Advertisement

Protocols for Molecular Dynamics Simulations of RNA Nanostructures

  • Taejin Kim
  • Wojciech K. Kasprzak
  • Bruce A. ShapiroEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1632)

Abstract

Molecular dynamics (MD) simulations have been used as one of the main research tools to study a wide range of biological systems and bridge the gap between X-ray crystallography or NMR structures and biological mechanism. In the field of RNA nanostructures, MD simulations have been used to fix steric clashes in computationally designed RNA nanostructures, characterize the dynamics, and investigate the interaction between RNA and other biomolecules such as delivery agents and membranes.

In this chapter we present examples of computational protocols for molecular dynamics simulations in explicit and implicit solvent using the Amber Molecular Dynamics Package. We also show examples of post-simulation analysis steps and briefly mention selected tools beyond the Amber package. Limitations of the methods, tools, and protocols are also discussed. Most of the examples are illustrated for a small RNA duplex (helix), but the protocols are applicable to any nucleic acid structure, subject only to the computational speed and memory limitations of the hardware available to the user.

Key words

RNA Molecular dynamics simulations Force field Antechamber MM-PB(GB)SA Generalized born Elastic network model 

Notes

Acknowledgments

This project has been funded in part with federal funds from the Frederick National Laboratory for Cancer Research, National Institutes of Health, under contract HHSN261200800001E for W.K.K. and E.B. This research was supported in part by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does the mention of trade names, commercial products, or organizations imply endorsement by the US Government.

