June  2018, 23(4): 1623-1643. doi: 10.3934/dcdsb.2018064

Ion size effects on individual fluxes via Poisson-Nernst-Planck systems with Bikerman's local hard-sphere potential: Analysis without electroneutrality boundary conditions

1. 

School of Mathematics and Statistics, Shandong University, Weihai, Shandong 264209, China

2. 

School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

3. 

Department of Mathematics, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA

Received  May 2017 Revised  September 2017 Published  February 2018

A quasi-one-dimensional steady-state Poisson-Nernst-Planck model with Bikerman's local hard-sphere potential for ionic flows of two oppositely charged ion species through a membrane channel is analyzed. Of particular interest is the qualitative properties of ionic flows in terms of individual fluxes without the assumption of electroneutrality conditions, which is more realistic to study ionic flow properties of interest. This is the novelty of this work. Our result shows that ⅰ) boundary concentrations and relative size of ion species play critical roles in characterizing ion size effects on individual fluxes; ⅱ) the first order approximation $\mathcal{J}_{k1} = D_kJ_{k1}$ in ion volume of individual fluxes $\mathcal{ J}_k = D_kJ_k$ is linear in boundary potential, furthermore, the signs of $\partial_V \mathcal{ J}_{k1}$ and $\partial^2_{Vλ} \mathcal{J}_{k1}$, which play key roles in characterizing ion size effects on ionic flows can be both negative depending further on boundary concentrations while they are always positive and independent of boundary concentrations under electroneutrality conditions (see Corollaries 3.2-3.3, Theorems 3.4-3.5 and Proposition 3.7). Numerical simulations are performed to identify some critical potentials defined in (2). We believe our results will provide useful insights for numerical and even experimental studies of ionic flows through membrane channels.

Citation: Hong Lu, Ji Li, Joseph Shackelford, Jeremy Vorenberg, Mingji Zhang. Ion size effects on individual fluxes via Poisson-Nernst-Planck systems with Bikerman's local hard-sphere potential: Analysis without electroneutrality boundary conditions. Discrete & Continuous Dynamical Systems - B, 2018, 23 (4) : 1623-1643. doi: 10.3934/dcdsb.2018064
References:
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show all references

References:
[1]

N. AbaidR. S. Eisenberg and W. Liu, Asymptotic expansions of Ⅰ-Ⅴ relations via a Poisson-Nernst-Planck system, SIAM J. Appl. Dyn. Syst., 7 (2008), 1507-1526.  doi: 10.1137/070691322.  Google Scholar

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V. Barcilon, Ion flow through narrow membrane channels: Part Ⅰ, SIAM J. Appl. Math., 52 (1992), 1391-1404.  doi: 10.1137/0152080.  Google Scholar

[3]

D. BodaD. BusathB. EisenbergD. Henderson and W. Nonner, Monte Carlo simulations of ion selectivity in a biological Na+ channel: Charge-space competition, Phys. Chem. Chem. Phys., 4 (2002), 5154-5160.  doi: 10.1039/B203686J.  Google Scholar

[4]

V. BarcilonD.-P. Chen and R. S. Eisenberg, Ion flow through narrow membrane channels: Part Ⅱ, SIAM J. Appl. Math., 52 (1992), 1405-1425.  doi: 10.1137/0152081.  Google Scholar

[5]

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[6]

M. BurgerR. S. Eisenberg and H. W. Engl, Inverse problems related to ion channel selectivity, SIAM J. Appl. Math., 67 (2007), 960-989.  doi: 10.1137/060664689.  Google Scholar

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[8]

J. J. Bikerman, Structure and capacity of the electrical double layer, Philos. Mag., 33 (1942), 384-397.  doi: 10.1080/14786444208520813.  Google Scholar

[9]

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[10]

P. W. BatesW. LiuH. Lu and M. Zhang, Ion size and valence effects on ionic flows via Poisson-Nernst-Planck models, Commu. Math. Sci., 15 (2017), 881-901.  doi: 10.4310/CMS.2017.v15.n4.a1.  Google Scholar

[11]

J. H. ChaudhryS. D. Bond and L. N. Olson, Finite Element Approximation to a Finite-Size Modified Poisson-Boltzmann Equation, J. Sci. Comput, 47 (2011), 347-364.  doi: 10.1007/s10915-010-9441-7.  Google Scholar

[12]

A. E. CardenasR. D. Coalson and M. G. Kurnikova, Three-dimensional poisson-nernst-planck theory studies: Influence of membrane electrostatics on gramicidin a channel conductance, Biophys. J., 79 (2000), 80-93.  doi: 10.1016/S0006-3495(00)76275-8.  Google Scholar

[13]

D. P. Chen and R. S. Eisenberg, Charges, currents and potentials in ionic channels of one conformation, Biophys. J., 64 (1993), 1405-1421.  doi: 10.1016/S0006-3495(93)81507-8.  Google Scholar

[14]

S. Chung and S. Kuyucak, Predicting channel function from channel structure using Brownian dynamics simulations, Clin. Exp. Pharmacol Physiol., 28 (2001), 89-94.   Google Scholar

[15]

R. Coalson and M. Kurnikova, Poisson-Nernst-Planck theory approach to the calculation of current through biological ion channels, IEEE Transaction on NanoBioscience, 4 (2005), 81-93.  doi: 10.1109/TNB.2004.842495.  Google Scholar

[16]

B. Eisenberg, Ion channels as devices, J. Comp. Electro., 2 (2003), 245-249.  doi: 10.1023/B:JCEL.0000011432.03832.22.  Google Scholar

