A Brownian Dynamics Analysis of Ion Movement in Membrane Channels
Cooper, Kimbal Edward
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/71425
Description
Title
A Brownian Dynamics Analysis of Ion Movement in Membrane Channels
Author(s)
Cooper, Kimbal Edward
Issue Date
1983
Department of Study
Physiology and Biophysics
Discipline
Physiology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Biology, Animal Physiology
Abstract
The purpose of this thesis is to review and extend the theory of ion transport through membrane channel. A review of previous theory is presented which includes both Nernst-Planck and Eyring Rate theory approaches. The predictions and assumptions of the two theories are discussed and a unified derivation of both from a more fundamental stochastic theory is presented. That more fundamental stochastic theory is based on the Langevin equation. A simulation technique based on this equation is presented. The technique called Brownian dynamics is then used to study ion transport through membrane channels. Four cases are considered: (1) no ion-ion interaction, no channel structure; (2) no ion-ion interaction, channel structure present; (3) ion-ion interaction, no channel structure; (4) ion-ion interaction, channel structure present. A detailed discussion of the simulation is given with an indication of possible future improvements. The Brownian dynamic approach illustrates nicely the shortcomings of the Nernst-Planck and Eyring theory approaches.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
