Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

Coarse-grained molecular dynamics simulations of biomolecules

1 Department of Cardiovascular Physiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan;
2 School of Medicine, Okayama University, Okayama, Japan

Coarse-grained molecular dynamics (CGMD) simulations are increasingly being used to analyze the behaviors of biological systems. When appropriately used, CGMD can simulate the behaviors of molecular systems several hundred times faster than elaborate all-atom molecular dynamics simulations with similar accuracy. CGMD parameters for lipids, proteins, nucleic acids, and some artificial substances such as carbon nanotubes have been suggested. Here we briefly discuss a method for CGMD system configuration and the types of analysis and perturbations that can be performed with CGMD simulations. We also describe specific examples to show how CGMD simulations have been applied to various situations, and then describe experimental results that were used to validate the simulation results. CGMD simulations are applicable to resolving problems for various biological systems.
  Figure/Table
  Supplementary
  Article Metrics

Keywords coarse-grained molecular dynamics; all atom-molecular dynamics; reverse graining; protein-protein interactions; protein-lipid interactions; in silico drug design

Citation: Ken Takahashi, Takayuki Oda, Keiji Naruse. Coarse-grained molecular dynamics simulations of biomolecules. AIMS Biophysics, 2014, 1(1): 1-15. doi: 10.3934/biophy.2014.1.1

