The routinely employed periodic boundary conditions complicate molecular simulations of physiologically relevant asymmetric lipid membranes together with their distinct solvent environments. Therefore, separating the extracellular fluid from its cytosolic counterpart has often been performed using a costly double-bilayer setup. Here, we demonstrate that the lipid membrane and solvent asymmetry can be efficiently modeled with a single lipid bilayer by applying an inverted flat-bottom potential to ions and other solute molecules, thereby restraining them to only interact with the relevant leaflet. We carefully optimized the parameters of the suggested method so that the results obtained using the flat-bottom and double-bilayer approaches become mutually indistinguishable. Then, we apply the flat-bottom approach to lipid bilayers with various compositions and solvent environments, covering ions and cationic peptides to validate the approach in a realistic use case. We also discuss the possible limitations of the method as well as its computational efficiency and provide a step-by-step guide on how to set up such simulations in a straightforward manner.

Central European Institute of Technology Masaryk University Kamenice 5 Brno CZ 62500 Czech Republic

Institute of Biotechnology University of Helsinki Helsinki FI 00790 Finland

Institute of Organic Chemistry and Biochemistry Academy of Sciences of the Czech Republic Flemingovo nam 2 Prague 6 CZ 16610 Czech Republic

Zobrazit více v PubMed

Rothman J. E.; Lenard J. Membrane asymmetry. Science 1977, 195, 743–753. 10.1126/science.402030. PubMed DOI

Van Meer G.; Voelker D. R.; Feigenson G. W. Membrane lipids: where they are and how they behave. Nat. Rev. Mol. Cell Biol. 2008, 9, 112–124. 10.1038/nrm2330. PubMed DOI PMC

Lorent J.; Levental K.; Ganesan L.; Rivera-Longsworth G.; Sezgin E.; Doktorova M.; Lyman E.; Levental I. Plasma membranes are asymmetric in lipid unsaturation, packing and protein shape. Nat. Chem. Biol. 2020, 16, 644–652. 10.1038/s41589-020-0529-6. PubMed DOI PMC

Fadeel B.; Xue D. The ins and outs of phospholipid asymmetry in the plasma membrane: Roles in health and disease. Crit. Rev. Biochem. Mol. Biol. 2009, 44, 264–277. 10.1080/10409230903193307. PubMed DOI PMC

Daleke D. L. Regulation of transbilayer plasma membrane phospholipid asymmetry. J. Lipid Res. 2003, 44, 233–242. 10.1194/jlr.r200019-jlr200. PubMed DOI

Lodish H.; Berk A.; Zipursky S. L.; Matsudaira P.; Baltimore D.; Darnell J.. Molecular Cell Biology, 4th ed.; W. H. Freeman, 2000.

Enkavi G.; Javanainen M.; Kulig W.; Róg T.; Vattulainen I. Multiscale simulations of biological membranes: The challenge to understand biological phenomena in a living substance. Chem. Rev. 2019, 119, 5607–5774. 10.1021/acs.chemrev.8b00538. PubMed DOI PMC

Marrink S. J.; Corradi V.; Souza P. C.; Ingólfsson H. I.; Tieleman D. P.; Sansom M. S. Computational modeling of realistic cell membranes. Chem. Rev. 2019, 119, 6184–6226. 10.1021/acs.chemrev.8b00460. PubMed DOI PMC

Blumer M.; Harris S.; Li M.; Martinez L.; Untereiner M.; Saeta P. N.; Carpenter T. S.; Ingólfsson H. I.; Bennett W. Simulations of asymmetric membranes illustrate cooperative leaflet coupling and lipid adaptability. Front. Cell Dev. Biol. 2020, 8, 575.10.3389/fcell.2020.00575. PubMed DOI PMC

Ingólfsson H. I.; Melo M. N.; Van Eerden F. J.; Arnarez C.; Lopez C. A.; Wassenaar T. A.; Periole X.; De Vries A. H.; Tieleman D. P.; Marrink S. J. Lipid organization of the plasma membrane. J. Am. Chem. Soc. 2014, 136, 14554–14559. 10.1021/ja507832e. PubMed DOI

Ingólfsson H. I.; Carpenter T. S.; Bhatia H.; Bremer P.-T.; Marrink S. J.; Lightstone F. C. Computational lipidomics of the neuronal plasma membrane. Biophys. J. 2017, 113, 2271–2280. 10.1016/j.bpj.2017.10.017. PubMed DOI PMC

