کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5370925 1503919 2015 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Characterization of 3D Voronoi tessellation nearest neighbor lipid shells provides atomistic lipid disruption profile of protein containing lipid membranes
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی تئوریک و عملی
پیش نمایش صفحه اول مقاله
Characterization of 3D Voronoi tessellation nearest neighbor lipid shells provides atomistic lipid disruption profile of protein containing lipid membranes
چکیده انگلیسی


- New 3D Voronoi tessellation (VT) method to study protein-induced lipiddisruption
- Classification of multiple VT lipid shells based on VT nearest-atom-neighbors
- Observed non-uniform recovery of fractional lipid volume across lipid shells
- Bilayer thickness and lipid order parameter calculations validated the VT results.
- This method is applicable to all coordinate-based membrane structural data.

Quantifying protein-induced lipid disruptions at the atomistic level is a challenging problem in membrane biophysics. Here we propose a novel 3D Voronoi tessellation nearest-atom-neighbor shell method to classify and characterize lipid domains into discrete concentric lipid shells surrounding membrane proteins in structurally heterogeneous lipid membranes. This method needs only the coordinates of the system and is independent of force fields and simulation conditions. As a proof-of-principle, we use this multiple lipid shell method to analyze the lipid disruption profiles of three simulated membrane systems: phosphatidylcholine, phosphatidylcholine/cholesterol, and beta-amyloid/phosphatidylcholine/cholesterol. We observed different atomic volume disruption mechanisms due to cholesterol and beta-amyloid. Additionally, several lipid fractional groups and lipid-interfacial water did not converge to their control values with increasing distance or shell order from the protein. This volume divergent behavior was confirmed by bilayer thickness and chain orientational order calculations. Our method can also be used to analyze high-resolution structural experimental data.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biophysical Chemistry - Volume 198, March 2015, Pages 22-35
نویسندگان
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