Hierarchical approach to predicting permeation in ion channels.
A hierarchical computational strategy combining molecular modeling, electrostatics calculations, molecular dynamics, and Brownian dynamics simulations is developed and implemented to compute electrophysiologically measurable properties of the KcsA potassium channel. Models for a series of channels with different pore sizes are developed from the known x-ray structure, using insights into the gating conformational changes as suggested by a variety of published experiments. Information on the pH dependence of the channel gating is incorporated into the calculation of potential profiles for K(+) ions inside the channel, which are then combined with K(+) ion mobilities inside the channel, as computed by molecular dynamics simulations, to provide inputs into Brownian dynamics simulations for computing ion fluxes. The open model structure has a conductance of approximately 110 pS under symmetric 250 mM K(+) conditions, in reasonable agreement with experiments for the largest conducting substate. The dimensions of this channel are consistent with electrophysiologically determined size dependence of quaternary ammonium ion blocking from the intracellular end of this channel as well as with direct structural evidence that tetrabutylammonium ions can enter into the interior cavity of the channel. Realistic values of Ussing flux ratio exponents, distribution of ions within the channel, and shapes of the current-voltage and current-concentration curves are obtained. The Brownian dynamics calculations suggest passage of ions through the selectivity filter proceeds by a "knock-off" mechanism involving three ions, as has been previously inferred from functional and structural studies of barium ion blocking. These results suggest that the present calculations capture the essential nature of K(+) ion permeation in the KcsA channel and provide a proof-of-concept for the integrated microscopic/mesoscopic multitiered approach for predicting ion channel function from structure, which can be applied to other channel structures.
Mashl
R J
RJ
Beckman Institute for Advanced Science and Technology, Department of Molecular and Integrative Physiology, University of Illinois, Urbana-Champaign, Urbana, Illinois 61801, USA. mashl@ncsa.uiuc.edu
Tang
Y
Y
Schnitzer
J
J
Jakobsson
E
E
D001426:Bacterial Proteins; D003198:Computer Simulation; D005544:Forecasting / Q000379:methods; D007473:Ion Channels / Q000737:chemistry / Q000378:metabolism; D017136:Ion Transport / Q000502:physiology; D008958:Models, Molecular; D010539:Permeability; D011188:Potassium / Q000737:chemistry / Q000378:metabolism*; D015221:Potassium Channels / Q000737:chemistry / Q000378:metabolism*; D011199:Potentiometry / Q000379:methods; D055672:Static Electricity; D013302:Streptomyces; D013816:Thermodynamics
D001426:Bacterial Proteins; D007473:Ion Channels; D015221:Potassium Channels; C107790:prokaryotic potassium channel; D011188:Potassium