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Molecular dynamics simulation of the sliding of distamycin anticancer drug along DNA: interactions and sequence selectivity

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Abstract

Molecular dynamics simulations and umbrella sampling have been used to investigate the sliding of distamycin anticancer drug along the DNA minor groove. The potential energy surface calculated for the sliding of drug shows three minima. The global minimum corresponds to the binding of drug to the AT-rich region, which is the origin of sequence selectivity of distamycin. This selectivity originates from both structural factors and energy contributions. The analysis of energy contributions of binding was performed by the MM–PBSA method. The analysis of hydrogen bonds and van der Waals, electrostatic, and solvation interactions show that structural or steric factors are more important in the selectivity of distamycin than energetic factors. The results of this study can be applied in the design of new derivatives of distamycin anticancer drug with improved properties.

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References

  1. R. Palchaudhuri, P.J. Hergenrother, DNA as a target for anticancer compounds: methods to determine the mode of binding and the mechanism of action. Curr. Opin. Biotechnol. 18(6), 497–503 (2007)

    Article  CAS  Google Scholar 

  2. L.H. Nahid Shahabadi, Binding studies of the antidiabetic drug, metformin to calf thymus DNA using multispectroscopic methods. Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 97, 406–410 (2012)

    Article  Google Scholar 

  3. J.J. Gills, J. LoPiccolo, P.A. Dennis, Nelfinavir, a new anti-cancer drug with pleiotropic effects and many paths to autophagy. Autophagy 4(1), 107–109 (2008)

    Article  CAS  Google Scholar 

  4. B.P. Reddy, S.M. Sondhi, J.W. Lown, Synthetic DNA minor groove-binding drugs. Pharmacol. Ther. 84(1), 1–111 (1999)

    Article  CAS  Google Scholar 

  5. R. Palchaudhuri, P.J. Hergenrother, DNA as a target for anticancer compounds: methods to determine the mode of binding and the mechanism of action. Curr. Opin. Biotechnol. 18, 497–503 (2007)

    Article  CAS  Google Scholar 

  6. L. Ls, Structural considerations in the interaction of DNA and acridines. J. Mol. Biol. 3, 18–30 (1961)

    Article  Google Scholar 

  7. M. Brana et al., Intercalators as anticancer drugs. Curr. Pharm. Des. 7(17), 1745–1780 (2001)

    Article  CAS  Google Scholar 

  8. L. Lerman, Structural considerations in the interaction of DNA and acridines. J. Mol. Biol. 3(1), 18IN13–30IN14 (1961)

    Article  Google Scholar 

  9. B.S.P. Reddy, S.M. Sodhi, J.W. Lown, Synthetic DNA minor groove-binding drugs. Pharmacol. Ther. 84, 1–111 (1999)

    Article  CAS  Google Scholar 

  10. C. Bailly, J.P. Henichart, DNA recognition by intercalator-minor-groove binder hybrid molecules. Bioconjug. Chem. 2, 379–393 (1991)

    Article  CAS  Google Scholar 

  11. J. Bc, Energetics of drug–DNA interactions. Biopolymers 44, 201–215 (1997)

    Article  Google Scholar 

  12. C. Zimmer, U. Wähnert, Nonintercalating DNA-binding ligands: specificity of the interaction and their use as tools in biophysical, biochemical and biological investigations of the genetic material. Prog. Biophys. Mol. Biol. 47, 31–112 (1986)

    Article  CAS  Google Scholar 

  13. P.G. Baraldi, M.A. Tabrizi, D. Preti, F. Fruttarolo, B. Avitabile, A. Bovero, G. Pavani, M. Carmen Nunez del Carretero, R. Romagnoli, DNA minor-groove binders. Design, synthesis, and biological evaluation of ligands structurally related to CC-1065, distamycin, and anthramycin. Pure Appl. Chem. 75, 187–194 (2003)

    Article  CAS  Google Scholar 

  14. P. Cozzi, A new class of cytotoxic DNA minor groove binders: α-halogenoacrylic derivatives of pyrrolecarbamoyl oligomers. 56, 57–65 (2001)

