Paper
23 March 2011 Single channel conductance modeling of the peptide alamethicin in synthetically formed bilayers
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Abstract
Bilayers are synthetically made cell membranes that are used to study cell membrane properties and make functional devices that incorporate inherent properties of the cell membranes. Lipids and proteins are two of the main components of a cell membrane. Lipids provide the structure of the membrane in the form of two leaflets or layers that are held together by the amphiphilic interaction between the lipids and water. Proteins are made from a combination of amino acids and the properties of these proteins are dependent on the amino acid sequence. Some proteins are antibiotics and can easily self insert into the membrane of a cell or into a synthetically formed bilayer. The peptide alamethicin is one such antibiotic that easily inserts into a bilayer and changes the conductance properties of the bilayer. Analytical models of the conductance change with respect to the potential and other variables across the bilayer follows the nonlinear conductance changes seen with the incorporation of the peptide in a bilayer. The individual channels formed by the peptide have been studied and the peptide has several discrete conductance levels. These discrete levels have been shown to be dependent on the potential across the bilayer and several other variables including the lipid variety. The conductance level for a single channel can change with time in a probabilistic fashion. This paper will model these discrete conductance levels of the peptide alamethicin and the model of the single channel conductance will be used to model the cumulative effect of multiple channels within a bilayer.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Austin Creasy and Donald J. Leo "Single channel conductance modeling of the peptide alamethicin in synthetically formed bilayers", Proc. SPIE 7975, Bioinspiration, Biomimetics, and Bioreplication, 79750V (23 March 2011); https://doi.org/10.1117/12.880565
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KEYWORDS
Proteins

Systems modeling

Statistical modeling

Data modeling

Interfaces

Picosecond phenomena

Ions

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