General Purpose Coarse-Grained Force Field

Article16

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Last Updated: Wednesday, 21 August 2013 11:20

Polyunsaturated lipids are remarkably flexible molecules, with a great influence on the membrane structure and dynamics, affecting from mechanical properties to domain segregation. In this work, we studied phospholipid mixtures of dipalmitoylphosphatidylcholine (DPPC) and diunsaturated phosphatidylcholine lipids (diunsPC) of different lengths, by means of molecular dynamic simulations of a coarse-grained interaction model. These diunsPC:DPPC binary mixtures show nonideal behavior characterized by one mixed phase with composition fluctuations on a length scale of nanometers. Motivated by this observation, we studied comprehensively the characteristics of molecular structure as a function of the compositional gradient. We analyzed orientational order profiles, density distributions, and pair−pair correlation functions between the molecule residues. We observed that, in diunsPC-enriched regions, DPPC tails become expanded and disordered, especially toward the membrane center. On the other hand, in the more condensed DPPC-enriched patches, diunsaturated acyl chains become displaced toward the interface instead of stretching along the membrane normal. From the comparison of the two diunsPC lipids of different tail length, we measured that the presence of a longer terminal saturated segment induces better mixing with DPPC, and most interestingly eliminates the up−down composition correlation measured with the shorter tail-diunsPC. At molecular level, there is a reduced redistribution of densities and changes in the local order as a function of composition. We interpret these results as indicative that the packing incompatibility between polyunsaturated and saturated lipids rules their mixing behavior.

Article15

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Last Updated: Wednesday, 21 August 2013 11:20

Line-active molecules (“linactants”) that bind to the boundary interface between different fluid lipid domains in membranes have a strong potential as regulators of the lateral heterogeneity that is important for many biological processes. Here, we use molecular dynamics simulations in combination with a coarse-grain model that retains near-atomic resolution to identify lipid species that can act as linactants in a model membrane that is segregated into two lipid domains of different fluidity. Our simulations predict that certain hybrid saturated/unsaturated chain lipids can bind to the interface and lower the line tension, whereas cone-shaped lysolipids have a less pronounced effect.

Article14

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"Lipid mediated Interactions tune the association of Glycophorin A helix and its disruptive mutants in membranes"
D. Sengupta, S.J. Marrink. Phys. Chem. Chem. Phys., 12:12987-12996, 2010.

The specific and non-specific driving forces of helix association within membranes are still poorly understood. Here, we use coarse-grain molecular dynamics simulations to study the association behavior of glycophorin A and two disruptive mutants, T87F and a triple mutant of the GxxxG motif (G79LG83LG86L), embedded in a lipid membrane. Self-assembly simulations and the association free-energy profile confirm an energetically-favorable dimerized state for both the wild type and the mutants. The reduced association of the mutants compared to the wild type, as observed in experiments, can be justified from comparisons of the free energy profiles. Less-favorable protein–protein interactions as well as disruption of lipid packing around the mutant dimers is responsible for their reduced association. The role of the non-specific “lipid-phobic” contribution appears to be as important as the specific “helix–helix” contribution. However, the differences between the wild type and mutants are subtle and our simulations predict a dimerization state not only for the wild-type glycophorin A, but also for these ‘disruptive’ mutants. Our results highlight the importance of both specific as well as non-specific driving forces in the association of transmembrane helices, and point to the need of more careful interpretation of experimental measurements.

Article13

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Last Updated: Wednesday, 21 August 2013 11:20

"Direct Simulation of Protein-Mediated Vesicle Fusion: Lung Surfactant Protein B"
S. Baoukina, D.P. Tieleman. Biophys. J. 2010, 99, 2134-2142

We simulated spontaneous fusion of small unilamellar vesicles mediated by lung surfactant protein B (SP-B) using the MARTINI force field. An SP-B monomer triggers fusion events by anchoring two vesicles and facilitating the formation of a lipid bridge between the proximal leaflets. Once a lipid bridge is formed, fusion proceeds via a previously described stalk – hemifusion diaphragm – pore-opening pathway. In the absence of protein, fusion of vesicles was not observed in either unbiased simulations or upon application of a restraining potential to maintain the vesicles in close proximity. The shape of SP-B appears to enable it to bind to two vesicles at once, forcing their proximity, and to facilitate the initial transfer of lipids to form a high-energy hemifusion intermediate. Our results may provide insight into more general mechanisms of protein-mediated membrane fusion, and a possible role of SP-B in the secretory pathway and transfer of lung surfactant to the gas exchange interface..

