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Coarse-Grained Force Fields for Molecular Simulations

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Molecular Modeling of Proteins

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1215))

Abstract

Molecular dynamics (MD) simulations at the atomic scale are a powerful tool to study the structure and dynamics of model biological systems. However, because of their high computational cost, the time and length scales of atomistic simulations are limited. Biologically important processes, such as protein folding, ion channel gating, signal transduction, and membrane remodeling, are difficult to investigate using atomistic simulations. Coarse-graining reduces the computational cost of calculations by reducing the number of degrees of freedom in the model, allowing simulations of larger systems for longer times. In the first part of this chapter we review briefly some of the coarse-grained models available for proteins, focusing on the specific scope of each model. Then we describe in more detail the MARTINI coarse-grained force field, and we illustrate how to set up and run a simulation of a membrane protein using the Gromacs software package. We explain step-by-step the preparation of the protein and the membrane, the insertion of the protein in the membrane, the equilibration of the system, the simulation itself, and the analysis of the trajectory.

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References

  1. Dror RO, Dirks RM, Grossman JP, Xu H, Shaw DE (2012) Biomolecular simulation: a computational microscope for molecular biology. Annu Rev Biophys 41:429–452

    Article  PubMed  CAS  Google Scholar 

  2. Shaw DE, Chao JC, Eastwood MP, Gagliardo J, Grossman JP, Ho CR et al (2008) Anton, a special-purpose machine for molecular dynamics simulation. Commun ACM 51:91

    Article  Google Scholar 

  3. Lindorff-Larsen K, Piana S, Dror RO, Shaw DE (2011) How fast-folding proteins fold. Science 334:517–520

    Article  PubMed  CAS  Google Scholar 

  4. Bussi G, Laio A, Parrinello M (2006) Equilibrium free energies from non-equilibrium metadynamics. Phys Rev Lett 96:090601

    Article  PubMed  Google Scholar 

  5. Sugita Y, Okamoto Y (1999) Replica-exchange molecular dynamics method for protein folding. Chem Phys Lett 314:141–151

    Article  CAS  Google Scholar 

  6. Torrie GM, Valleau JP (1977) Nonphysical sampling distributions in Monte Carlo free-energy estimation: umbrella sampling. J Comput Phys 23:187–199

    Article  Google Scholar 

  7. Carbone P, Varzaneh HAK, Chen X, Müller-Plathe F (2008) Transferability of coarse-grained force fields: the polymer case. J Chem Phys 128:064904

    Article  PubMed  Google Scholar 

  8. Levitt M, Warshel A (1975) Computer simulation of protein folding. Nature 253:694–698

    Article  PubMed  CAS  Google Scholar 

  9. Liwo A, Oldziej S, Pincus MR, Wawak RJ, Rackovsky S, Scheraga HA (1997) A united-residue force field for off-lattice protein-structure simulations. I. Functional forms and parameters of long-range side-chain interaction potentials from protein crystal data. J Comput Chem 18:849–873

    Article  CAS  Google Scholar 

  10. Maupetit J, Tuffery P, Derreumaux P (2007) A coarse-grained protein force field for folding and structure prediction. Proteins 69:394–408

    Article  PubMed  CAS  Google Scholar 

  11. Bereau T, Deserno M (2009) Generic coarse-grained model for protein folding and aggregation. J Chem Phys 130:235106

    Article  PubMed  PubMed Central  Google Scholar 

  12. Pasi M, Lavery R, Ceres N (2013) PaLaCe: a coarse-grain protein model for studying mechanical properties. J Chem Theory Comput 9:785–793

    Article  CAS  Google Scholar 

  13. Zacharias M (2003) Protein-protein docking with a reduced protein model accounting for side-chain flexibility. Protein Sci 12:1271–1282

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  14. Setny P, Zacharias M (2011) A coarse-grained force field for Protein-RNA docking. Nucleic Acids Res 39:9118–9129

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  15. Den Otter WK, Renes MR, Briels WJ (2010) Asymmetry as the key to clathrin cage assembly. Biophys J 99:1231–1238

    Article  Google Scholar 

  16. Matthews R, Likos CN (2013) Structures and pathways for clathrin self-assembly in the bulk and on membranes. Soft Matter 9:5794–5806. doi:10.1039/c3sm50737h

    Article  CAS  Google Scholar 

  17. Shi Q, Izvekov S, Voth GA (2006) Mixed atomistic and coarse-grained molecular dynamics: simulation of a membrane-bound ion channel. J Phys Chem B 110:15045–15048

    Article  PubMed  CAS  Google Scholar 

  18. Rzepiela AJ, Louhivuori M, Peter C, Marrink SJ (2011) Hybrid simulations: combining atomistic and coarse-grained force fields using virtual sites. Phys Chem Chem Phys 13:10437–10448