References

  • 1. Scuseria GE (1999) Linear Scaling Density Functional Calculations with Gaussian Orbitals. J Phys Chem A 103: 4782-4790.    
  • 2. Go N (1983) Theoretical Studies of Protein Folding. Annu Rev Biophys Bioeng 12: 183-210.    
  • 3. Doi K, Takeuchi H, Nii R, et al. (2013) Self-assembly of 50 bp poly(dA).poly(dT) DNA on highly oriented pyrolytic graphite via atomic force microscopy observation and molecular dynamics simulation. J Chem Phys 139: 085102.
  • 4. Lin J, Alexander-Katz A (2013) Cell Membranes Open "Doors" for Cationic Nanoparticles/Biomolecules: Insights into Uptake Kinetics. ACS Nano 7: 10799-10808.    
  • 5. Tozzini V (2005) Coarse-grained models for proteins. Curr Opin Struct Biol 15: 144-150.    
  • 6. Cheon M, Chang I, Hall CK (2010) Extending the PRIME model for protein aggregation to all 20 amino acids. Proteins 78: 2950-2960.    
  • 7. Marrink SJ, Risselada HJ, Yefimov S, et al. (2007) The MARTINI force field: coarse grained model for biomolecular simulations. J Phys Chem B 111: 7812-7824.    
  • 8. Monticelli L, Kandasamy SK, Periole X, et al. (2008) The MARTINI coarse-grained force field: Extension to proteins. J Chem Theory Comput 4: 819-834.    
  • 9. Shih AY, Arkhipov A, Freddolino PL, et al. (2006) Coarse grained protein-lipid model with application to lipoprotein particles. J Phys Chem B 110: 3674-3684.    
  • 10. Takada S (2012) Coarse-grained molecular simulations of large biomolecules. Curr Opin Struct Biol 22: 130-137.    
  • 11. Stark AC, Andrews CT, Elcock AH (2013) Toward optimized potential functions for proteinprotein interactions in aqueous solutions: osmotic second virial coefficient calculations using the MARTINI coarse-grained force field. J Chem Theory Comput 9: 4176-4185.    
  • 12. Kopelevich DI (2013) One-dimensional potential of mean force underestimates activation barrier for transport across flexible lipid membranes. J Chem Phys 139: 134906.    
  • 13. May A, Pool R, van Dijk E, et al. (2013) Coarse-grained versus atomistic simulations: realistic interaction free energies for real proteins. Bioinformatics 30: 326-334.
  • 14. Periole X, Knepp AM, Sakmar TP, et al. (2012) Structural determinants of the supramolecular organization of G protein-coupled receptors in bilayers. J Am Chem Soc 134: 10959-10965.    
  • 15. Mondal S, Johnston JM, Wang H, et al. (2013) Membrane Driven Spatial Organization of GPCRs. Sci Rep 3: 2909.
  • 16. Lewis DR, Kholodovych V, Tomasini MD, et al. (2013) In silico design of anti-atherogenic biomaterials. Biomaterials 34: 7950-7959.    
  • 17. Li H, Gorfe AA (2013) Aggregation of lipid-anchored full-length H-Ras in lipid bilayers: simulations with the MARTINI force field. Plos One 8: e71018.    
  • 18. Bucher D, Hsu YH, Mouchlis VD, et al. (2013) Insertion of the Ca(2)(+)-independent phospholipase A(2) into a phospholipid bilayer via coarse-grained and atomistic molecular dynamics simulations. PLoS Comput Biol 9: e1003156.    
  • 19. Lee H (2013) Membrane penetration and curvature induced by single-walled carbon nanotubes: the effect of diameter, length, and concentration. Phys Chem Chem Phys 15:16334-16340.    
  • 20. Siuda I, Thogersen L (2013) Conformational flexibility of the leucine binding protein examined by protein domain coarse-grained molecular dynamics. J Mol Model 19: 4931-4945.    
  • 21. Liu FF, Huang B, Dong XY, et al. (2013) Molecular basis for the dissociation dynamics of protein a-immunoglobulin g1 complex. Plos One 8: e66935.    
  • 22. Lopez CA, Sovova Z, van Eerden FJ, et al. (2013) Martini Force Field Parameters for Glycolipids. J Chem Theory Comput 9: 1694-1708.    
  • 23. Khalid S, Bond PJ, Holyoake J, et al. (2008) DNA and lipid bilayers: self-assembly and insertion. J R Soc Interface 5 Suppl 3: S241-250.
  • 24. Cruz VL, Ramos J, Melo MN, et al. (2013) Bacteriocin AS-48 binding to model membranes and pore formation as revealed by coarse-grained simulations. Biochim Biophys Acta 1828:2524-2531.    
  • 25. Hess B, Kutzner C, van der Spoel D, et al. (2008) GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4: 435-447.    
  • 26. Dahlberg M (2007) Polymorphic phase behavior of cardiolipin derivatives studied by coarsegrained molecular dynamics. J Phys Chem B 111: 7194-7200.
  • 27. López CA, Rzepiela AJ, de Vries AH, et al. (2009) Martini Coarse-Grained Force Field: Extension to Carbohydrates. J Chem Theory Comput 5: 3195-3210.    
  • 28. Yesylevskyy SO, Schafer LV, Sengupta D, et al. (2010) Polarizable Water Model for the Coarse-Grained MARTINI Force Field. Plos Comput Biol 6: e1000810.    
  • 29. Yoo J, Cui Q (2009) Curvature generation and pressure profile modulation in membrane by lysolipids: insights from coarse-grained simulations. Biophys J 97: 2267-2276.    
  • 30. Donnini S, Tegeler F, Groenhof G, et al. (2011) Constant pH Molecular Dynamics in Explicit Solvent with lambda-Dynamics. J Chem Theory Comput 7: 1962-1978.    
  • 31. Bennett WFD, Chen AW, Donnini S, et al. (2013) Constant pH simulations with the coarsegrained MARTINI model - Application to oleic acid aggregates. Can J Chem 91: 839-846.    
  • 32. Schonichen A, Webb BA, Jacobson MP, et al. (2013) Considering protonation as a posttranslational modification regulating protein structure and function. Annu Rev Biophys42: 289-314.
  • 33. Brunger AT, Adams PD, Rice LM (1997) New applications of simulated annealing in X-ray crystallography and solution NMR. Structure 5: 325-336.    
  • 34. Kirkpatrick S, Gelatt CD, Jr., Vecchi MP (1983) Optimization by simulated annealing. Science 220: 671-680.    
  • 35. Nury H, Poitevin F, Van Renterghem C, et al. (2010) One-microsecond molecular dynamics simulation of channel gating in a nicotinic receptor homologue. Proc Natl Acad Sci U S A107: 6275-6280.
  • 36. Jensen MO, Jogini V, Borhani DW, et al. (2012) Mechanism of voltage gating in potassium channels. Science 336: 229-233.    
  • 37. Baoukina S, Marrink SJ, Tieleman DP (2012) Molecular Structure of Membrane Tethers. Biophys J 102: 1866-1871.    
  • 38. Louhivuori M, Risselada HJ, van der Giessen E, et al. (2010) Release of content through mechano-sensitive gates in pressurized liposomes. Proc Natl Acad Sci USA 107: 19856-19860.    
  • 39. Dill KA, MacCallum JL (2012) The Protein-Folding Problem, 50 Years On. Science 338:1042-1046.    
  • 40. Clementi C (2008) Coarse-grained models of protein folding: toy models or predictive tools? Curr Opin Struct Biol 18: 10-15.    
  • 41. Gregersen N, Bross P, Vang S, et al. (2006) Protein Misfolding and Human Disease. Annu Rev Genomics Hum Genet 7: 103-124.    
  • 42. Borgia MB, Borgia A, Best RB, et al. (2011) Single-molecule fluorescence reveals sequencespecific misfolding in multidomain proteins. Nature 474: 662-665.    
  • 43. Yang S, Cho SS, Levy Y, et al. (2004) Domain swapping is a consequence of minimal frustration. Proc Natl Acad Sci USA 101: 13786-13791.    
  • 44. Wu C, Shea J-E (2011) Coarse-grained models for protein aggregation. Curr Opin Struct Biol21: 209-220.
  • 45. Nguyen HD, Hall CK (2004) Molecular dynamics simulations of spontaneous fibril formation by random-coil peptides. Proc Natl Acad Sci USA 101: 16180-16185.    
  • 46. Voegler Smith A, Hall CK (2001) α-Helix formation: Discontinuous molecular dynamics on an intermediate-resolution protein model. Proteins 44: 344-360.    
  • 47. Arkhipov A, Roos WH, Wuite GJ, et al. (2009) Elucidating the mechanism behind irreversible deformation of viral capsids. Biophys J 97: 2061-2069.    
  • 48. Krishna V, Ayton GS, Voth GA (2010) Role of protein interactions in defining HIV-1 viral capsid shape and stability: a coarse-grained analysis. Biophys J 98: 18-26.    
  • 49. Grime JM, Voth GA (2012) Early stages of the HIV-1 capsid protein lattice formation. Biophys J 103: 1774-1783.    
  • 50. Zhang R, Linse P (2013) Icosahedral capsid formation by capsomers and short polyions. J Chem Phys 138: 154901.    
  • 51. Rapaport DC (2004) Self-assembly of polyhedral shells: A molecular dynamics study. Phys Rev E 70: 051905.    
  • 52. Khelashvili G, Harries D (2013) How sterol tilt regulates properties and organization of lipid membranes and membrane insertions. Chem Phys Lipids 169: 113-123.    
  • 53. Bennett WFD, MacCallum JL, Hinner MJ, et al. (2009) Molecular View of Cholesterol Flip- Flop and Chemical Potential in Different Membrane Environments. J Am Chem Soc 131:12714-12720.    
  • 54. Verma J, Khedkar VM, Coutinho EC (2010) 3D-QSAR in drug design--a review. Curr Top Med Chem 10: 95-115.    
  • 55. Roos WH, Gibbons MM, Arkhipov A, et al. (2010) Squeezing Protein Shells: How Continuum Elastic Models, Molecular Dynamics Simulations, and Experiments Coalesce at the Nanoscale. Biophys J 99: 1175-1181.    
  • 56. Chen X, Cui Q, Tang Y, et al. (2008) Gating Mechanisms of Mechanosensitive Channels of Large Conductance, I: A Continuum Mechanics-Based Hierarchical Framework. Biophys J95: 563-580.
  • 57. Riniker S, van Gunsteren WF (2012) Mixing coarse-grained and fine-grained water in molecular dynamics simulations of a single system. J Chem Phys 137: 044120.    

