun. 8:1026 [Google Scholar]
  51. Mezzenga R, Fischer P. 51.  2013. The self-assembly, aggregation and phase transitions of food protein systems in one, two and three dimensions. Rep. Prog. Phys. 76:046601 [Google Scholar]
  52. Müller P. 52.  1994. Glossary of terms used in physical organic chemistry (IUPAC recommendations 1994). Pure Appl. Chem. 66:1077–184 [Google Scholar]
  53. Meisl G, Yang X, Hellstrand E, Frohm B, Kirkegaard JB. 53.  et al. 2014. Differences in nucleation behavior underlie the contrasting aggregation kinetics of the Aβ40 and Aβ42 peptides. PNAS 1119384–89
  54. Michaels TCT, Garcia GA, Knowles TPJ. 54.  2014. Asymptotic solutions of the Oosawa model for the length distribution of biofilaments. J. Chem. Phys. 140:194906 [Google Scholar]
  55. Galvagnion C, Buell AK, Meisl G, Michaels TCT, Vedruscolo M. 55.  et al. 2015. Lipid vesicles trigger α-synuclein aggregation by stimulating primary nucleation. Nat. Chem. Biol. 11:229–34 [Google Scholar]
  56. Meisl G, Kirkegaard JB, Arosio P, Michaels TCT, Vendruscolo M. 56.  et al. 2016. Molecular mechanisms of protein aggregation from global fitting of kinetic models. Nat. Protoc. 11:252–72 [Google Scholar]
  57. Michaels TCT, Knowles TPJ. 57.  2014. Mean-field master equation formalism for biofilament growth. Am. J. Phys. 82:476–83 [Google Scholar]
  58. Krapivsky PL, Redner S, Ben-Naim E. 58.  2010. A Kinetic View of Statistical Physics Cambridge, UK: Cambridge Univ. Press
  59. Knowles TPJ, Waudby CA, Devlin GL, Cohen SIA, Aguzzi A. 59.  et al. 2009. An analytical solution to the kinetics of breakable filament assembly. Science 326:1533–37 [Google Scholar]
  60. Cohen SIA, Vendruscolo M, Welland ME, Dobson CM, Terentjev EM, Knowles TPJ. 60.  2011. Nucleated polymerization with secondary pathways. I. Time evolution of the principal moments. J. Chem. Phys. 135:065105 [Google Scholar]
  61. Šarić A, Michaels TCT, Zaccone A, Knowles TPJ, Frenkel D. 61.  2016. Kinetics of spontaneous filament nucleation via oligomers: insights from theory and simulations. J. Chem. Phys. 145:211926 [Google Scholar]
  62. Cohen SIA, Vendruscolo M, Dobson CM, Knowles TPJ. 62.  2012. From macroscopic measurements to microscopic mechanisms of protein aggregation. J. Mol. Biol. 421:160–71 [Google Scholar]
  63. Cohen SIA, Vendruscolo M, Dobson CM, Knowles TPJ. 63.  2011. Nucleated polymerization with secondary pathways. II. Determination of self-consistent solutions to growth processes described by non-linear master equations. J. Chem. Phys. 135:065106 [Google Scholar]
  64. Cohen SIA, Vendruscolo M, Dobson CM, Knowles TPJ. 64.  2011. Nucleated polymerization with secondary pathways. III. Equilibrium behavior and oligomer population. J. Chem. Phys. 135:065107 [Google Scholar]
  65. Michaels TCT, Garcia GA, Knowles TPJ. 65.  2014. Asymptotic solutions of the Oosawa model for the length distribution of biofilaments. J. Chem. Phys. 140:194906 [Google Scholar]
  66. Michaels TCT, Yde P, Willis JC, Jensen MH, Otzen D. 66.  et al. 2015. The length distribution of frangible biofilaments. J. Chem. Phys. 143:164901 [Google Scholar]
  67. Michaels TCT, Lazell HW, Arosio P, Knowles TPJ. 67.  2015. Dynamics of protein aggregation and oligomer formation governed by secondary nucleation. J. Chem. Phys. 143:054901 [Google Scholar]
  68. Michaels TCT, Knowles TPJ. 68.  2015. Kinetic theory of protein filament growth: self-consistent methods and perturbative techniques. Int. J. Mod. Phys. B 29:1530002 [Google Scholar]
