Molecular dynamics simulations of ethanol permeation through single and double-lipid bilayers

被引:24
作者
Ghorbani, Mahdi [1 ,2 ]
Wang, Eric [1 ]
Kramer, Andreas [2 ]
Klauda, Jeffery B. [1 ,3 ]
机构
[1] Univ Maryland, Dept Chem & Biomol Engn, College Pk, MD 20742 USA
[2] NHLBI, Lab Computat Biol, NIH, Bethesda, MD 20824 USA
[3] Univ Maryland, Biophys Grad Program, College Pk, MD 20742 USA
关键词
GUI MEMBRANE-BUILDER; WATER PERMEATION; PERMEABILITY ASSAY; FORCE-FIELD; DIFFUSION; COEFFICIENTS; TRANSPORT; TOLERANCE; ALCOHOLS; MODELS;
D O I
10.1063/5.0013430
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Permeation of small molecules through membranes is a fundamental biological process, and molecular dynamics simulations have proven to be a promising tool for studying the permeability of membranes by providing a precise characterization of the free energy and diffusivity. In this study, permeation of ethanol through three different membranes of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine (POPS), PO-phosphatidylethanolamine (POPE), and PO-phosphatidylcholine (POPC) is studied. Permeabilities are calculated and compared with two different approaches based on Fick's first law and the inhomogeneous solubility-diffusion model. Microsecond simulation of double bilayers of these membranes provided a direct measurement of permeability by a flux-based counting method. These simulations show that a membrane of POPC has the highest permeability, followed by POPE and POPS. Due to the membrane-modulating properties of ethanol, the permeability increases as functions of concentration and saturation of the inner leaflet in a double bilayer setting, as opposed to the customary definition as a proportionality constant. This concentration dependence is confirmed by single bilayer simulations at different ethanol concentrations ranging from 1% to 18%, where permeability estimates are available from transition-based counting and the inhomogeneous solubility-diffusion model. We show that the free energy and diffusion profiles for ethanol lack accuracy at higher permeant concentrations due to non-Markovian kinetics caused by collective behavior. In contrast, the counting method provides unbiased estimates. Finally, the permeabilities obtained from single bilayer simulations are combined to represent natural gradients felt by a cellular membrane, which accurately models the non-equilibrium effects on ethanol permeability from single bilayer simulations in equilibrium.
引用
收藏
页数:15
相关论文
共 62 条
[31]   Physicochemical high throughput screening: Parallel artificial membrane permeation assay in the description of passive absorption processes [J].
Kansy, M ;
Senner, F ;
Gubernator, K .
JOURNAL OF MEDICINAL CHEMISTRY, 1998, 41 (07) :1007-1010
[32]   Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types [J].
Klauda, Jeffery B. ;
Venable, Richard M. ;
Freites, J. Alfredo ;
O'Connor, Joseph W. ;
Tobias, Douglas J. ;
Mondragon-Ramirez, Carlos ;
Vorobyov, Igor ;
MacKerell, Alexander D., Jr. ;
Pastor, Richard W. .
JOURNAL OF PHYSICAL CHEMISTRY B, 2010, 114 (23) :7830-7843
[33]   Biophysical Changes of Lipid Membranes in the Presence of Ethanol at Varying Concentrations [J].
Konas, Ryan M. ;
Daristotle, John L. ;
Harbor, Ndubuisi B. ;
Klauda, Jeffery B. .
JOURNAL OF PHYSICAL CHEMISTRY B, 2015, 119 (41) :13134-13141
[34]   Membrane permeability of small molecules from unbiased molecular dynamics simulations [J].
Kramer, Andreas ;
Ghysels, An ;
Wang, Eric ;
Venable, Richard M. ;
Klauda, Jeffery B. ;
Brooks, Bernard R. ;
Pastor, Richard W. .
JOURNAL OF CHEMICAL PHYSICS, 2020, 153 (12)
[35]   Predicting caco-2 cell permeation coefficients of organic molecules using membrane-interaction QSAR analysis [J].
Kulkarni, A ;
Han, Y ;
Hopfinger, AJ .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2002, 42 (02) :331-342
[36]   Simulation-Based Approaches for Determining Membrane Permeability of Small Compounds [J].
Lee, Christopher T. ;
Comer, Jeffrey ;
Herndon, Conner ;
Leung, Nelson ;
Pavlova, Anna ;
Swift, Robert V. ;
Tung, Chris ;
Rowley, Christopher N. ;
Amaro, Rommie E. ;
Chipot, Christophe ;
Wang, Yi ;
Gumbart, James C. .
JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2016, 56 (04) :721-733
[37]   CHARMM-GUI Membrane Builder for Complex Biological Membrane Simulations with Glycolipids and Lipoglycans [J].
Lee, Jumin ;
Patel, Dhilon S. ;
Stahle, Jonas ;
Park, Sang-Jun ;
Kern, Nathan R. ;
Kim, Seonghoon ;
Lee, Joonseong ;
Cheng, Xi ;
Valvano, Miguel A. ;
Holst, Otto ;
Knirel, Yuriy A. ;
Qi, Yifei ;
Jo, Sunhwan ;
Klauda, Jeffery B. ;
Widmalm, Goran ;
Im, Wonpil .
JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2019, 15 (01) :775-786
[38]   CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field [J].
Lee, Jumin ;
Cheng, Xi ;
Swails, Jason M. ;
Yeom, Min Sun ;
Eastman, Peter K. ;
Lemkul, Justin A. ;
Wei, Shuai ;
Buckner, Joshua ;
Jeong, Jong Cheol ;
Qi, Yifei ;
Jo, Sunhwan ;
Pande, Vijay S. ;
Case, David A. ;
Brooks, Charles L., III ;
MacKerell, Alexander D., Jr. ;
Klauda, Jeffery B. ;
Im, Wonpil .
JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 2016, 12 (01) :405-413
[39]   Probing Lipid Bilayers under Ionic Imbalance [J].
Lin, Jiaqi ;
Alexander-Katz, Alfredo .
BIOPHYSICAL JOURNAL, 2016, 111 (11) :2460-2469
[40]   Structure and dynamics of the TIP3P, SPC, and SPC/E water models at 298 K [J].
Mark, P ;
Nilsson, L .
JOURNAL OF PHYSICAL CHEMISTRY A, 2001, 105 (43) :9954-9960