Skip to main content
Log in

Methylation-targeted specificity of the DNA binding proteins R.DpnI and MeCP2 studied by molecular dynamics simulations

  • Original Paper
  • Published:
Journal of Molecular Modeling Aims and scope Submit manuscript

Abstract

DNA methylation plays a major role in organismal development and the regulation of gene expression. Methylation of cytosine bases and the cellular roles of methylated cytosine in eukaryotes are well established, as well as methylation of adenine bases in bacterial genomes. Still lacking, however, is a general mechanistic understanding, in structural and thermodynamic terms, of how proteins recognize methylated DNA. Toward this aim, we present the results of molecular dynamics simulations, alchemical free energy perturbation, and MM-PBSA calculations to explain the specificity of the R.DpnI enzyme from Streptococcus pneumonia in binding to adenine-methylated DNA with both its catalytic and winged-helix domains. We found that adenine-methylated DNA binds more favorably to the catalytic subunit of R.DpnI (−4 kcal mol−1) and to the winged-helix domain (−1.6 kcal mol−1) than non-methylated DNA. In particular, N6-adenine methylation is found to enthalpically stabilize binding to R.DpnI. In contrast, C5-cytosine methylation entropically favors complexation by the MBD domain of the human MeCP2 protein with almost no contribution of the binding enthalpy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1a,b
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6a–c
Fig. 7

Similar content being viewed by others

References

  1. Low DA, Weyand NJ, Mahan MJ (2001) Roles of DNA adenine methylation in regulating bacterial gene expression and virulence. Infect Immun 69(12):7197–7204

    Article  CAS  Google Scholar 

  2. Wu TP, Wang T, Seetin MG, Lai YQ, Zhu SJ, Lin KX, Liu YF, Byrum SD, Mackintosh SG, Zhong M, Tackett A, Wang GL, Hon LS, Fang G, Swenberg JA, Xiao AZ (2016) DNA methylation on N-6-adenine in mammalian embryonic stem cells. Nature 532(7599):329–333

    Article  CAS  Google Scholar 

  3. Siwek W, Czapinska H, Bochtler M, Bujnicki JM, Skowronek K (2012) Crystal structure and mechanism of action of the N6-methyladenine-dependent type IIM restriction endonuclease R.DpnI. Nucleic Acids Res 40(15):7563–7572

    Article  CAS  Google Scholar 

  4. Delacampa AG, Springhorn SS, Kale P, Lacks SA (1988) Proteins encoded by DpnI restriction gene cassette- hyperproduction and characterization of the DpnI endonuclease. J Biol Chem 263(29):14696–14702

    CAS  Google Scholar 

  5. Mierzejewska K, Siwek W, Czapinska H, Skowronek K, Bujnicki J, Bochtler M (2014) Structural basis of the methylation specificity of R.DpnI. Nucleic Acids Res 42:8745–8754

    Article  CAS  Google Scholar 

  6. Chahrour M, Jung SY, Shaw C, Zhou XB, Wong STC, Qin J, Zoghbi HY (2008) MeCP2, a key contributor to neurological disease, activates and represses transcription. Science 320(5880):1224–1229

    Article  CAS  Google Scholar 

  7. Chen WG, Chang Q, Lin YX, Meissner A, West AE, Griffith EC, Jaenisch R, Greenberg ME (2003) Derepression of BDNF transcription involves calcium-dependent phosphorylation of MeCP2. Science 302(5646):885–889

    Article  CAS  Google Scholar 

  8. Bekinschtein P, Cammarota M, Katche C, Slipczuk L, Rossato JI, Goldin A, Lzquierdo I, Medina JH (2008) BDNF is essential to promote persistence of long-term memory storage. Proc Natl Acad Sci USA 105(7):2711–2716

    Article  CAS  Google Scholar 

  9. Ho KL, McNae LW, Schmiedeberg L, Klose RJ, Bird AP, Walkinshaw MD (2008) MeCP2 binding to DNA depends upon hydration at methyl-CpG. Mol Cell 29(4):525–531

    Article  CAS  Google Scholar 

  10. Pabo CO, Sauer RT (1984) Protein-DNA recognition. Annu Rev Biochem 53:293–321

    Article  CAS  Google Scholar 

  11. Wecker K, Bonnet MC, Meurs EF, Delepierre M (2002) The role of the phosphorus BI-BII transition in protein-DNA recognition: the NF-kappa B complex. Nucleic Acids Res 30(20):4452–4459