  69. Khalil HK. 69.  1996. Nonlinear Systems Upper Saddle River, NJ: Prentice-Hall
  70. Bishop MF, Ferrone FA. 70.  1984. Kinetics of nucleation-controlled polymerization. A perturbation treatment for use with a secondary pathway. Biophys. J. 46:631–44 [Google Scholar]
  71. Michaels TCT, Knowles TPJ. 71.  2014. Role of filament annealing in the kinetics and thermodynamics of nucleated polymerization. J. Chem. Phys. 140:214904 [Google Scholar]
  72. Dear AJ, Michaels TCT, Knowles TPJ. 72.  2016. Dynamics of heteromolecular filament formation. J. Chem. Phys. 145:175101 [Google Scholar]
  73. Michaels TCT, Cohen SIA, Vendruscolo M, Dobson CM, Knowles TPJ. 73.  2016. Hamiltonian dynamics of protein filament formation. Phys. Rev. Lett. 116:038101 [Google Scholar]
  74. Morris AM, Watzky MA, Finke RG. 74.  2009. Protein aggregation kinetics, mechanism, and curve-fitting: a review of the literature. Biochim. Biophys. Acta 1794:375–97 [Google Scholar]
  75. Morris AM, Watzky MA, Agar JN, Finke RG. 75.  2008. Fitting neurological protein aggregation kinetic data via a 2-step, minimal/“Ockham's razor” model: the Finke–Watzky mechanism of nucleation followed by autocatalytic surface growth. Biochemistry 47:2413–27 [Google Scholar]
  76. Meisl G, Rajah L, Cohen SIA, Pfammater M, Šarić A. 76.  et al. 2017. Scaling behaviour and rate-determining steps in filamentous self-assembly. Chem. Sci. 8:7087–97 [Google Scholar]
  77. Oosawa F, Asakura S. 77.  1975. Thermodynamics of the Polymerization of Protein London: Academic
  78. Westermark GT, Johnson KH, Westermark P. 78.  1999. Amyloid, Prions, and Other Protein Aggregates Amsterdam: Elsevier
  79. Hellstrand E, Boland B, Walsh DM, Linse S. 79.  2010. Amyloid β-protein aggregation produces highly reproducible kinetic data and occurs by a two-phase process. ACS Chem. Neurosci. 1:13–18 [Google Scholar]
  80. Cohen SIA, Linse S, Luheshi LM, Hellstrand E, White DA. 80.  et al. 2013. Proliferation of amyloid-β42 aggregates occurs through a secondary nucleation mechanism. PNAS 110:9758–63 [Google Scholar]
  81. Bolognesi B, Cohen SIA, Aran Terol P, Esbjorner EK, Giorgetti S. 81.  et al. 2013. Single point mutations induce a switch in the molecular mechanism of the aggregation of the Alzheimer's disease associated Aβ42 peptide. ACS Chem. Biol. 9:378–82 [Google Scholar]
  82. Gaspar R, Meisl G, Buell A, Young L, Kaminski CF. 82.  et al. 2017. Secondary nucleation of monomers on fibril surface dominates α-synuclein aggregation and provides autocatalytic amyloid amplification. Q. Rev. Biophys. 50:e6 [Google Scholar]
  83. Iljina M, Garcia GA, Dear AJ, Flint J, Narayan P. 83.  et al. 2016. Quantitative analysis of co-oligomer formation by amyloid-β peptide isoforms. Sci. Rep. 6:28658 [Google Scholar]
  84. Knowles TPJ, White DA, Abate AR, Agresti JJ, Cohen SIA. 84.  et al. 2011. Observation of spatial propagation of amyloid assembly from single nuclei. PNAS 108:14746–51 [Google Scholar]
  85. Szavits-Nossan J, Eden K, Morris RJ, MacPhee CE, Evans MR, Allen RJ. 85.  2014. Inherent variability in the kinetics of autocatalytic protein self-assembly. Phys. Rev. Lett. 113:098101 [Google Scholar]
  86. Michaels TCT, Dear AJ, Kirkegaard JB, Saar KL, Weitz DA, Knowles TPJ. 86.  2016. Fluctuations in the kinetics of linear protein self-assembly. Phys. Rev. Lett. 116:258103 [Google Scholar]