Article12

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Last Updated: Wednesday, 21 August 2013 11:20

"Splaying of Aliphatic Tails Plays a Central Role in Barrier Crossing During Liposome Fusion"
D. Mirjanian, A.N. Dickey, J.H. Hoh, T.B. Woolf, M.J. Stevens. J. Phys. Chem. B 2010, 114, 11061–11068

The fusion between two lipid bilayers involves crossing a complicated energy landscape. The limiting barrier
in the process appears to be between two closely opposed bilayers and the intermediate state where the outer
leaflets are fused. We have performed molecular dynamics simulations to characterize the free energy barrier
for the fusion of two liposomes and to examine the molecular details of barrier crossing. To capture the slow
dynamics of fusion, a model using coarse-grained representations of lipids was used. The fusion between
pairs of liposomes was simulated for four systems: DPPC, DOPC, a 3:1 mixture of DPPC/DPPE, and an
asymmetric lipid tail system in which one tail of DPPC was reduced to half the length (ASTail). The weighted
histogram method was used to compute the free energy as a function of separation distance. The relative
barrier heights for these systems was found to be ASTail . DPPC > DPPC/DPPE > DOPC, in agreement
with experimental observations. Further, the free energy curves for all four can be overlaid on a single curve
by plotting the free energy versus the surface separation (differing only in the point of fusion). These simulations
also confirm that the two main contributions to the free energy barrier are the removal of water between the
vesicles and the deformation of the vesicle. The most prominent molecular detail of barrier crossing in all
cases examined was the splaying of lipid tails, where initially a single splayed lipid formed a bridge between
the two outer leaflets that promotes additional lipid mixing between the vesicles and eventually leads to
fusion. The tail splay appears to be closely connected to the energetics of the process. For example, the high
barrier for the ASTail is the result of a smaller distance between terminal methyl groups in the splayed
molecule. The shortening of this distance requires the liposomes to be closer together, which significantly
increases the cost of water removal and bilayer deformation. Before tail splay can initiate fusion, contact
must occur between a tail end and the external water. In isolated vesicles, the contact fraction is correlated
to the fusogenicity difference between DPPC and DOPC. Moreover, for planar bilayers, the contact fraction
is much lower for DPPC, which is consistent with its lack of fusion in giant vesicles. The simulation results
show the key roles of lipid tail dynamics in governing the fusion energy landscape.

Lipid Bilayers

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Last Updated: Thursday, 11 February 2021 11:23

Many properties of lipid membranes have been characterized over the past decades by all-atom models. Such properties include the area per lipid, order parameters, and density profiles for instance. Currently 100s of nanoseconds are routinely probed for membranes containing a few thousands of lipids.

However, for many membrane related processes more extensive sampling is required, either in the time domain or in terms of an increased system size to study collective events. In those cases the Martini model is a good alternative. Examples include the nucleation of gel domains in either pure [1] or mixed [2] lipid membranes (see figure), transition toward non-lamellar phases [3], partitioning of other compounds such as alcohols [9,19], voltage sensitive dyes [4], phytochemicals [12], the flip-flop of cholesterol [5,6] and the clustering behavior of gangliosides [17]. Furthermore, extensive sampling allowed us to compute the local area compressibility along the membrane normal, an important quantity that had not been considered before [11].

The Martini model can also be efficiently used for systematic studies in which a large number of simulations need to be performed, i.e., in high-throughput applications. For instance, the membrane area and thickness as a function of location of double bonds [7], or the self-diffusion of transmembrane peptides as a function of peptide sequence [8] have been systematically explored with Martini, as well as the in-silico design of membranes with controlled properties using e.g. bolalipids [10]. More recently, the effect of periodic boundary conditions on the lipid self-diffusion has been tested in a series of long timescale and increasing length scale simulations [18] up to patches of more than half a million lipids [22]. In another high-throughput application, Martini was used to study the membrane permeation process of more than 500000 (!) compounds [23].

A number of dedicated tools are available to automatize the initialization of Martini membrane simulations, such as Insane [14] and Charmm GUI Martini-maker [15,16], with hundreds of different lipid types currently available. For even larger scale lipid applications, the Dry martini force field is available [13]. Coupling to all-atom membrane models can be done with our virtual site approach [20,21].