References

  1. 1.
    Severcan I, Geary C, Verzemnieks E, Chworos A, Jaeger L (2009) Square-shaped RNA particles from different RNA folds. Nano Lett 9(3):1270–1277CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Yingling YG, Shapiro BA (2007) Computational design of an RNA hexagonal nanoring and an RNA nanotube. Nano Lett 7(8):2328–2334CrossRefPubMedGoogle Scholar
  3. 3.
    Afonin KA, Bindewald E, Yaghoubian AJ, Voss N, Jacovetty E, Shapiro BA, Jaeger L (2010) In vitro assembly of cubic RNA-based scaffolds designed in silico. Nat Nanotechnol 5(9):676–682CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Grabow WW, Zakrevsky P, Afonin KA, Chworos A, Shapiro BA, Jaeger L (2011) Self-assembling RNA nanorings based on RNAI/II inverse kissing complexes. Nano Lett 11(2):878–887CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Afonin KA, Grabow WW, Walker FM, Bindewald E, Dobrovolskaia MA, Shapiro BA, Jaeger L (2011) Design and self-assembly of siRNA-functionalized RNA nanoparticles for use in automated nanomedicine. Nat Protoc 6(12):2022–2034CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Afonin KA, Viard M, Koyfman AY, Martins AN, Kasprzak WK, Panigaj M, Desai R, Santhanam A, Grabow WW, Jaeger L, Heldman E, Reiser J, Chiu W, Freed EO, Shapiro BA (2014) Multifunctional RNA nanoparticles. Nano Lett 14(10):5662–5671CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Martinez HM, Maizel JV Jr, Shapiro BA (2008) RNA2D3D: a program for generating, viewing, and comparing 3-dimensional models of RNA. J Biomol Struct Dyn 25(6):669–683CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Bindewald E, Grunewald C, Boyle B, O’Connor M, Shapiro BA (2008) Computational strategies for the automated design of RNA nanoscale structures from building blocks using NanoTiler. J Mol Graph Model 27(3):299–308CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Kasprzak W, Bindewald E, Kim TJ, Jaeger L, Shapiro BA (2011) Use of RNA structure flexibility data in nanostructure modeling. Methods 54(2):239–250CrossRefPubMedGoogle Scholar
  10. 10.
    Paliy M, Melnik R, Shapiro BA (2009) Molecular dynamics study of the RNA ring nanostructure: a phenomenon of self-stabilization. Phys Biol 6(4):046003CrossRefPubMedGoogle Scholar
  11. 11.
    Paliy M, Melnik R, Shapiro BA (2010) Coarse-graining RNA nanostructures for molecular dynamics simulations. Phys Biol 7(3):036001CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Kim T, Afonin KA, Viard M, Koyfman AY, Sparks S, Heldman E, Grinberg S, Linder C, Blumenthal RP, Shapiro BA (2013) In silico, in vitro, and in vivo studies indicate the potential use of bolaamphiphiles for therapeutic siRNAs delivery. Mol Ther Nucleic Acids 2:e80CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Gupta K, Afonin KA, Viard M, Herrero V, Kasprzak W, Kagiampakis I, Kim T, Koyfman AY, Puri A, Stepler M, Sappe A, KewalRamani VN, Grinberg S, Linder C, Heldman E, Blumenthal R, Shapiro BA (2015) Bolaamphiphiles as carriers for siRNA delivery: from chemical syntheses to practical applications. J Control Release 213:142–151CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Case DA et al (2014) AMBER 14, University of California, San FranciscoGoogle Scholar
  15. 15.
    Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26(16):1781–1802CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Berendsen HJC, van der Spoel D, Drunen R (1995) GROMACS: a message-passing parallel molecular dynamics implementation. Comp Phys Comm 91:43–56CrossRefGoogle Scholar
  17. 17.
    Pronk S, Páll S, Schulz R, Larsson P, Bjelkmar P, Apostolov R, Shirts MR, Smith JC, Kasson PM, van der Spoel D, Hess B, Lindhal E (2013) GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29(7):845–854CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M (1983) CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. J Comput Chem 4(2):187–217CrossRefGoogle Scholar
  19. 19.
    Brooks BR et al (2009) CHARMM: the biomolecular simulation program. J Comput Chem 30(10):1545–1614CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Zgrabova M, Otyepka M, Sponer J, Mladek A, Banas P, Cheatham TE 3rd, Jurecka P (2011) Refinement of the Cornell et al. nucleic acids force filed based on reference quantum chemical calculations of glycosidic torsion profiles. J Chem Theory Comput 7(9):2886–2902CrossRefGoogle Scholar
  21. 21.
    Darden T, York D, Pedersen LG (1993) Particle mesh Ewald: an N-log(N) method for Ewald sums in large systems. J Chem Phys 98(12):10089–10092CrossRefGoogle Scholar
  22. 22.
    Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG (1995) A smooth particle mesh EWALD method. J Chem Phys 103(19):8577–8593CrossRefGoogle Scholar
  23. 23.
    Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81(8):3684–3690CrossRefGoogle Scholar
  24. 24.
    Srinivasan J, Cheatham TE 3rd, Cieplak P, Kollman PA, Case DA (1998) Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate-DNA helices. J Am Chem Soc 120:9401–9409CrossRefGoogle Scholar
  25. 25.
    Afonin KA, Kasprzak WK, Bindewald E, Kireeva M, Viard M, Kashlev M, Shapiro BA (2014) In silico design and enzymatic synthesis of functional RNA nanoparticles. Acc Chem Res 47:1731–1741CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins 55(2):383–−394CrossRefPubMedGoogle Scholar
  27. 27.
    Hawkins GD, Cramer CJ, Truhlar DG (1995) Pairwise solute descreening of solute charges from a dielectric medium. Chem Phys Lett 246(1):122–−129CrossRefGoogle Scholar
  28. 28.
    Tsui V, Case DA (2000) Theory and applications of the generalized Born solvation model in macromolecular simulations. Biopolymers 56(4):275–291CrossRefPubMedGoogle Scholar
  29. 29.
    Gaillard T, Case DA (2011) Evaluation of DNA force fields in implicit solvation. J Chem Theory Comput 7(10):3181−3198CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Liu Y, Haddadian E, Sosnick TR, Freed KF, Gong H (2013) A novel implicit solvent model for simulating the molecular dynamics of RNA. Biophys J 105(5):1248–1257CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Nguyen H, Perez A, Bermeo S, Simmerling C (2015) Refinement of generalized born implicit solvation parameters for nucleic acids and their complexes with proteins. J Chem Theory Comput 11(8):3714–3728CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Levitt L (1983) Computer simulation of DNA double-helix dynamics. Cold Spring Harb Symp Quant Biol 47:251–275CrossRefPubMedGoogle Scholar