  87. Cohen SIA, Rajah L, Yoon CH, Buell AK, White DA. 87.  et al. 2014. Spatial propagation of protein polymerization. Phys. Rev. Lett. 112:098101 [Google Scholar]
  88. Morriss-Andrews A, Shea J-E. 88.  2015. Computational studies of protein aggregation: methods and applications. Annu. Rev. Phys. Chem. 66:643–66 [Google Scholar]
  89. Wu C, Shea J-E. 89.  2011. Coarse-grained models for protein aggregation. Curr. Opin. Struct. Biol. 21:209–20 [Google Scholar]
  90. Nagel-Steger L, Owen MC, Strodel B. 90.  2016. An account of amyloid oligomers: facts and figures obtained from experiments and simulations. Chem. Biochem. 17:657–76 [Google Scholar]
  91. Zhang J, Muthukumar M. 91.  2009. Simulations of nucleation and elongation of amyloid fibrils. J. Chem. Phys. 130:035102 [Google Scholar]
  92. Ruff KM, Khan SJ, Pappu RV. 92.  2014. A coarse-grained model for polyglutamine aggregation modulated by amphipathic flanking sequences. Biophys. J. 107:1226–35 [Google Scholar]
  93. Ilie IM, den Otter WK, Briels WJ. 93.  2016. A coarse grained protein model with internal degrees of freedom. Application to α-synuclein aggregation. J. Chem. Phys. 144:085103 [Google Scholar]
  94. Bieler NS, Knowles TPJ, Frenkel D, Vácha R. 94.  2012. Connecting macroscopic observables and microscopic assembly events in amyloid formation using coarse grained simulations. PLOS Comput. Biol. 8:10e1002692 [Google Scholar]
  95. Vácha R, Linse S, Lund M. 95.  2014. Surface effects on aggregation kinetics of amyloidogenic peptides. J. Am. Chem. Soc. 136:11776–82 [Google Scholar]
  96. Šarić A, Chebaro YC, Knowles TPJ, Frenkel D. 96.  2014. Crucial role of nonspecific interactions in amyloid nucleation. PNAS 111:17869–74 [Google Scholar]
  97. Šarić A, Buell AK, Meisl G, Michaels TCT, Dobson CM. 97.  et al. 2016. Physical determinants for self-replication of amyloid fibrils. Nat. Phys. 12:874–80 [Google Scholar]
  98. Ferreira ST, Vieira MNN, De Felice FG. 98.  2007. Soluble protein oligomers as emerging toxins in Alzheimer's and other amyloid diseases. IUBMB Life 59:332–45 [Google Scholar]
  99. Patrick G. 99.  2009. An Introduction to Medicinal Chemistry Oxford, UK: Oxford Univ. Press
  100. Cohen P, Alessi DR. 100.  2013. Kinase drug discovery—what's next in the field?. ACS Chem. Biol. 8:96–104 [Google Scholar]
  101. Necula M, Kayed R, Milton S, Glabe CG. 101.  2007. Small molecule inhibitors of aggregation indicate that amyloid β oligomerization and fibrillization pathways are independent and distinct. J. Biol. Chem. 282:10311–24 [Google Scholar]
  102. Aguzzi A, O'Connor T. 102.  2010. Protein aggregation diseases: pathogenicity and therapeutic perspectives. Nat. Rev. Drug Discov. 9:237–48 [Google Scholar]
  103. Cummings J, Zhong K, Bernick C. 103.  2014. The Cleveland Clinic Lou Ruvo Center for Brain Health: keeping memory alive. J. Alzheimers Dis. 38:103–9 [Google Scholar]
  104. Huang Y, Mucke L. 104.  2012. Alzheimer mechanisms and therapeutic strategies. Cell 148:1204–22 [Google Scholar]
  105. Becker RE, Greig NH, Giacobini E, Schneider LS, Ferrucci L. 105.  2014. A new roadmap for drug development for Alzheimer's disease. Nat. Rev. Drug Discov. 13:156 [Google Scholar]
  106. Amijee H, Scopes DI. 106.  2009. The quest for small molecules as amyloid inhibiting therapies for Alzheimer's disease. J. Alzheimers Dis. 17:33–47 [Google Scholar]
