Computational models explain how copper binding to amyloid-β peptide oligomers enhances oxidative pathways

Literature Information

Publication Date 2019-04-02
DOI 10.1039/C9CP00293F
Impact Factor 3.676
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Abstract

Amyloid-β (Aβ) peptides are intrinsically disordered peptides and their aggregation is the major hallmark of Alzheimer's disease (AD) development. The interactions between copper ions and Aβ peptides create catalysts that activate the production of reactive oxygen species in the synaptic region, a reactivity that is strongly related to AD onset. Recent experimental work [Gu et al., Sci. Rep., 2018, 8(1), 16190] confirmed that the oxidative reactivity of Cu–Aβ catalyzes the formation of Tyr–Tyr crosslinks in peptide dimers. This work provides a structural basis to these observations, describing structures of Cu–Aβ dimers that enhance the propagation of the oxidative pathways activated around the Cu center. Among these, the formation of Tyr–Tyr crosslinks becomes more likely when previous crosslinks involve Cu forming bridges between different peptides. Peptides are, therefore, easily assembled into dimers and tetramers, the latter being dimers of dimers. The size of such dimers and tetramers fits with ion mobility mass spectrometry results [Sitkiewicz et al., J. Mol. Biol., 2014, 426(15), 2871].

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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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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