Martini Artefacts

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Last Updated: Tuesday, 23 March 2021 15:43

martini-glass.pngmartini-glass-break.pngTS2CG-Martiniglass.jpgbunny_equil_lipids.jpg

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Membrane shapes

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Last Updated: Wednesday, 25 January 2023 14:26

Membranes provide identity not only to the cell as a whole, through the enveloping plasma membrane, but also to many internal organelles. Membrane spatial organization ranges from a locally flat, lamellar geometry to highly curved ones as can be found, for instance, in the endoplasmic reticulum, Golgi apparatus, thylakoids, or mitochondria. Moreover, these structures are dynamic, involved in many remodelling processes often with highly curved intermediates.

Martini-based simulations have proven useful in capturing these membrane shapes, from the strongly curved regions present in small lipid vesicles [1,2] and lipid tethers [3], to the large scale undulations of planar membrane patches. These type of simulations provide important clues about the interplay between curvature and protein/lipid sorting (see Figure, taken from [4]).

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Recently, efforts are directed in modeling realistic shapes of large cellular substructures and even entire organelles, such as the mitochondrion [5]. A sophisticated tool to generate Martini membranes with arbitrary curvatures is TS2CG [5,6], and a tool to identify lipid leaflets in complex curved membranes is also available [7].

In addition, recent Martini-based simulation efforts are directed to understand membrane curvature generation via protein-lipid interplay. Recent examples include the strong membrane deformations induced by ECF transporters [8] and around a signal peptidase [9], and membrane deformation induced by functionalized oligonucleotides [10].

  • [1] H.J. Risselada, S.J. Marrink. Curvature effects on lipid packing and dynamics in liposomes revealed by coarse grained molecular dynamics simulations. Phys. Chem. Chem. Phys., 11:2056-2067, 2009.
  • [2] H.J. Risselada, S.J. Marrink, M. Muller. Curvature-dependent elastic properties of liquid-ordered domains result in inverted domain sorting on uniaxially compressed vesicles. Phys. Rev. Lett., 106:148102, 2011. abstract
  • [3] S. Baoukina, H.I. Ingólfsson, S.J. Marrink, D.P. Tieleman. Curvature‐Induced Sorting of Lipids in Plasma Membrane Tethers. Advanced Theory Simul., 1:1800034, 2018. doi:10.1002/adts.201800034
  • [4] W. Pezeshkian, S.J. Marrink. Simulating realistic membrane shapes. Curr. Opin. Cell Biol., 71:103-111, 2021. https://doi.org/10.1016/j.ceb.2021.02.009
  • [5] W. Pezeshkian, M. Konig, T.A. Wassenaar, S.J. Marrink. Backmapping triangulated surfaces to coarse-grained membrane models. Nature Commun. 11:2296, 2020. doi.org/10.1038/s41467-020-16094-y
  • [6] W. Pezeshkian, M. König, S.J. Marrink, J.H. Ipsen. A multi-scale approach to membrane remodeling processes. Front. Mol. Biosci. 6, 59, 2019. doi:10.3389/fmolb.2019.00059
  • [7] B.M.H. Bruininks, A.S. Thie, P.C.T. Souza, T.A. Wassenaar, S. Faraji, S.J. Marrink. Sequential Voxel-Based Leaflet Segmentation of Complex Lipid Morphologies. J. Chem. Theory Comput., 2021. online
  • [8] I. Faustino, H. Abdizadeh, P.C.T. Souza, A. Jeucken, W.K. Stanek, A. Guskov, D.J. Slotboom, S.J. Marrink. Membrane mediated toppling mechanism of the folate energy coupling factor transporter. Nature Commun. 11:1763, 2020. doi.org/10.1038/s41467-020-15554-9
  • [9] A.M. Liaci, ..., S.J.Marrink, R.A.Scheltema, F. Förster. Structure of the human signal peptidase complex reveals the determinants for signal peptide cleavage. Mol. Cell. 81, 3934-3948, 2021. https://doi.org/10.1016/j.molcel.2021.07.031
  • [10] N. De Franceschi, W. Pezeshkian, A. Fragasso, B.M.H. Bruininks, S. Tsai, S.J. Marrink, C. Dekker. Synthetic Membrane Shaper for Controlled Liposome Deformation. ACS Nano, online, 2023. doi:10.1021/acsnano.2c06125