    CAS  Google Scholar 

  15. T.J. Dwyer, B.H. Geierstanger, Y. Bathini, J.W. Lown, D.E. Wemmer, Design and binding of a distamycin A analog to d(CGCAAGTTGGC)–d(GCCAACTTGCG): synthesis, NMR studies, and implications for the design of sequence-specific minor groove binding oligopeptides. J. Am. Chem. Soc. 114, 5911–5919 (1992)

    Article  CAS  Google Scholar 

  16. M. D’Incalci, C. Sessa, Review oncologic, endocrine & metabolic DNA minor groove binding ligands: a new class of anticancer agents. Exp. Opin. Invest. Drugs 6, 875–884 (1997)

    Article  Google Scholar 

  17. H.C. Nelson et al., The structure of an oligo (dA)· oligo (dT) tract and its biological implications. Nature 330(6145), 221–226 (1987)

    Article  CAS  Google Scholar 

  18. B. Pullman, Electrostatics of polymorphic DNA. J. Biomol. Struct. Dyn. 1(3), 773–794 (1983)

    Article  CAS  Google Scholar 

  19. M.L. Kopka et al., The molecular origin of DNA–drug specificity in netropsin and distamycin. Proc. Natl. Acad. Sci. 82(5), 1376–1380 (1985)

    Article  CAS  Google Scholar 

  20. M. Broggini, M. D’Incalci, Modulation of transcription factor DNA interaction by anticancer drugs. Anticancer Drug Des. 9, 373–387 (1994)

    CAS  Google Scholar 

  21. M. Broggini et al., Selective DNA interaction of the novel distamycin derivative FCE 24517. Cancer Res. 51(1), 199–204 (1991)

    CAS  Google Scholar 

  22. K. Uytterhoeven, J. Sponer, L. Van Meervelt, Two 1:1 binding modes for distamycin in the minor groove of d(GGCCAATTGG). Eur. J. Biochem. 269, 2868–2877 (2002)

    Article  CAS  Google Scholar 

  23. T.A. Steitz, Structural studies of protein–nucleic acid interaction: the sources of sequence-specific binding. Q. Rev. Biophys. 23(3), 205–280 (1990)

    Article  CAS  Google Scholar 

  24. M. Coll et al., A bifurcated hydrogen-bonded conformation in the d (AT) base pairs of the DNA dodecamer d (CGCAAATTTGCG) and its complex with distamycin. Proc. Natl. Acad. Sci. 84(23), 8385–8389 (1987)

    Article  CAS  Google Scholar 

  25. D.A. Pearlman et al., AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput. Phys. Commun. 91(1), 1–41 (1995)

    Article  CAS  Google Scholar 

  26. K. Boehncke et al., Molecular dynamics investigation of the interaction between DNA and distamycin. Biochemistry 30(22), 5465–5475 (1991)

    Article  CAS  Google Scholar 

  27. S.B. Singh, D.E. Wemmer, P.A. Kollman, Relative binding affinities of distamycin and its analog to d(CGCAAGTTGGC). d(GCCAACTTGCG): comparison of simulation results with experiment. Proc. Natl. Acad. Sci. 91(16), 7673–7677 (1994)

    Article  CAS  Google Scholar 

  28. M.V. Koonammackal, U.V.N. Nellipparambil, C. Sudarsanakumar, Molecular dynamics simulations and binding free energy analysis of DNA minor groove complexes of curcumin. J. Mol. Model. 17(11), 2805–2816 (2011)

    Article  CAS  Google Scholar 

  29. J. Dolenc et al., Molecular dynamics simulations and free energy calculations of netropsin and distamycin binding to an AAAAA DNA binding site. Nucleic Acids Res. 33(2), 725–733 (2005)

    Article  CAS  Google Scholar 

  30. K. Wittayanarakul et al., Ranking ligand affinity for the DNA minor groove by experiment and simulation. ACS Med. Chem. Lett. 1(8), 376–380 (2010)

    Article  CAS  Google Scholar 

  31. B.M. Pettitt, M. Karplus, The potential of mean force surface for the alanine dipeptide in aqueous solution: a theoretical approach. Chem. Phys. Lett. 121(3), 194–201 (1985)

