Journal Article

PreJuSER-11899

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Thermodynamics of Competitive Molecular Channel Transport. Application to Artificial Nuclear Pores

Bauer, W. R. ; Nadler, W.FZJ*

2010
PLoS Lawrence, Kan.

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Please use a persistent id in citations: http://hdl.handle.net/2128/11183  doi:10.1371/journal.pone.0015160

Abstract: In an analytical model channel transport is analyzed as a function of key parameters, determining efficiency and selectivity of particle transport in a competitive molecular environment. These key parameters are the concentration of particles, solvent-channel exchange dynamics, as well as particle-in-channel- and interparticle interaction. These parameters are explicitly related to translocation dynamics and channel occupation probability. Slowing down the exchange dynamics at the channel ends, or elevating the particle concentration reduces the in-channel binding strength necessary to maintain maximum transport. Optimized in-channel interaction may even shift from binding to repulsion. A simple equation gives the interrelation of access dynamics and concentration at this transition point. The model is readily transferred to competitive transport of different species, each of them having their individual in-channel affinity. Combinations of channel affinities are determined which differentially favor selectivity of certain species on the cost of others. Selectivity for a species increases if its in-channel binding enhances the species' translocation probability when compared to that of the other species. Selectivity increases particularly for a wide binding site, long channels, and fast access dynamics. Recent experiments on competitive transport of in-channel binding and inert molecules through artificial nuclear pores serve as a paradigm for our model. It explains qualitatively and quantitatively how binding molecules are favored for transport at the cost of the transport of inert molecules.

Keyword(s): Active Transport, Cell Nucleus (MeSH) ; Animals (MeSH) ; Binding Sites (MeSH) ; Binding, Competitive (MeSH) ; Biochemistry: methods (MeSH) ; Biological Transport (MeSH) ; Biophysics: methods (MeSH) ; Cattle (MeSH) ; Models, Biological (MeSH) ; Models, Statistical (MeSH) ; Models, Theoretical (MeSH) ; Serum Albumin: chemistry (MeSH) ; Solvents: chemistry (MeSH) ; Thermodynamics (MeSH) ; Serum Albumin ; Solvents ; J

Note: This work was partially supported by the Collaborative Research Centre 688 of the German Research Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Contributing Institute(s):

1. Jülich Supercomputing Centre (JSC)

Research Program(s):

1. Scientific Computing (FUEK411) (FUEK411)
2. 411 - Computational Science and Mathematical Methods (POF2-411) (POF2-411)

Appears in the scientific report 2010

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