The yin and yang of amyloid: insights from α-synuclein and repeat domain of Pmel17

Literature Information

Publication Date 2011-10-12
DOI 10.1039/C1CP21376H
Impact Factor 3.676
Authors

Ryan P. McGlinchey, Thai Leong Yap, Jennifer C. Lee


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Abstract

Amyloid has been traditionally viewed in the context of disease. However, the emerging concept of ‘functional amyloid’ has taken a new direction into how we view amyloid. Recent studies have identified amyloid fibrils ranging from bacteria to humans that have a beneficial role, instead of being associated with a misfolded state that has been implicated in diseases such as Alzheimer's, Parkinson's and prion diseases. Here, we review our work on two human amyloidogenic polypeptides, one associated with Parkinson’s disease, α-synuclein (α-syn), and the other important for melanin synthesis, the repeat domain (RPT) from Pmel17. Particularly, we focused our attention on spectroscopic studies of protein conformation and dynamics and their impact on α-syn amyloid formation and for RPT, we discussed the strict pH dependence of amyloid formation and its role in melanin biosynthesis.

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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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