Membrane packing defects in synaptic vesicles recruit complexin and synuclein

Literature Information

Publication Date 2020-12-18
DOI 10.1039/D0CP03546G
Impact Factor 3.676
Authors

Jie Liu, Bing Bu, Michael Crowe, Dechang Li, Jiajie Diao, Baohua Ji


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Abstract

Complexin-1 (Cpx) and α-synuclein (α-Syn) are involved in neurotransmitter release through an interaction with synaptic vesicles (SVs). Recent studies demonstrated that Cpx and α-Syn preferentially associate with highly curved membranes, like SVs, to correctly position them for fusion. Here, based on recent experimental results, to further propose a possible explanation for this mechanism, we performed in silico simulations probing interactions between Cpx or α-Syn and membranes of varying curvature. We found that the preferential association is attributed to smaller, curved membranes containing more packing defects that expose hydrophobic acyl tails, which may favorably interact with hydrophobic residues of Cpx and α-Syn. The number of membrane defects is proportional to the curvature and the size can be regulated by cholesterol.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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