Hossein A.; Deserno M. Spontaneous curvature, differential stress, and bending modulus of asymmetric lipid membranes. Biophys. J. 2020, 118, 624–642. 10.1016/j.bpj.2019.11.3398. PubMed DOI PMC

Chaisson E. H.; Heberle F. A.; Doktorova M. Building asymmetric lipid bilayers for molecular dynamics simulations: What methods exist and how to choose one?. Membranes 2023, 13, 629.10.3390/membranes13070629. PubMed DOI PMC

Park S.; Beaven A. H.; Klauda J. B.; Im W. How tolerant are membrane simulations with mismatch in area per lipid between leaflets?. J. Chem. Theory Comput. 2015, 11, 3466–3477. 10.1021/acs.jctc.5b00232. PubMed DOI PMC

Doktorova M.; Weinstein H. Accurate in silico modeling of asymmetric bilayers based on biophysical principles. Biophys. J. 2018, 115, 1638–1643. 10.1016/j.bpj.2018.09.008. PubMed DOI PMC

Miettinen M. S.; Lipowsky R. Bilayer membranes with frequent flip-flops have tensionless leaflets. Nano Lett. 2019, 19, 5011–5016. 10.1021/acs.nanolett.9b01239. PubMed DOI PMC

Varma M.; Deserno M. Distribution of cholesterol in asymmetric membranes driven by composition and differential stress. Biophys. J. 2022, 121, 4001–4018. 10.1016/j.bpj.2022.07.032. PubMed DOI PMC

Sachs J. N.; Crozier P. S.; Woolf T. B. Atomistic simulations of biologically realistic transmembrane potential gradients. J. Chem. Phys. 2004, 121, 10847–10851. 10.1063/1.1826056. PubMed DOI

Gurtovenko A. A. Asymmetry of lipid bilayers induced by monovalent salt: Atomistic molecular-dynamics study. J. Chem. Phys. 2005, 122, 244902.10.1063/1.1942489. PubMed DOI

Lee S.-J.; Song Y.; Baker N. A. Molecular dynamics simulations of asymmetric NaCl and KCl solutions separated by phosphatidylcholine bilayers: potential drops and structural changes induced by strong Na+-lipid interactions and finite size effects. Biophys. J. 2008, 94, 3565–3576. 10.1529/biophysj.107.116335. PubMed DOI PMC

Denning E. J.; Woolf T. B. Double bilayers and transmembrane gradients: A molecular dynamics study of a highly charged peptide. Biophys. J. 2008, 95, 3161–3173. 10.1529/biophysj.108.134049. PubMed DOI PMC

Darden T.; York D.; Pedersen L. Particle mesh Ewald: An N·log(N) method for Ewald sums in large systems. J. Chem. Phys. 1993, 98, 10089–10092. 10.1063/1.464397. DOI

Wennberg C. L.; Murtola T.; Hess B.; Lindahl E. Lennard-Jones lattice summation in bilayer simulations has critical effects on surface tension and lipid properties. J. Chem. Theory Comput. 2013, 9, 3527–3537. 10.1021/ct400140n. PubMed DOI

Melcr J.; Bonhenry D.; Timr S.; Jungwirth P. Transmembrane potential modeling: Comparison between methods of constant electric field and ion imbalance. J. Chem. Theory Comput. 2016, 12, 2418–2425. 10.1021/acs.jctc.5b01202. PubMed DOI

Kasparyan G.; Hub J. S. Equivalence of charge imbalance and external electric fields during free energy calculations of membrane electroporation. J. Chem. Theory Comput. 2023, 19, 2676–2683. 10.1021/acs.jctc.3c00065. PubMed DOI

Bilkova E.; Pleskot R.; Rissanen S.; Sun S.; Czogalla A.; Cwiklik L.; Róg T.; Vattulainen I.; Cremer P. S.; Jungwirth P.; et al. Calcium directly regulates phosphatidylinositol 4,5-bisphosphate headgroup conformation and recognition. J. Am. Chem. Soc. 2017, 139, 4019–4024. 10.1021/jacs.6b11760. PubMed DOI PMC