    Article  PubMed  CAS  Google Scholar 

  19. Zacharias M (2013) Combining coarse-grained nonbonded and atomistic bonded interactions for protein modeling. Proteins 81:81–92

    Article  PubMed  CAS  Google Scholar 

  20. Taylor WR, Katsimitsoulia Z (2010) A coarse-grained molecular model for actin-myosin simulation. J Mol Graph Model 29:266–279

    Article  PubMed  CAS  Google Scholar 

  21. Praprotnik M, Delle Site L (2013) Multiscale molecular modeling. Methods Mol Biol 924:567–583

    Article  PubMed  CAS  Google Scholar 

  22. Marrink SJ, de Vries AH, Mark AE (2004) Coarse grained model for semiquantitative lipid simulations. J Phys Chem B 108:750–760

    Article  CAS  Google Scholar 

  23. Marrink SJ, Risselada HJ, Yefimov S, Tieleman DP, De Vries AH (2007) The MARTINI force field: coarse grained model for biomolecular simulations. J Phys Chem B 111:7812–7824

    Article  PubMed  CAS  Google Scholar 

  24. Monticelli L, Kandasamy SK, Periole X, Larson RG, Tieleman DP, Marrink S-J (2008) The MARTINI coarse-grained force field: extension to proteins. J Chem Theory Comput 4:819–834

    Article  CAS  Google Scholar 

  25. De Jong DH, Singh G, Bennett WFD, Arnarez C, Wassenaar TA, Schäfer LV et al (2013) Improved parameters for the martini coarse-grained protein force field. J Chem Theory Comput 9:687–697

    Article  Google Scholar 

  26. Marrink SJ, Tieleman DP (2013) Perspective on the Martini model. Chem Soc Rev 42:6801–6822. doi:10.1039/c3cs60093a

    Article  PubMed  CAS  Google Scholar 

  27. López CA, Rzepiela AJ, de Vries AH, Dijkhuizen L, Hünenberger PH, Marrink SJ (2009) Martini coarse-grained force field: extension to carbohydrates. J Chem Theory Comput 5:3195–3210

    Article  Google Scholar 

  28. Rossi G, Fuchs PFJ, Barnoud J, Monticelli L (2012) A coarse-grained MARTINI model of polyethylene glycol and of polyoxyethylene alkyl ether surfactants. J Phys Chem B 116:14353–14362

    Article  PubMed  CAS  Google Scholar 

  29. Rossi G, Monticelli L, Puisto SR, Vattulainen I, Ala-Nissila T (2011) Coarse-graining polymers with the MARTINI force-field: polystyrene as a benchmark case. Soft Matter 7:698

    Article  CAS  Google Scholar 

  30. Wong-Ekkabut J, Baoukina S, Triampo W, Tang I-M, Tieleman DP, Monticelli L (2008) Computer simulation study of fullerene translocation through lipid membranes. Nat Nanotechnol 3:363–368

    Article  PubMed  CAS  Google Scholar 

  31. Monticelli L (2012) On atomistic and coarse-grained models for C60 fullerene. J Chem Theory Comput 8:1370–1378

    Article  CAS  Google Scholar 

  32. Marrink SJ, Mark AE (2003) The mechanism of vesicle fusion as revealed by molecular dynamics simulations. J Am Chem Soc 125:11144–11145

    Article  PubMed  CAS  Google Scholar 

  33. Risselada HJ, Marrink SJ (2008) The molecular face of lipid rafts in model membranes. Proc Natl Acad Sci U S A 105:17367–17372

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  34. Baoukina S, Marrink SJ, Tieleman DP (2012) Molecular structure of membrane tethers. Biophys J 102:1866–1871

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  35. Baron R, Trzesniak D, de Vries AH, Elsener A, Marrink SJ, van Gunsteren WF (2007) Comparison of thermodynamic properties of coarse-grained and atomic-level simulation models. ChemPhysChem 8:452–461

    Article  PubMed  CAS  Google Scholar 

  36. Shih AY, Arkhipov A, Freddolino PL, Schulten K (2006) Coarse grained protein-lipid model with application to lipoprotein particles. J Phys Chem B 110:3674–3684

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  37. Shinoda W, DeVane R, Klein ML (2010) Zwitterionic lipid assemblies: molecular dynamics studies of monolayers, bilayers, and vesicles using a new coarse grain force field. J Phys Chem B 114:6836–6849

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  38. Yesylevskyy SO, Schäfer LV, Sengupta D, Marrink SJ (2010) Polarizable water model for the coarse-grained MARTINI force field. PLoS Comput Biol 6:e1000810

    Article  PubMed  PubMed Central  Google Scholar 

  39. Monticelli L, Tieleman DP, Fuchs PFJ (2010) Interpretation of 2H-NMR experiments on the orientation of the transmembrane helix WALP23 by computer simulations. Biophys J 99:1455–1464