• [1] S.J. Marrink, J. Risselada, A.E. Mark. Simulation of gel phase formation and melting in lipid bilayers using a coarse grained model. Chem. Phys. Lip., 135:223-244, 2005.
• [2] R. Faller, S.J. Marrink. Simulation of domain formation in DLPC-DSPC mixed bilayers. Langmuir, 20:7686-7693, 2004.
• [3] S.J. Marrink, A.E. Mark. Molecular view of hexagonal phase formation in phospholipid membranes. Biophys. J., 87:3894-3900, 2004.
• [4] M.J. Hinner, S.J. Marrink, A.H. de Vries. Location, tilt, and binding: a molecular dynamics study of voltage sensitve dyes in biomembranes. J. Phys. Chem. B, 113:15807-15819, 2009.
• [5] S.J. Marrink, A.H. de Vries, T.A. Harroun, J. Katsaras, S.R. Wassall. Cholesterol shows preference for the interior of polyunsaturated lipid membranes. JACS, 130:10-11, 2008.
• [6] W.F.D. Bennett, J.L. MacCallum, M.J. Hinner, S.J. Marrink, D.P. Tieleman. A molecular view of cholesterol flip-flop and chemical potential in different membrane environments. JACS, 131:12714-12720, 2009.
• [7] N. Kucerka, J. Gallova, D. Uhrikova, P. Balgavy, M. Bulacu, S.J. Marrink, J. Katsaras. Areas of monounsaturated diacylphosphatidylcholines. Biophys. J., 97:1926-1932, 2009.
• [8] S. Ramadurai, A. Holt, L.V. Schäfer, V.V. Krasnikov, D.T.S. Rijkers, S.J. Marrink, J.A. Killian, B. Poolman. Influence of hydrophobic mismatch and amino acid composition on the lateral diffusion of transmembrane peptides. Biophys. J., 99:1447-1454, 2010.
• [9] M. Klacsová,  M. Bulacu, N. Kučerka, D. Uhríková, J. Teixeirad, S.J. Marrink, P. Balgavý. The effect of aliphatic alcohols on fluid bilayers in unilamellar DOPC vesicles – a small-angle neutron scattering and molecular dynamics study. BBA Biomembr., 808:2136-2146, 2011. abstract
• [10] M. Bulacu, X. Periole, S.J. Marrink. In-silico design of robust bolalipid membranes, Biomacromol., 13:196–205, 2012. abstract
• [11] F. Campelo, C. Arnarez, S.J. Marrink, M.M. Kozlov. Helfrich model of membrane bending: from Gibbs theory of liquid interfaces to membranes as thick anisotropic elastic layers. Adv. Colloid Interf. Sci., 208:25-33, 2014. abstract
• [12] H.I. Ingólfsson, P. Thakur, K.F. Herold, E.A. Hobart, N.B. Ramsey, X. Periole, D.H. de Jong, M. Zwama, D. Yilmaz, K. Hall, T. Maretzky, H.C. Hemmings, C. Blobel, S.J. Marrink, A. Kocer, J.T. Sack, O.S. Andersen. Phytochemicals perturb membranes and promiscuously alter protein function. ACS Chem. Biol., 9:1788–1798, 2014. abstract
• [13] C. Arnarez, J.J. Uusitalo, M.F. Masman, H.I. Ingólfsson, D.H. de Jong, M.N. Melo, X. Periole, A.H. De Vries, S.J. Marrink. Dry Martini, a coarse-grained force field for lipid membrane simulations with implicit solvent. JCTC, 11:260–275, 2015. abstract
• [14] T.A. Wassenaar, H.I. Ingólfsson, R.A. Böckmann, D.P. Tieleman, S.J. Marrink. Computational lipidomics with insane: a versatile tool for generating custom membranes for molecular simulations. JCTC, 11:2144–2155, 2015. abstract
• [15] Y. Qi, H.I. Ingólfsson, X. Cheng, J. Lee, S.J. Marrink, W. Im. CHARMM-GUI Martini Maker for coarse-grained simulations with the Martini force field. JCTC, 11:4486–4494, 2015. abstract
• [16] P.C. Hsu, B.M.H. Bruininks, D. Jefferies, P.C. Telles de Souza, J. Lee, D.S. Patel, S.J .Marrink, Y. Qi, S. Khalid, W. Im. CHARMM‐GUI Martini Maker for modeling and simulation of complex bacterial membranes with lipopolysaccharides. J. Comput. Chem., 38:2354–2363, 2017. abstract
• [17] R.X. Gu, H.I. Ingólfsson, A.H. de Vries, S.J. Marrink, D.P. Tieleman. Ganglioside-lipid and ganglioside-protein interactions revealed by coarse-grained and atomistic molecular dynamics simulations. JPCB, 121:3262–3275, 2017. open access
• [18] R.M. Venable, H.I. Ingólfsson, M.G. Lerner, B.S. Perrin, Jr., B.A. Camley, S.J. Marrink, F.L.H. Brown, R.W. Pastor. Lipid and peptide diffusion in bilayers: The Saffman-Delbrück model and periodic boundary conditions. JPCB, 121:3443–3457, 2017. abstract
• [19] T. Kondela, J. Gallová, T. Hauß, J. Barnoud, S.J. Marrink, N. Kučerka. Alcohol interactions with lipid bilayers. Molecules, 22:2078, 2017. abstract
• [20] Y. Liu, W. Pezeshkian, J. Barnoud, A.H. de Vries, S.J. Marrink. Coupling coarse-grained to fine-grained models via Hamiltonian replica exchange. JCTC, 2020. doi.org/10.1021/acs.jctc.0c00429
• [21] Y. Liu, A.H. de Vries, J. Barnoud, W. Pezeshkian, J. Melcr, S.J. Marrink. Dual resolution membrane simulations using virtual sites. JPCB 124:3944, 2020. doi.org/10.1021/acs.jpcb.0c01842
• [22] M. Vögele, J. Köfinger, G. Hummer. Hydrodynamics of Diffusion in Lipid Membrane Simulations. Phys. Rev. Lett. 120:268104, 2018.
• [23] R. Menichetti, K.H. Kanekal, T. Bereau. Drug–Membrane Permeability across Chemical Space. ACS Central Science 5:290-298, 2019.
  doi:10.1021/acscentsci.8b00718