Human Scale Martini

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Last Updated: Wednesday, 15 January 2014 22:19

Using top-secret parameters, Martini now also simulates full-body humans:

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Movies of the girl and boy in a simulated tap-dancing routine can be downloaded: (girl, boy)

Carbohydrates

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Last Updated: Sunday, 27 November 2022 15:09

 

sugars2Carbohydrates (saccharides), the most abundant product of photosynthesis, play an important role in the energetic metabolism of living species and the signaling and immunological responses and are a fundamental component of the external cell wall of many organisms. In addition, saccharides are present in a variety of emerging classes of biomimetic materials. Furthermore, due to their cryo- and anhydro-protective properties, many sugars have been shown to be effective stabilizers of biological components, such as proteins and membranes, in the low-temperature or dehydrated states. This class of compounds encompasses a huge variety of possible monomeric units (differing in stereochemistry and functionalization) that can be connected in chains presenting a virtually infinite number of possible residue sequences, linkage types, and degrees of branching.

The large size of most oligosaccharides warrants the use of a coarse-grained model, yet the complexity of carbohydrate physico-chemical properties makes this a very challenging undertaking. In 2009, Martini has been parameterized for common mono- and disaccharides [1,5] that can serve as a basis for further carbohydrate modeling. Based on this model, oligosaccharides such as amylose [1], cellulose [2,6], and cyclodextrins [4] have been parameterized as well.

Other extensions include the important class of glyco-lipids, with parameters for MGDG, DGDG, SQDG, PI, PIPn, GCER, and GM1 [3], as well as lipopolysaccharides [7], and the ability to simulate glycans  [8].

The latest carbohydrate parameters compatible with Martini 3 can be found here [9].

  • [1] C.A. Lopez, A. Rzepiela, A.H. de Vries, L. Dijkhuizen, P.H. Huenenberger, S.J. Marrink. The Martini coarse grained force field: extension to carbohydrates. J. Chem. Th. Comp., 5:3195-3210, 2009.
  • [2] J. Wohlert, L.A. Berglund. A coarse-grained model for molecular dynamics simulations of native cellulose. J. Chem. Theo. Comp. 7:753-760, 2011.
  • [3] C.A. Lopez, Z. Sovova, F.J. van Eerden, A.H. de Vries, S.J. Marrink. Martini force field parameters for glycolipids. JCTC, 9:1694–1708, 2013. abstract
  • [4] C.A. Lopez, A.H. de Vries, S.J. Marrink. Computational microscopy of cyclodextrin mediated cholesterol extraction from lipid model membranes. Sci. Rep., 3:2071, 2013. open access
  • [5] G. Moiset, C.A. López, R. Bartelds, L. Syga, E. Rijpkema, A. Cukkemane, M. Baldus, B. Poolman, S.J. Marrink. Disaccharides impact the lateral organization of lipid membranes. JACS, 136:16167-16175, 2014. open access
  • [6] C.A. López, G. Bellesia, A. Redondo, P. Langan, S.P.S. Chundawat, B.E. Dale, S.J. Marrink, S. Gnanakaran. MARTINI coarse-grained model for crystalline cellulose microfibers. JPCB, 119:465–473, 2015. abstract
  • [7] 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
  • [8] A.T. Shivgan, J.K. Marzinek, R.G. Huber, A. Krah, R.H. Henchman, P. Matsudaira, C.S. Verma, P.J. Bond. Extending the Martini Coarse-Grained Force Field to N-Glycans. J. Chem. Inf. Mod. 60:3864-3883, 2020. open access
  • [9] F. Grünewald, M.H. Punt, E.E. Jefferys, P.A. Vainikka, M. König, V. Virtanen, T.A. Meyer, W. Pezeshkian, A.J. Gormley, M. Karonen, M.S.P. Sansom, P.C.T. Souza, S.J. Marrink. Martini 3 Coarse-Grained Force Field for Carbohydrates. Journal of Chemical Theory and Computation, online, 2022. https://pubs.acs.org/doi/10.1021/acs.jctc.2c00757