[17]

B. Eisenberg, Proteins, channels, and crowded ions, Biophys. Chem., 100 (2003), 507-517.  doi: 10.1016/S0301-4622(02)00302-22.  Google Scholar

[18]

R. S. Eisenberg, Channels as enzymes, J. Memb. Biol., 115 (1990), 1-12.  doi: 10.1007/BF01869101.  Google Scholar

[19]

R. S. Eisenberg and A. Biology, Electrostatics and Ionic Channels, In New Developments and Theoretical Studies of Proteins, R. Elber, Editor, 269-357, World Scientific, Philadelphia, (1996).   Google Scholar

[20]

R. S. Eisenberg, From structure to function in open ionic channels, J. Memb. Biol., 171 (1999), 1-24.  doi: 10.1007/s002329900554.  Google Scholar

[21]

B. Eisenberg and W. Liu, Poisson-Nernst-Planck systems for ion channels with permanent charges, SIAM J. Math. Anal., 38 (2007), 1932-1966.  doi: 10.1137/060657480.  Google Scholar

[22]

B. EisenbergW. Liu and H. Xu, Reversal permanent charge and reversal potential: Case studies via classical Poisson-Nernst-Planck models, Nonlinearity, 28 (2015), 103-127.   Google Scholar

[23]

A. ErnR. Joubaud and T. Leliévre, Mathematical study of non-ideal electrostatic correlations in equilibrium electrolytes, Nonlinearity, 25 (2012), 1635-1652.  doi: 10.1088/0951-7715/25/6/1635.  Google Scholar

[24]

J. Fischer and U. Heinbuch, Relationship between free energy density functional, Born-Green-Yvon, and potential distribution approaches for inhomogeneous fluids, J. Chem. Phys., 88 (1988), 1909-1913.  doi: 10.1063/1.454114.  Google Scholar

[25]

D. Gillespie and R. S. Eisenberg, Physical descriptions of experimental selectivity measurements in ion channels, European Biophys. J., 31 (2002), 454-466.  doi: 10.1007/s00249-002-0239-x.  Google Scholar

[26]

D. Gillespie, A Singular Perturbation Analysis of the Poisson-Nernst-Planck System: Applications to Ionic Channels, Ph. D Dissertation, Rush University at Chicago, 1999.  Google Scholar

[27]

D. GillespieW. Nonner and R. S. Eisenberg, Coupling Poisson-Nernst-Planck and density functional theory to calculate ion flux, J. Phys.: Condens. Matter, 14 (2002), 12129-12145.  doi: 10.1088/0953-8984/14/46/317.  Google Scholar

[28]

D. Gillespie, W. Nonner and R. S. Eisenberg, Density functional theory of charged, hard-sphere fluids Phys. Rev. E, 68 (2003), 0313503 (1-10). doi: 10.1103/PhysRevE.68.031503.  Google Scholar

[29]

D. GillespieW. Nonner and R. S. Eisenberg, Crowded charge in biological ion channels, Nanotech, 3 (2003), 435-438.   Google Scholar

[30]

E. GongadzeU. van RienenV. Kralj-lglič and A. lglič, Spatial variation of permittivity of an electrolyte solution in contact with a charged metal surface: A mini review, Computer Method in Biomechanics and Biomedical Engineering, 16 (2013), 463-480.   Google Scholar

[31]

D. GillespieL. XuY. Wang and G. Meissner, (De)constructing the Ryanodine Receptor: Modeling Ion Permeation and Selectivity of the Calcium Release Channel, J. Phys. Chem. B, 109 (2005), 15598-15610.  doi: 10.1021/jp052471j.  Google Scholar

[32]

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Figure 1.  Numerical detection of critical values for $\lambda$ (left graph) and $m$ (right one) in Theorem 3.2.
Figure 2.  Numerical detection of critical values for $\sigma$, which corresponds to statement (Ⅰ) in Theorem 3.2. The left graph is for $\lambda<\lambda_1^* = 0.072$, and the right one is for $\lambda>\lambda_2^* = 13.93.$
Figure 3.  Numerical detection of critical values $\sigma$ corresponding to statement (Ⅱ) in Theorem 3.2 with $\lambda_1^*<\lambda<\lambda_2^*$. The left graph is for $0<m<m^* = 0.4934$, and the right one is for $m^*<m<\frac{1}{2}.$
Figure 4.  Numerical identification of six critical potentials in (15) with $z_1 = -z_2 = 1$. In the left column, the vertical axis actually represents, from top to bottom, ${\mathcal I}(V;\nu, \lambda)-{\mathcal I}_0(V), \ {\mathcal J}_1(V;\nu, \lambda)-{\mathcal J}_{10}(V)$ and ${\mathcal J}_2(V;\nu, \lambda)-{\mathcal J}_{20}(V)$, respectively. In particular, the x-axis for all figures actually represents $\frac{e}{k_BT}V$.
Figure 5.  Numerical identification of critical potentials $V_{1c}$ and $ V_1^c$ for individual flux ${\mathcal J}_1$ with $z_1 = -z_2 = 1$ and nonzero permanent charge. The x-axis for all figures actually represents $\frac{e}{k_BT}V$.
Figure 6.  Numerical approximations of critical potentials $V_1^c$ for individual flux ${\mathcal J}_1$ with $z_1 = -z_2 = 1$ and nonzero permanent charge as illustrated in Proposition 3.14. The x-axis for all figures actually represents $\frac{e}{k_BT}V$.
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