Duboue-Dijon E.; Javanainen M.; Delcroix P.; Jungwirth P.; Martinez-Seara H. A practical guide to biologically relevant molecular simulations with charge scaling for electronic polarization. J. Chem. Phys. 2020, 153, 050901.10.1063/5.0017775. PubMed DOI

Luo Y.; Roux B. Simulation of osmotic pressure in concentrated aqueous salt solutions. J. Phys. Chem. Lett. 2010, 1, 183–189. 10.1021/jz900079w. DOI

Sinelnikova A.; van der Spoel D. NMR refinement and peptide folding using the GROMACS software. J. Biomol. NMR 2021, 75, 143–149. 10.1007/s10858-021-00363-z. PubMed DOI PMC

Bischoff M.; Biriukov D.; Předota M.; Roke S.; Marchioro A. Surface potential and interfacial water order at the amorphous TiO2 nanoparticle/aqueous interface. J. Phys. Chem. C 2020, 124, 10961–10974. 10.1021/acs.jpcc.0c01158. PubMed DOI PMC

Allolio C.; Magarkar A.; Jurkiewicz P.; Baxová K.; Javanainen M.; Mason P. E.; Šachl R.; Cebecauer M.; Hof M.; Horinek D.; et al. Arginine-rich cell-penetrating peptides induce membrane multilamellarity and subsequently enter via formation of a fusion pore. Proc. Natl. Acad. Sci. U.S.A. 2018, 115, 11923–11928. 10.1073/pnas.1811520115. PubMed DOI PMC

Abraham M. J.; Murtola T.; Schulz R.; Páll S.; Smith J. C.; Hess B.; Lindahl E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX 2015, 1–2, 19–25. 10.1016/j.softx.2015.06.001. DOI

Páll S.; Zhmurov A.; Bauer P.; Abraham M.; Lundborg M.; Gray A.; Hess B.; Lindahl E. Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS. J. Chem. Phys. 2020, 153, 134110.10.1063/5.0018516. PubMed DOI

Nguyen M. T. H.; Biriukov D.; Tempra C.; Baxova K.; Martinez-Seara H.; Evci H.; Singh V.; Šachl R.; Hof M.; Jungwirth P.; et al. Ionic strength and solution composition dictate the adsorption of cell-penetrating peptides onto phosphatidylcholine membranes. Langmuir 2022, 38, 11284–11295. 10.1021/acs.langmuir.2c01435. PubMed DOI PMC

Jo S.; Lim J. B.; Klauda J. B.; Im W. CHARMM-GUI Membrane Builder for mixed bilayers and its application to yeast membranes. Biophys. J. 2009, 97, 50–58. 10.1016/j.bpj.2009.04.013. PubMed DOI PMC

Wu E. L.; Cheng X.; Jo S.; Rui H.; Song K. C.; Dávila-Contreras E. M.; Qi Y.; Lee J.; Monje-Galvan V.; Venable R. M.; et al. CHARMM-GUI membrane builder toward realistic biological membrane simulations. J. Comput. Chem. 2014, 35, 1997–2004. 10.1002/jcc.23702. PubMed DOI PMC

Lee J.; Cheng X.; Swails J. M.; Yeom M. S.; Eastman P. K.; Lemkul J. A.; Wei S.; Buckner J.; Jeong J. C.; Qi Y.; et al. CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J. Chem. Theory Comput. 2016, 12, 405–413. 10.1021/acs.jctc.5b00935. PubMed DOI PMC

Klauda J. B.; Venable R. M.; Freites J. A.; O’Connor J. W.; Tobias D. J.; Mondragon-Ramirez C.; Vorobyov I.; MacKerell A. D. Jr.; Pastor R. W. Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J. Phys. Chem. B 2010, 114, 7830–7843. 10.1021/jp101759q. PubMed DOI PMC

Lim J. B.; Rogaski B.; Klauda J. B. Update of the cholesterol force field parameters in CHARMM. J. Phys. Chem. B 2012, 116, 203–210. 10.1021/jp207925m. PubMed DOI

Jorgensen W. L.; Chandrasekhar J.; Madura J. D.; Impey R. W.; Klein M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79, 926–935. 10.1063/1.445869. DOI

Durell S. R.; Brooks B. R.; Ben-Naim A. Solvent-induced forces between two hydrophilic groups. J. Phys. Chem. 1994, 98, 2198–2202. 10.1021/j100059a038. DOI

