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Molecular modeling of methyl-α-Neu5Ac analogues docked against cholera toxin - a molecular dynamics study

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Abstract

Molecular modeling of synthetic methyl-α-Neu5Ac analogues modified in C-9 position was investigated by molecular docking and molecular dynamics (MD) simulation methods. Methyl-α-Neu5Ac analogues were docked against cholera toxin (CT) B subunit protein and MD simulations were carried out for three Methyl-α-Neu5Ac analogue-CT complexes (30, 10 and 10 ns) to estimate the binding activity of cholera toxin-Methyl-α-Neu5Ac analogues using OPLS_2005 force field. In this study, direct and water mediated hydrogen bonds play a vital role that exist between the methyl-α-9-N-benzoyl-amino-9-deoxy-Neu5Ac (BENZ)-cholera toxin active site residues. The Energy plot, RMSD and RMSF explain that the simulation was stable throughout the simulation run. Transition of phi, psi and omega angle for the complex was calculated. Molecular docking studies could be able to identify the binding mode of methyl-α-Neu5Ac analogues in the binding site of cholera toxin B subunit protein. MD simulation for Methyl-α-9-N-benzoyl-amino-9-deoxy-Neu5Ac (BENZ), Methyl-α-9-N-acetyl-9-deoxy-9-amino-Neu5Ac and Methyl-α-9-N-biphenyl-4-acetyl-deoxy-amino-Neu5Ac complex with CT B subunit protein was carried out, which explains the stable nature of interaction. These methyl-α-Neu5Ac analogues that have computationally acceptable pharmacological properties may be used as novel candidates for drug design for cholera disease.

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References

  1. Corfield, A. P., Schauer, R., in Schauer, R. (Ed.), Sialic acids: chemistry, metabolism and function. Cell Biology Monographs. 10 195–261. Springer Wien, Vienna (1982)

  2. Simanek, E.E., McGarvey, G.J., Jablonowski, J.A., Wong, C.-H.: Selectin-Carbohydrate Interactions: from natural ligands to designed mimics. Chem. Rev. 98, 833–862 (1998)

    Article  CAS  PubMed  Google Scholar 

  3. Kiefel, M.J., von Itzstein, M.: Recent advances in the synthesis of sialic acid derivatives and sialylmimetics as biological probes. Chem. Rev. 102, 471–490 (2002)

    Article  CAS  PubMed  Google Scholar 

  4. Royle, L., Matthews, E., Corfield, A., Berry, M., Rudd, P.M., Dwek, R.A., Carrington, S.D.: Glycan structures of ocular surface mucins in man, rabbit and dog display species differences. Glycoconj. J. 25, 763–773 (2008)

    Article  CAS  PubMed  Google Scholar 

  5. Varki, A.: Sialic acids in human health and disease. Trends Mol. Med. 14, 351–360 (2008)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  6. Woronowicz, A., Amith, S.R., De Vusser, K., Laroy, W., Contreras, R., Basta, S., Szewczuk, M.R.: Dependence of neurotrophic factor activation of Trk tyrosine kinase receptors on cellular sialidase. Glycobiology 17, 10–24 (2006)

    Article  PubMed  Google Scholar 

  7. Schauer, R.: in Sansom, C., Markman O. (Eds.), The diversity of sialic acids and their interplay with lectins. Glycobiology. Scion Bloxham, 136–149 (2007)

  8. Zaccai, N.R., Maenaka, K., Maenaka, T., Crocker, P.R., Brossmer, R., Kelm, S., Jones, E.Y.: Structure-guided design of sialic acid-based siglec inhibitors and crystallographic analysis in complex with sialoadhesin. Structure 11, 557–567 (2003)

  9. Lehmann, F., Tiralongo, E., Tiralongo, J.: Sialic acid-specific lectins: occurrence, specificity and function. Cell. Mol. Life Sci. 63, 1331–1354 (2006)

    Article  CAS  PubMed  Google Scholar 

  10. Heyningen, W.E.V.: Membrane receptors for bacterial toxins. Surface Membrane Receptors. 147–167 (1976)

  11. Sharmila, D.J.S., Veluraja, K.: Monosialogangliosides and Their Interaction with cholera toxin – investigation by molecular modeling and molecular mechanics. J. Biomol. Struct. Dyn. 21, 591–613 (2004)

    Article  CAS  PubMed  Google Scholar 

  12. Sharmila, D.J.S., Veluraja, K.: Disialogangliosides and their interaction with cholera toxin – investigation by molecular modeling, molecular mechanics and molecular dynamics. Journal of Biomolecular Structure & Dynamics. 22, 299–313 (2004)

    Article  CAS  Google Scholar 

  13. Sharmila, D.J.S., Veluraja, K.: Conformations of higher gangliosides and their binding with cholera toxin – investigation by molecular modeling, molecular mechanics, and molecular dynamics. J. Biomol. Struct. Dyn. 23, 641–656 (2006)

    Article  CAS  PubMed  Google Scholar 

  14. Branson, T.R., Turnbull, W.B.: Bacterial toxin inhibitors based on multivalent scaffolds. Chem. Soc. Rev. 42, 4613 (2013)