    Article  CAS  Google Scholar 

  12. Ray BK, Dhar S, Henry C, Rich A, Ray A (2013) Epigenetic regulation by Z-DNA silencer function controls cancer-associated ADAM-12 expression in breast cancer: cross-talk between MeCP2 and NF1 transcription factor family. Cancer Res 73(2):736–744

    Article  CAS  Google Scholar 

  13. Madhumalar A, Bansal M (2005) Sequence preference for BI/II conformations in DNA: MD and crystal structure data analysis. J Biomol Struct Dyn 23(1):13–27

    Article  CAS  Google Scholar 

  14. Buck-Koehntop BA, Stanfield RL, Ekiert DC, Martinez-Yamout MA, Dyson HJ, Wilson IA, Wright PE (2012) Molecular basis for recognition of methylated and specific DNA sequences by the zinc finger protein Kaiso. Proc Natl Acad Sci USA 109(38):15229–15234

    Article  CAS  Google Scholar 

  15. Zou X, Ma W, Solov’yov IA, Chipot C, Schulten K (2012) Recognition of methylated DNA through methyl-CpG binding domain proteins. Nucleic Acids Res 40(6):2747–2758

    Article  CAS  Google Scholar 

  16. Schenkelberger M, Shanak S, Finkler M, Worst E, Noireaux V, Helms V, Ott A (2017) Expression regulation by a methyl-CpG binding domain in an E. coli based, cell-free TX-TL system. Phys Biol. doi:10.1088/1478-3975/aa5d37

    Google Scholar 

  17. Hess B, Kutzner C, van der Spoel D, Lindahl E (2008) GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4(3):435–447

    Article  CAS  Google Scholar 

  18. Foloppe N, MacKerell AD (2000) All-atom empirical force field for nucleic acids: I. Parameter optimization based on small molecule and condensed phase macromolecular target data. J Comput Chem 21(2):86–104

    Article  CAS  Google Scholar 

  19. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79(2):926–935

    Article  CAS  Google Scholar 

  20. Shanak S., Helms V. (2014) Hydration properties of natural and synthetic DNA sequences with methylated adenine or cytosine bases in the R.DpnI target and BDNF promoter studied by molecular dynamics simulations. J Chem Phys. p. 22D512

  21. Darden T, York D, Pedersen L (1993) Particle Mesh Ewald- an n.log(n) method for Ewald sums in large systems. J Chem Phys 98(12):10089–10092

    Article  CAS  Google Scholar 

  22. Van Gunsteren WF, Berendsen HJC (1988) A leap-frog algorithm for stochastic dynamics. Mol Simul 1(3):173–185

    Article  Google Scholar 

  23. Bennett CH (1976) Efficient estimation of free-energy differences from Monte-Carlo data. J Comput Phys 22(2):245–268

    Article  Google Scholar 

  24. Pohorille A, Jarzynski C, Chipot C (2010) Good practices in free-energy calculations. J Phys Chem B 114(32):10235–10253

    Article  CAS  Google Scholar 

  25. Mobley DL, Chodera JD, Dill KA (2006) On the use of orientational restraints and symmetry corrections in alchemical free energy calculations. J Chem Phys 125(8):084902

    Article  Google Scholar 

  26. Hornak V, Simmerling C (2004) Development of softcore potential functions for overcoming steric barriers in molecular dynamics simulations. J Mol Graph Model 22(5):405–413

    Article  CAS  Google Scholar 

  27. Beutler TC, Mark AE, Vanschaik RC, Gerber PR, Vangunsteren WF (1994) Avoiding singularities and numerical instabilities in free-energy calculations based on molecular simulations. Chem Phys Lett 222(6):529–539

    Article  CAS  Google Scholar 

  28. Srinivasan J, Cheatham TE, Cieplak P, Kollman PA, Case DA (1998) Case, Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate–DNA helices. J Am Chem Soc 120(37):9401–9409

    Article  CAS  Google Scholar 

  29. Baker NA, Sept D, Holst MJ, McCammon JA (2001) The adaptive multilevel finite element solution of the Poisson-Boltzmann equation on massively parallel computers. IBM J Res Dev 45(3–4):427–438

