Thermodynamics of amyloid fibril formation from chemical depolymerization
文献情報
Nicola Vettore
Amyloid fibrils are homo-molecular protein polymers that play an important role in disease and biological function. While much is known about their kinetics and mechanisms of formation, the origin and magnitude of their thermodynamic stability has received significantly less attention. This is despite the fact that the thermodynamic stability of amyloid fibrils is an important determinant of their lifetimes and processing in vivo. Here we use depolymerization by chemical denaturants of amyloid fibrils of two different proteins (PI3K-SH3 and glucagon) at different concentrations and show that the previously applied isodesmic linear polymerization model is an oversimplification that does not capture the concentration dependence of chemical depolymerization of amyloid fibrils. We show that cooperative polymerization, which is compatible with the picture of amyloid formation as a nucleated polymerization process, is able to quantitatively describe the thermodynamic data. We use this combined experimental and conceptual framework in order to probe the ionic strength dependence of amyloid fibril stability. In combination with previously published data on the ionic strength dependence of amyloid fibril growth kinetics, our results provide strong evidence for the product-like nature of the transition state of amyloid fibril growth.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.










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