 

This article has been cited by

  • 1. Yihua Zhou, Walter Hu, Bei Peng, Yaling Liu, Biomarker Binding on an Antibody-Functionalized Biosensor Surface: The Influence of Surface Properties, Electric Field, and Coating Density, The Journal of Physical Chemistry C, 2014, 118, 26, 14586, 10.1021/jp501885p
  • 2. Ken Takahashi, Mechanosensor, Okayama Igakkai Zasshi (Journal of Okayama Medical Association), 2016, 128, 1, 61, 10.4044/joma.128.61
  • 3. Ehsan Dehnavi, Mehrnoosh Fathi-Roudsari, Sako Mirzaie, Seyed Shahriar Arab, Seyed Omid Ranaei Siadat, Khosro Khajeh, Engineering disulfide bonds in Selenomonas ruminantium β-xylosidase by experimental and computational methods, International Journal of Biological Macromolecules, 2017, 95, 248, 10.1016/j.ijbiomac.2016.10.104
  • 4. Pratiti Bhadra, Debnath Pal, Pipeline for inferring protein function from dynamics using coarse-grained molecular mechanics forcefield, Computers in Biology and Medicine, 2017, 10.1016/j.compbiomed.2017.02.009
  • 5. Gözde Ergin, Mária Lbadaoui-Darvas, Satoshi Takahama, Molecular structure inhibiting synergism in charged surfactant mixtures: An atomistic molecular dynamics simulation study, Langmuir, 2017, 10.1021/acs.langmuir.7b03346
  • 6. Mathieu Fossépré, Laurence Leherte, Aatto Laaksonen, Daniel P. Vercauteren, , Biomolecular Simulations in Structure-Based Drug Discovery, 2018, 105, 10.1002/9783527806836.ch6
  • 7. Mangesh Damre, Alessandro Marchetto, Alejandro Giorgetti, MERMAID: dedicated web server to prepare and run coarse-grained membrane protein dynamics, Nucleic Acids Research, 2019, 10.1093/nar/gkz416

Reader Comments

your name: *   your email: *  

Copyright Info: 2014, Ken Takahashi, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved