ArticleThe journal of physical chemistry. B2017
The Levinthal Problem in Amyloid Aggregation: Sampling of a Flat Reaction Space.
Article in The journal of physical chemistry. B, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Competing addition processes give distinct growth regimes in the assembly of 1D filaments.Biophysical journal · 2025Article
- The mechanism of amyloid fibril growth from Φ-value analysis.Nature chemistry · 2025Article
- Distinct growth regimes of α-synuclein amyloid elongation.Biophysical journal · 2023Article
- Beneficial and detrimental effects of non-specific binding during DNA hybridization.Biophysical journal · 2023Article
- Self-Assembly of Amyloid Fibrils into 3D Gel Clusters versus 2D Sheets.Biomolecules · 2023Article
- Conformational entropy limits the transition from nucleation to elongation in amyloid aggregation.Biophysical journal · 2022Article
- Insight Into Seeded Tau Fibril Growth From Molecular Dynamics Simulation of the Alzheimer's Disease Protofibril Core.Frontiers in molecular biosciences · 2021Article
- Amyloid assembly is dominated by misregistered kinetic traps on an unbiased energy landscape.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Theory of Sequence Effects in Amyloid Aggregation.The journal of physical chemistry. B · 2018Article
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Authors and funding
4 authors.
Funding
Abstract
The formation of amyloid fibrils has been associated with many neurodegenerative disorders, yet the mechanism of aggregation remains elusive, partly because aggregation time scales are too long to probe with atomistic simulations. A microscopic theory of fibril elongation was recently developed that could recapitulate experimental results with respect to the effects of temperature, denaturants, and protein concentration on fibril growth kinetics (Schmit, J. D. J. Chem. Phys. 2013, 138 (18), 185102). The theory identifies the conformational search over H-bonding states as the slowest step in the aggregation process and suggests that this search can be efficiently modeled as a random walk on a rugged one-dimensional energy landscape. This insight motivated the multiscale computational algorithm for simulating fibril growth presented in this paper. Briefly, a large number of short atomistic simulations are performed to compute the system diffusion tensor in the reaction coordinate space predicted by the analytic theory. Ensemble aggregation pathways and growth kinetics are then computed from Markov state model (MSM) trajectories. The algorithm is deployed here to understand the fibril growth mechanism and kinetics of Aβ
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.