  33. 33.
    Zhao G et al (2013) Mature HIV-1 capsid structure by cryo-electron microscopy and all-atom molecular dynamics. Nature 497:643–646CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Pianaa S, Lindorff-Larsena K, Shawa DE (2013) Atomic-level description of ubiquitin folding. Proc Natl Acad Sci U S A 110:5915–5920CrossRefGoogle Scholar
  35. 35.
    Freudenthal BD, Beard WA, Perera L, Shock DD, Kim T, Schlick T, Wilson SH (2015) Uncovering the polymerase-induced cytotoxicity of an oxidized nucleotide. Nature 517:635–639CrossRefPubMedGoogle Scholar
  36. 36.
    Kim T, Freudenthal BD, Beard WA, Wilson SH, Schlick T (2016) Insertion of oxidized nucleotide triggers rapid DNA polymerase opening. Nucleic Acids Res 44:4409–4424CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Kim T, Shapiro B (2013) The role of sodium and magnesium ion concentration in HIV-1 subtype-A and subtype-B kissing loop dimerization structures. J Biomol Struct Dyn 31(5):495–510CrossRefPubMedGoogle Scholar
  38. 38.
    Bolhuis PG, Chandler D, Dellago C, Geissler PL (2002) Transition path sampling: throwing ropes over rough mountain passes, in the dark. Annu Rev Phys Chem 53:291–318CrossRefPubMedGoogle Scholar
  39. 39.
    Mitsutake A, Sugita Y, Okamoto Y (2001) Generalized-ensemble algorithms for molecular simulations of biopolymers. Biopolymers 60:96–123CrossRefPubMedGoogle Scholar
  40. 40.
    Miao Y, Feher VA, McCammon JA (2015) Gaussian accelerated molecular dynamics: unconstrained enhanced sampling and free energy calculation. J Chem Theory Comput 11(8):3584–3595CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Elber R, Karplus M (1990) Enhanced sampling in molecular dynamics. Use of the time dependent Hartree approximation for a simulation of carbon monoxide diffusion through myoglobin. J Am Chem Soc 112:9161–9175CrossRefGoogle Scholar
  42. 42.
    Afonin KA, Kasprzak W, Bindewald E, Puppala PS, Diehl AR, Hall KT, Kim TJ, Zimmermann MT, Jernigan RL, Jaeger L, Shapiro BA (2014) Computational and experimental characterization of RNA cubic nanoscaffolds. Methods 67(2):256–265CrossRefPubMedGoogle Scholar
  43. 43.
    Bahar I, Atilgan AR, Erman B (1997) Direct evaluation of thermal fluctuations in proteins using a single-parameter harmonic potential. Fold Des 2(3):173–181CrossRefPubMedGoogle Scholar
  44. 44.
    Bahar I, Erman B, Haliloglu T, Jernigan RL (1997) Efficient characterization of collective motions and inter residue correlations in proteins by low-resolution simulations. Biochemistry 36(44):13512–13523CrossRefPubMedGoogle Scholar
  45. 45.
    Bahar I, Rader AJ (2005) Coarse-grained normal mode analysis in structural biology. Curr Opin Struct Biol 15(5):586–592CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Sherwood P, Brooks BR, Sansom MS (2008) Multiscale methods for macromolecular simulations. Curr Opin Struct Biol 18(5):630–640CrossRefPubMedGoogle Scholar
  47. 47.
    Yang L, Song G, Carriquiry A, Jernigan RL (2008) Close correspondence between the motions from principal component analysis of multiple HIV-1 protease structures and elastic network modes. Structure 16(2):321–330CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    Atilgan AR, Durell SR, Jernigan RL et al (2001) Anisotropy of fluctuation dynamics of proteins with an elastic network model. Biophys J 80(1):505–515CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Sen TZ, Feng Y, Garcia JV, Kloczkowski A, Jernigan RL (2006) The extent of cooperativity of protein motions observed with elastic network models is similar for atomic and coarser-grained models. J Chem Theory Comput 2(3):696–704CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Wang Y, Jernigan RL (2005) Comparison of tRNA motions in the free and ribosomal bound structures. Biophys J 89(5):3399–3409CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Yan A, Wang Y, Kloczkowski A, Jernigan RL (2008) Effects of protein subunits removal on the computed motions of partial 30S structures of the ribosome. J Chem Theory Comput 4(10):1757–1767CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Yang L, Song G, Jernigan RL (2007) How well can we understand large-scale protein motions using normal modes of elastic network models? Biophys J 93(3):920–929CrossRefPubMedPubMedCentralGoogle Scholar
  53. 53.
    Zimmermann MT, Jernigan RL (2014) Elastic network models capture the motions apparent within ensembles of RNA structures. RNA 20(6):792–804CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Bakan A, Bahar I (2011) Computational generation of inhibitor-bound conformers of p38 MAP kinase and comparison with experiments. Pac Symp Biocomput 181–192.Google Scholar
  55. 55.
    Doruker P, Jernigan RL, Bahar I (2002) Dynamics of large proteins through hierarchical levels of coarse-grained structures. J Comput Chem 23(1):119–127CrossRefPubMedGoogle Scholar
  56. 56.
    Wang Y, Rader AJ, Bahar I, Jernigan RL (2004) Global ribosome motions revealed with elastic network model. J Struct Biol 147(3):302–314CrossRefPubMedGoogle Scholar
  57. 57.
    Zimmermann MT, Kloczkowski A, Jernigan RL (2011) MAVENs: motion analysis and visualization of elastic networks and structural ensembles. BMC Bioinformatics 12:264–270CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  • Taejin Kim
    • 1
  • Wojciech K. Kasprzak
    • 2
  • Bruce A. Shapiro
    • 3
    Email author
  1. 1.Department of ChemistryNew York UniversityNew YorkUSA
  2. 2.Basic Science Program, Leidos Biomedical Research, Inc.Frederick National Laboratory for Cancer ResearchFrederickUSA
  3. 3.RNA Structure and Design Section, RNA Biology LaboratoryNational Cancer Institute, National Institutes of HealthFrederickUSA

Personalised recommendations