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  40. Castillo N, Monticelli L, Barnoud J, Tieleman DP (2013) Free energy of WALP23 dimer association in DMPC, DPPC, and DOPC bilayers. Chem Phys Lipids 169:95–105

    Article  PubMed  CAS  Google Scholar 

  41. Deplazes E, Louhivuori M, Jayatilaka D, Marrink SJ, Corry B (2012) Structural Investigation of MscL gating using experimental data and coarse grained MD simulations. PLoS Comput Biol 8:e1002683

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  42. Periole X, Cavalli M, Marrink S-J, Ceruso MA (2009) Combining an elastic network with a coarse-grained molecular force field: structure, dynamics, and intermolecular recognition. J Chem Theory Comput 5:2531–2543

    Article  CAS  Google Scholar 

  43. Dony N, Crowet JM, Joris B, Brasseur R, Lins L (2013) SAHBNET, an accessible surface-based elastic network: an application to membrane protein. Int J Mol Sci 14:11510–11526

    Article  PubMed  PubMed Central  Google Scholar 

  44. Pronk S, Páll S, Schulz R, Larsson P, Bjelkmar P, Apostolov R et al (2013) GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29:845–854

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  45. Kabsch W, Sander C (1983) Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22:2577–2637

    Article  PubMed  CAS  Google Scholar 

  46. Okada T, Fujiyoshi Y, Silow M, Navarro J, Landau EM, Shichida Y (2002) Functional role of internal water molecules in rhodopsin revealed by X-ray crystallography. Proc Natl Acad Sci U S A 99:5982–5987

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  47. Humphrey W, Dalke A, Schulten K (1996) VMD – visual molecular dynamics. J Mol Graph 14:33–38

    Article  PubMed  CAS  Google Scholar 

  48. Jo S, Lim JB, Klauda JB, Im W (2009) CHARMM-GUI Membrane Builder for mixed bilayers and its application to yeast membranes. Biophys J 97:50–58

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  49. Lomize MA, Lomize AL, Pogozheva ID, Mosberg HI (2006) OPM: orientations of proteins in membranes database. Bioinformatics 22:623–625

    Article  PubMed  CAS  Google Scholar 

  50. Lomize MA, Pogozheva ID, Joo H, Mosberg HI, Lomize AL (2012) OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Res 40:D370–D376

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  51. Tusnády GE, Dosztányi Z, Simon I (2004) Transmembrane proteins in the Protein Data Bank: identification and classification. Bioinformatics 20:2964–2972

    Article  PubMed  Google Scholar 

  52. Tusnády GE, Dosztányi Z, Simon I (2005) PDB_TM: selection and membrane localization of transmembrane proteins in the protein data bank. Nucleic Acids Res 33:D275–D278

    Article  PubMed  PubMed Central  Google Scholar 

  53. Kozma D, Simon I, Tusnády GE (2013) PDBTM: protein data bank of transmembrane proteins after 8 years. Nucleic Acids Res 41:D524–D529

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  54. Tusnády GE, Dosztányi Z, Simon I (2005) TMDET: web server for detecting transmembrane regions of proteins by using their 3D coordinates. Bioinformatics 21:1276–1277

    Article  PubMed  Google Scholar 

  55. Schmidt TH, Kandt C (2012) LAMBADA and InflateGRO2: efficient membrane alignment and insertion of membrane proteins for molecular dynamics simulations. J Chem Inf Model 52:2657–2669

    Article  PubMed  CAS  Google Scholar 

  56. Wolf MG, Hoefling M, Aponte-Santamaría C, Grubmüller H, Groenhof G (2010) g_membed: efficient insertion of a membrane protein into an equilibrated lipid bilayer with minimal perturbation. J Comput Chem 31:2169–2174

    Article  PubMed  CAS  Google Scholar 

  57. Kandt C, Ash WL, Tieleman DP (2007) Setting up and running molecular dynamics simulations of membrane proteins. Methods 41:475–488

    Article  PubMed  CAS  Google Scholar 

  58. Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81:3684

    Article  CAS  Google Scholar 

  59. Bussi G, Donadio D, Parrinello M (2007) Canonical sampling through velocity rescaling. J Chem Phys 126:014101

    Article  PubMed  Google Scholar 

  60. Parrinello M, Rahman A (1981) Polymorphic transitions in single crystals: a new molecular dynamics method. J Appl Phys 52:7182

    Article  CAS  Google Scholar 

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Acknowledgments

The authors thank Juliette Martin and Nicoletta Ceres for their useful comments on the manuscript.

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Correspondence to Luca Monticelli .

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Barnoud, J., Monticelli, L. (2015). Coarse-Grained Force Fields for Molecular Simulations. In: Kukol, A. (eds) Molecular Modeling of Proteins. Methods in Molecular Biology, vol 1215. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1465-4_7

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  • DOI: https://doi.org/10.1007/978-1-4939-1465-4_7

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1464-7

  • Online ISBN: 978-1-4939-1465-4

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