Huang J.; Rauscher S.; Nawrocki G.; Ran T.; Feig M.; De Groot B. L.; Grubmüller H.; MacKerell A. D. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods 2017, 14, 71–73. 10.1038/nmeth.4067. PubMed DOI PMC

Nencini R.; Tempra C.; Biriukov D.; Polák J.; Ondo D.; Heyda J.; Ollila S. O.; Javanainen M.; Martinez-Seara H. Prosecco: polarization reintroduced by optimal scaling of electronic continuum correction origin in MD simulations. Biophys. J. 2022, 121, 157a.10.1016/j.bpj.2021.11.1935. PubMed DOI

Páll S.; Hess B. A flexible algorithm for calculating pair interactions on SIMD architectures. Comput. Phys. Commun. 2013, 184, 2641–2650. 10.1016/j.cpc.2013.06.003. DOI

Essmann U.; Perera L.; Berkowitz M. L.; Darden T.; Lee H.; Pedersen L. G. A smooth particle mesh Ewald method. J. Chem. Phys. 1995, 103, 8577–8593. 10.1063/1.470117. DOI

Nosé S. A unified formulation of the constant temperature molecular dynamics methods. J. Chem. Phys. 1984, 81, 511–519. 10.1063/1.447334. DOI

Hoover W. G. Canonical dynamics: Equilibrium phase-space distributions. Phys. Rev. A 1985, 31, 1695–1697. 10.1103/physreva.31.1695. PubMed DOI

Parrinello M.; Rahman A. Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 1981, 52, 7182–7190. 10.1063/1.328693. DOI

Hess B. P-LINCS: A Parallel Linear Constraint Solver for Molecular Simulation. J. Chem. Theory Comput. 2008, 4, 116–122. 10.1021/ct700200b. PubMed DOI

Hess B.; Bekker H.; Berendsen H. J.; Fraaije J. G. LINCS: a linear constraint solver for molecular simulations. J. Comput. Chem. 1997, 18, 1463–1472. 10.1002/(sici)1096-987x(199709)18:12<1463::aid-jcc4>3.0.co;2-h. DOI

Miyamoto S.; Kollman P. A. SETTLE: An analytical version of the SHAKE and RATTLE algorithm for rigid water models. J. Comput. Chem. 1992, 13, 952–962. 10.1002/jcc.540130805. DOI

Catte A.; Girych M.; Javanainen M.; Loison C.; Melcr J.; Miettinen M. S.; Monticelli L.; Määttä J.; Oganesyan V. S.; Ollila O. H. S.; et al. Molecular electrometer and binding of cations to phospholipid bilayers. Phys. Chem. Chem. Phys. 2016, 18, 32560–32569. 10.1039/c6cp04883h. PubMed DOI

Antila H.; Buslaev P.; Favela-Rosales F.; Ferreira T. M.; Gushchin I.; Javanainen M.; Kav B.; Madsen J. J.; Melcr J.; Miettinen M. S.; et al. Headgroup structure and cation binding in phosphatidylserine lipid bilayers. J. Phys. Chem. B 2019, 123, 9066–9079. 10.1021/acs.jpcb.9b06091. PubMed DOI

Kopec W.; Gapsys V. Periodic boundaries in Molecular Dynamics simulations: why do we need salt?. bioRxiv 2022, 10.1101/2022.10.18.512672. DOI

Martínez L.; Andrade R.; Birgin E. G.; Martínez J. M. PACKMOL: A package for building initial configurations for molecular dynamics simulations. J. Comput. Chem. 2009, 30, 2157–2164. 10.1002/jcc.21224. PubMed DOI

Wassenaar T. A.; Ingólfsson H. I.; Bockmann R. A.; Tieleman D. P.; Marrink S. J. Computational lipidomics with insane: A versatile tool for generating custom membranes for molecular simulations. J. Chem. Theory Comput. 2015, 11, 2144–2155. 10.1021/acs.jctc.5b00209. PubMed DOI

Tribello G. A.; Bonomi M.; Branduardi D.; Camilloni C.; Bussi G. PLUMED 2: New feathers for an old bird. Comput. Phys. Commun. 2014, 185, 604–613. 10.1016/j.cpc.2013.09.018. DOI

Pathways to a Shiny Future: Building the Foundation for Computational Physical Chemistry and Biophysics in 2050