  107. Mangialasche F, Solomon A, Winblad B, Mecocci P, Kivipelto M. 107.  2010. Alzheimer's disease: clinical trials and drug development. Lancet Neurol 9:702–16 [Google Scholar]
  108. Bulic B, Pickhardt M, Schmidt B, Mandelkow EM, Waldmann H, Mandelkow E. 108.  2009. Development of tau aggregation inhibitors for Alzheimer's disease. Angew. Chem. Int. Ed. 48:1740–52 [Google Scholar]
  109. Lashuel HA, Overk CR, Oueslati A, Masliah E. 109.  2013. The many faces of α-synuclein: from structure and toxicity to therapeutic target. Nat. Rev. Neurosci. 14:38–48 [Google Scholar]
  110. Nie Q, Du XG, Geng MY. 110.  2011. Small molecule inhibitors of amyloid β peptide aggregation as a potential therapeutic strategy for Alzheimer's disease. Acta Pharmacol. Sin. 32:545–51 [Google Scholar]
  111. Karran E, Hardy J. 111.  2014. A critique of the drug discovery and phase 3 clinical programs targeting the amyloid hypothesis for Alzheimer disease. Ann. Neurol. 76:185–205 [Google Scholar]
  112. Cremades N, Chen SW, Dobson CM. 112.  2017. Structural characteristics of α-synuclein oligomers. Int. Rev. Cell Mol. Biol. 329:79–143 [Google Scholar]
  113. Monsellier E, Chiti F. 113.  2007. Prevention of amyloid-like aggregation as a driving force of protein evolution. EMBO Rep 8:737–42 [Google Scholar]
  114. Arosio P, Michaels TCT, Linse S, Månsson C, Emanuelsson C. 114.  et al. 2016. Kinetic analysis reveals the diversity of microscopic mechanisms through which molecular chaperones suppress amyloid formation. Nat. Commun. 7:10948 [Google Scholar]
  115. Habchi J, Chia S, Limbocker R, Mannini B, Ahn M. 115.  et al. 2016. Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer's disease. PNAS 114:E200–8 [Google Scholar]
  116. Cohen SIA, Arosio P, Presto J, Kurudenkandy FR, Biverstal H. 116.  et al. 2015. A molecular chaperone breaks the catalytic cycle that generates toxic Aβ oligomers. Nat. Struct. Mol. Biol. 22:207–13 [Google Scholar]
  117. Perni M, Galvagnion C, Maltsev A, Meisl G, Müller MBD. 117.  et al. 2017. A natural product inhibits the initiation of α-synuclein aggregation and suppresses its toxicity. PNAS 114:E1009–17 [Google Scholar]
  118. Aprile FA, Arosio P, Fusco G, Chen SW, Kumita JR. 118.  et al. 2017. Inhibition of α-synuclein fibril elongation by Hsp70 is governed by a kinetic binding competition between α-synuclein species. Biochemistry 56:1177–80 [Google Scholar]
  119. Habchi J, Arosio P, Perni M, Costa AR, Yagi-Utsumi M. 119. , et al. 2016. An anticancer drug suppresses the primary nucleation reaction that initiates the production of the toxic Aβ42 aggregates linked with Alzheimer's disease. Sci. Adv. 2:e1501244 [Google Scholar]
  120. Golde TE, Schneider LS, Koo EH. 120.  2011. Anti-Aβ therapeutics in Alzheimer's disease: the need for a paradigm shift. Neuron 69:203–13 [Google Scholar]
  121. Buell AK, Galvagnion C, Gaspar R, Sparr E, Vendruscolo M. 121.  et al. 2014. Solution conditions determine the relative importance of nucleation and growth processes in α-synuclein aggregation. PNAS 111:7671–76 [Google Scholar]
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Chemical Kinetics for Bridging Molecular Mechanisms and Macroscopic Measurements of Amyloid Fibril Formation
Annual Review of Physical Chemistry 69, 273 (2018); https://doi.org/10.1146/annurev-physchem-050317-021322
/content/journals/10.1146/annurev-physchem-050317-021322
/content/journals/10.1146/annurev-physchem-050317-021322
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