    Article  CAS  Google Scholar 

  30. Miller BR III, McGee TD Jr, Swails JM, Homeyer N, Gohlke H, Roitberg AE (2012) MMPBSA.py: an efficient program for end-state free energy calculations. J Chem Theory Comput 8(9):3314–3321

    Article  CAS  Google Scholar 

  31. Crowley MF, Williamson MJ, Walker RC (2009) CHAMBER: comprehensive support for CHARMM force fields within the AMBER software. Int J Quantum Chem 109(15):3767–3772

    Article  CAS  Google Scholar 

  32. Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph Model 14(1):33–38

    Article  CAS  Google Scholar 

  33. Roe DR, Cheatham TE III (2013) PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J Chem Theory Comput 9(7):3084–3095

    Article  CAS  Google Scholar 

  34. Furini S, Barbini P, Domene C (2013) DNA-recognition process described by MD simulations of the lactose repressor protein on a specific and a non-specific DNA sequence. Nucleic Acids Res 41(7):3963–3972

    Article  CAS  Google Scholar 

  35. Schlitter J (1993) Estimation of absolute and relative entropies of macromolecules using the covariance matrix. Chem Phys Lett 215(6):617–621

    Article  CAS  Google Scholar 

  36. Hartmann B, Piazzola D, Lavery R (1993) BI-BII transitions in B-DNA. Nucleic Acids Res 21(3):561–568

    Article  CAS  Google Scholar 

  37. Pauling L (1992) The nature of chemical bond. J Chem Educ 69(7):519–521

    Article  CAS  Google Scholar 

  38. Lu XJ, Olson WK (2003) 3DNA: a software package for the analysis, rebuilding and visualization of three-dimensional nucleic acid structures. Nucleic Acids Res 31(17):5108–5121

    Article  CAS  Google Scholar 

  39. Liu Y, Toh H, Sasaki H, Zhang X, Cheng X (2012) An atomic model of Zfp57 recognition of CpG methylation within a specific DNA sequence. Genes Dev 26(21):2374–2379

    Article  CAS  Google Scholar 

  40. Rohs R, Jin X, West SM, Joshi R, Honig B, Mann RS (2010) Origins of specificity in protein-DNA recognition. Annu Rev Biochem 79(79):233–269

    Article  CAS  Google Scholar 

  41. Jen-Jacobson L, Engler LE, Jacobson LA (2000) Structural and thermodynamic strategies for site-specific DNA binding proteins. Structure 8(10):1015–1023

    Article  CAS  Google Scholar 

  42. Smith E, Jones ME, Drew PA (2009) Quantitation of DNA methylation by melt curve analysis. Bmc Cancer 9:123

    Article  Google Scholar 

  43. Lu X-J, Olson WK (2008) 3DNA: a versatile, integrated software system for the analysis, rebuilding and visualization of three-dimensional nucleic-acid structures. Nat Protoc 3(7):1213–1227

    Article  CAS  Google Scholar 

Download references

Acknowledgments

We thank Prof. Matthias Bochtler (Warsaw/Poland) for valuable discussions on mechanistic issues of the R.DpnI system and for early access to the crystallographic data. In addition, we thank Dr. Wei Gu for fruitful discussions and helpful suggestions concerning the free energy perturbation calculations.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Volkhard Helms.

Ethics declarations

Funding sources

This work is embedded in the framework of the collaborative research center SFB 1027 funded by Deutsche Forschungsgemeinschaft (DFG). S.S. thanks the German Academic Exchange Service (DAAD) for a doctoral fellowship. O.U. was supported by DFG.

Electronic supplementary material

Supporting Information

Supplementary data available: two supplementary tables, seven supplementary figures. This material is available free of charge via the Internet at http://pubs.acs.org

ESM 1

(DOCX 319 kb)

ESM 2

(DOCX 267 kb)

ESM 3

(DOCX 77.3 kb)

ESM 4

(DOCX 309 kb)

ESM 5

(DOCX 196 kb)

ESM 6

(DOCX 259 kb)

ESM 7

(DOCX 113 kb)

ESM 8

(DOCX 34 kb)

ESM 9

(DOCX 34 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shanak, S., Ulucan, O. & Helms, V. Methylation-targeted specificity of the DNA binding proteins R.DpnI and MeCP2 studied by molecular dynamics simulations. J Mol Model 23, 152 (2017). https://doi.org/10.1007/s00894-017-3318-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00894-017-3318-8

Keywords

Navigation