    Article  CAS  Google Scholar 

  32. J.G. Kirkwood, Statistical mechanics of fluid mixtures. J. Chem. Phys. 3(5), 300–313 (1935)

    Article  CAS  Google Scholar 

  33. G.M. Torrie, J.P. Valleau, Monte Carlo free energy estimates using non-Boltzmann sampling: application to the sub-critical Lennard–Jones fluid. Chem. Phys. Lett. 28(4), 578–581 (1974)

    Article  CAS  Google Scholar 

  34. B. Roux, The calculation of the potential of mean force using computer simulations. Comput. Phys. Commun. 91(1), 275–282 (1995)

    Article  CAS  Google Scholar 

  35. A.V. Vargiu et al., Sliding of alkylating anticancer drugs along the minor groove of DNA: new insights on sequence selectivity. Biophys. J. 94(2), 550–561 (2008)

    Article  CAS  Google Scholar 

  36. M. Zacharias, Minor groove deformability of DNA: a molecular dynamics free energy simulation study. Biophys. J. 91(3), 882–891 (2006)

    Article  CAS  Google Scholar 

  37. W.L. Jorgensen et al., Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79(2), 926–935 (1983)

    Article  CAS  Google Scholar 

  38. J. Aaqvist, Ion–water interaction potentials derived from free energy perturbation simulations. J. Phys. Chem. 94(21), 8021–8024 (1990)

    Article  CAS  Google Scholar 

  39. T.I. Cheatham et al., Molecular dynamics simulations on solvated biomolecular systems: the particle mesh Ewald method leads to stable trajectories of DNA, RNA, and proteins. J. Am. Chem. Soc. 117(14), 4193–4194 (1995)

    Article  CAS  Google Scholar 

  40. J.-P. Ryckaert, G. Ciccotti, H.J. Berendsen, Numerical integration of the Cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J. Comput. Phys. 23(3), 327–341 (1977)

    Article  CAS  Google Scholar 

  41. H.C. Andersen, Molecular dynamics simulations at constant pressure and/or temperature. J. Chem. Phys. 72(4), 2384–2393 (1980)

    Article  CAS  Google Scholar 

  42. D. Case, et al., in AMBER 10; University of California, San Francisco, 2008, 2005

  43. J. Wang et al., Automatic atom type and bond type perception in molecular mechanical calculations. J. Mol. Graph. Model. 25(2), 247–260 (2006)

    Article  Google Scholar 

  44. J. Wang et al., Development and testing of a general amber force field. J. Comput. Chem. 25(9), 1157–1174 (2004)

    Article  CAS  Google Scholar 

  45. J. Wang, P. Cieplak, P.A. Kollman, How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? J. Comput. Chem. 21(12), 1049–1074 (2000)

    Article  CAS  Google Scholar 

  46. W. Cornell, et al., in A 2nd-Generation Force-Field for the Simulation of Proteins, Nucleic-Acids, and Small Molecules. Abstracts of Papers of the American Chemical Society (American Chemical Society, Washington, DC, 1992)

  47. T.E. Cheatham III, P. Cieplak, P.A. Kollman, A modified version of the Cornell et al. force field with improved sugar pucker phases and helical repeat. J. Biomol. Struct. Dyn. 16(4), 845–862 (1999)

    Article  CAS  Google Scholar 

  48. J.M. Rosenbergl, The weighted histogram analysis method for free-energy calculations on biomolecules. I. The method. J. Comput. Chem. 13(8), 1011–1021 (1992)

    Article  Google Scholar 

  49. A. Grossfield, in WHAM (Rochester, 2003)

  50. J. Srinivasan et al., Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate–DNA helices. J. Am. Chem. Soc. 120(37), 9401–9409 (1998)

    Article  CAS  Google Scholar 

  51. P.A. Kollman et al., Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc. Chem. Res. 33(12), 889–897 (2000)

    Article  CAS  Google Scholar 

  52. B.R. Miller III et al., MMPBSA. py: an efficient program for end-state free energy calculations. J. Chem. Theory Comput. 8(9), 3314–3321 (2012)

    Article  CAS  Google Scholar 

  53. J. Weiser, P.S. Shenkin, W.C. Still, Approximate atomic surfaces from linear combinations of pairwise overlaps (LCPO). J. Comput. Chem. 20(2), 217–230 (1999)

