A Three-Stage Kinetic Model of Amyloid Fibrillation
Open accessAbstract
Amyloid fibrillation has been intensively studied because of its association with various neurological disorders. While extensive time-dependent fibrillation experimental data are available and appear similar, few mechanistic models have been developed to unify those results. The aim of this work was to interpret these experimental results via a rigorous mathematical model that incorporates the physical chemistry of nucleation and fibril growth dynamics. A three-stage mechanism consisting of protein misfolding, nucleation, and fibril elongation is proposed and supported by the features of homogeneous fibrillation responses. Estimated by nonlinear least-squares algorithms, the rate constants for nucleation were approximately 10,000,000 times smaller than those for fibril growth. These results, coupled with the positive feedback characteristics of the elongation process, account for the typical sigmoidal behavior during fibrillation. In addition, experiments with different proteins, various initial concentrations, seeding versus nonseeding, and several agitation rates were analyzed with respect to fibrillation using our new model. The wide applicability of the model confirms that fibrillation kinetics may be fairly similar among amyloid proteins and for different environmental factors. Recommendations on further experiments and on the possible use of molecular simulations to determine the desired properties of potential fibrillation inhibitors are offered.
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Aβ fibrillation and plaque formation follow sigmoidal growth kinetics.
“Aβ fibrillation and plaque formation follow sigmoidal growth kinetics20,21”
From Oligodendrocytes produce amyloid-β and contribute to plaque formation alongside neurons in Alzheimer’s disease model mice (2024) · cites this paper as [20]
The In vitro fibrillation kinetics section describes sigmoidal behavior in amyloid fibrillation and reports that the model fits Aβ-40 fibrillation data. It identifies Aβ-40 as a protein fragment that aggregates into plaques, but does not show that plaque formation itself follows sigmoidal kinetics; the Conclusions likewise concern fibril formation, not plaque growth. Page numbers were not available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measuredA threshold level of Aβ accumulation is essential for plaque seeding to occur.
“a threshold level of Aβ accumulation is essential for plaque seeding to occur.”
From Oligodendrocytes produce amyloid-β and contribute to plaque formation alongside neurons in Alzheimer’s disease model mice (2024) · cites this paper as [20]
The 'Effects of seeding' section says fibril growth requires sufficient nuclei, and 'In vitro fibrillation kinetics' applies the model to Aβ-40. Neither section establishes that Aβ must accumulate to a threshold before plaque seeding can occur; the seeding example concerns insulin fibrils. Page numbers are unavailable in our copy. (LLM, conf=0.82)
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References 40 · Cited by 278
Research works printed but not linked: 7
- [1]1. Sipe, J. D. 2005. Amyloid Protein: The Beta Sheet Conformation and Disease. John Wiley and Sons, New York.
- [22]22. Lee, C.-C., A. Nayak, G. Belfort, and G. J. McRae. 2006. A Mathematical Model of Amyloid Fibrillation: The Case for Insulin. Biophysical Society Conference, Salt Lake City, Utah.
- [27]27. Gill, R. 1994. Protein engineering of insulin-like growth factor. PhD Thesis. University of London, London, UK.
- [35]35. Bird, R. B., W. E. Stewart, and E. N. Lightfoot. 2002. Transport Phenomena, 2nd Ed. John Wiley and Sons, New York.
- [37]37. Seber, G. A. F., and C. J. Wild. 2003. Nonlinear Regression. John Wiley and Sons, New York.
- [38]38. Kingsland, S. E. 1995. Modeling Nature. University Of Chicago Press, Chicago, IL.
- [46]46. Nguyen, H. D., and C. K. Hall. 2004. Molecular dynamics simulations of spontaneous fibril formation. Proc. Natl. Acad. Sci. USA. 101: 16180-16185.
- Authors
- Lee, C.-C., Nayak, A., Sethuraman, A., Belfort, G., & McRae, G. J.
- Affiliations
- Massachusetts Institute of Technology (US)
- Rensselaer Polytechnic Institute (US)
- Corresponding author
- Belfort, Georges
- McRae, Gregory J.
- ORCID
- Belfort, Georges
- Venue
- Biophysical Journal
- Publisher
- Elsevier BV
- Published
- 2007-05
- Volume
- 92
- Issue
- 10
- Pages
- 3448-3458
- ISSN
- 0006-3495 (ISSN-L)
- PMC
- PMC1853138
- OpenAlex
- W1972011321
- Cited by
- 278
- References
- 40
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 14 · 2023: 16 · 2022: 15 · 2021: 15 · 2020: 21 · 2019: 26 · 2018: 18 · 2017: 22 · 2016: 14 · 2015: 10 · 2014: 14 · 2013: 15 · 2012: 18
- FWCI
- 6.45
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Biophysical Journal (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Prion Diseases and Protein Misfolding
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- amyloid fibril formation, fibrillation kinetics, nucleation, fibril growth, protein misfolding, sigmoidal kinetics, positive feedback, seeding, neurological disorders
- MeSH terms
- Amyloid, Binding Sites, Computer Simulation, Kinetics, Models, Chemical, Models, Molecular, Protein Binding, Protein Conformation, Dimerization, Multiprotein Complexes
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