    Article  CAS  Google Scholar 

  54. C. Tan, Y.-H. Tan, R. Luo, Implicit nonpolar solvent models. J. Phys. Chem. B 111(42), 12263–12274 (2007)

    Article  CAS  Google Scholar 

  55. D. Sitkoff, K.A. Sharp, B. Honig, Accurate calculation of hydration free energies using macroscopic solvent models. J. Phys. Chem. 98(7), 1978–1988 (1994)

    Article  CAS  Google Scholar 

  56. B. Honig, A. Nicholls, Classical electrostatics in biology and chemistry. Science 268(5214), 1144–1149 (1995)

    Article  CAS  Google Scholar 

  57. M.K. Gilson, K.A. Sharp, B.H. Honig, Calculating the electrostatic potential of molecules in solution: method and error assessment. J. Comput. Chem. 9(4), 327–335 (1988)

    Article  CAS  Google Scholar 

  58. H. Gohlke, C. Kiel, D.A. Case, Insights into protein–protein binding by binding free energy calculation and free energy decomposition for the Ras–Raf and Ras–RalGDS complexes. J. Mol. Biol. 330(4), 891–913 (2003)

    Article  CAS  Google Scholar 

  59. H. Gohlke, D.A. Case, Converging free energy estimates: MM–PB (GB) SA studies on the protein–protein complex Ras–Raf. J. Comput. Chem. 25(2), 238–250 (2004)

    Article  CAS  Google Scholar 

  60. S.B. Rempe, H. Jónsson, A computational exercise illustrating molecular vibrations and normal modes. Chem. Educ. 3(4), 1–17 (1998)

    Article  Google Scholar 

  61. S. Hayward, A. Kitao, N. Gō, Harmonicity and anharmonicity in protein dynamics: a normal mode analysis and principal component analysis. Proteins Struct. Funct. Bioinform. 23(2), 177–186 (1995)

    Article  CAS  Google Scholar 

  62. R. Lavery et al., Conformational analysis of nucleic acids revisited: Curves+. Nucleic Acids Res. 37(17), 5917–5929 (2009)

    Article  CAS  Google Scholar 

  63. T.J. Dwyer et al., Design and binding of a distamycin A analog to d (CGCAAGTTGGC). cntdot. d (GCCAACTTGCG): synthesis, NMR studies, and implications for the design of sequence-specific minor groove binding oligopeptides. J. Am. Chem. Soc. 114(15), 5911–5919 (1992)

    Article  CAS  Google Scholar 

  64. J. Dolenc et al., Configurational entropy change of netropsin and distamycin upon DNA minor-groove binding. Biophys. J. 91(4), 1460–1470 (2006)

    Article  CAS  Google Scholar 

  65. T.A. Soares et al., An improved nucleic acid parameter set for the GROMOS force field. J. Comput. Chem. 26(7), 725–737 (2005)

    Article  CAS  Google Scholar 

  66. T.E. Cheatham, M.A. Young, Molecular dynamics simulation of nucleic acids: successes, limitations, and promise. Biopolymers 56(4), 232–256 (2000)

    Article  CAS  Google Scholar 

  67. D.R. Roe, T.E. Cheatham III, PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J. Chem. Theory Comput. 9(7), 3084–3095 (2013)

    Article  CAS  Google Scholar 

  68. S. Pronk et al., GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29(7), 845–854 (2013)

    Article  CAS  Google Scholar 

  69. D. Van Der Spoel et al., GROMACS: fast, flexible, and free. J. Comput. Chem. 26(16), 1701–1718 (2005)

    Article  Google Scholar 

  70. R. Luo, L. David, M.K. Gilson, Accelerated Poisson–Boltzmann calculations for static and dynamic systems. J. Comput. Chem. 23(13), 1244–1253 (2002)

    Article  CAS  Google Scholar 

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Correspondence to Seifollah Jalili.

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Jalili, S., Maddah, M. Molecular dynamics simulation of the sliding of distamycin anticancer drug along DNA: interactions and sequence selectivity. J IRAN CHEM SOC 14, 531–540 (2017). https://doi.org/10.1007/s13738-016-1001-0

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