    Article  CAS  PubMed  Google Scholar 

  15. Branson, T.R., McAllister, T.E., Garcia-Hartjes, J., Fascione, M.A., Ross, J.F., Warriner, S.L., Wennekes, T., Zuilhof, H., Turnbull, W.B.: A protein-based pentavalent inhibitor of the cholera toxin B-subunit. Angew. Chem. Int. Ed. 53, 8323–8327 (2014)

  16. Merritt, E.A., Kuhn, P., Sarfaty, S., Erbe, J.L., Holmes, R.K., Hol, W.G.J.: The 1.25 Å resolution refinement of the cholera toxin B-pentamer: evidence of peptide backbone strain at the receptor-binding site. J. Mol. Biol. 282, 1043–1059 (1998)

    Article  CAS  PubMed  Google Scholar 

  17. Lengauer, T., Rarey, M.: Computational methods for biomolecular docking. Curr. Opin. Struct. Biol. 6, 402–406 (1996)

    Article  CAS  PubMed  Google Scholar 

  18. Friesner, R.A., Murphy, R.B., Repasky, M.P., Frye, L.L., Greenwood, J.R., Halgren, T.A., Sanschagrin, P.C., Mainz, D.T.: Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. J. Med. Chem. 49, 6177–6196 (2006)

    Article  CAS  PubMed  Google Scholar 

  19. Alder, B.J., Wainwright, T.E.: Studies in molecular dynamics. I. General Method. J. Chem. Phys. 31, 459 (1959)

    CAS  Google Scholar 

  20. Shan, Y., Kim, E.T., Eastwood, M.P., Dror, R.O., Seeliger, M.A., Shaw, D.E.: How does a drug molecule find its target binding site? J. Am. Chem. Soc. 133, 9181–9183 (2011)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Maestro 9.0, versuib 70110, Schrodinger, New York (2009)

  22. Kaminski, G.A., Friesner, R.A., Tirado-Rives, J., Jorgensen, W.L.: Evaluation and reparametrization of the OPLS-AA force field for protein via comparison with accurate quantum chemical calculations on peptides. J. Phys. Chem. B 105, 6474–6487 (2001)

    Article  CAS  Google Scholar 

  23. Brooks, W.H., Daniel, K.G., Sung, S.S., Guida, W.C.: Computational validation of the importance of absolute stereochemistry in virtual screening. J. Chem. Inf. Model. 48, 639–645 (2008)

    Article  CAS  PubMed  Google Scholar 

  24. Chen, I.J., Foloppe, N.: Drug-like bioactive structures and conformational coverage with the LigPrep/ ConfGen suite: comparison to programs MOE and catalyst. J. Chem. Inf. Model. 50, 822–839 (2010)

    Article  CAS  PubMed  Google Scholar 

  25. Friesner, R.A., Banks, J.L., Murphy, R.B., Halgren, T.A., Klicic, J.J., Mainz, D.T., Repasky, M.P., Knoll, E.H., Shelley, M., Perry, J.K., Shaw, D.E., Francis, P., Shenkin, P.S.: Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem. 47, 1739–1749 (2004)

    Article  CAS  PubMed  Google Scholar 

  26. Jorgensen, W.L., Duffy, E.M.: Prediction of drug solubility from structure. Adv. Drug Deliv. Rev. 54, 355–366 (2002)

    Article  CAS  PubMed  Google Scholar 

  27. QikProp3.2, Schrodinger LLC, New York, NY (2009)

  28. Lipinski, C., Hopkins, A.: Navigating chemical space for biology and medicine. Nature 432, 855–861 (2004)

    Article  CAS  PubMed  Google Scholar 

  29. Jorgensen, W.L., Chandrasekhar, J., Madura, J.D., Impey, R.W., Klein, M.L.: Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics. 79, 926 (1983)

    Article  CAS  Google Scholar 

  30. Strahan, G.D., Keniry, M.A., Shafer, R.H.: NMR structure refinement and dynamics of the K + −[d(G3T4G3)]2 quadruplex via particle mesh Ewald molecular dynamics simulations. Biophys. J. 75, 968–981 (1998)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  31. Essmann, U., Perera, L., Berkowitz, M.L., Darden, T., Lee, H., Pedersen, L.G.: A smooth particle mesh Ewald method. The Journal of Chemical Physics. 103, 8577 (1995)

    Article  CAS  Google Scholar 

  32. Andersen, H.C.: Rattle: a “velocity” version of the shake algorithm for molecular dynamics calculations. J. Comput. Phys. 52, 24–34 (1983)

    Article  CAS  Google Scholar 

  33. Barb, A.W., Wang, X., Prestegard, J.H.: Refolded recombinant Siglec5 for NMR investigation of complex carbohydrate binding. Protein Expression Purification. 88, 183–189 (2013)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  34. Lipinski, C.A.: Drug-like properties and the causes of poor solubility and poor permeability. Journal of Pharmacological Toxicological Methods. 44, 235–249 (2000)

    Article  CAS  PubMed  Google Scholar 

  35. Lipinski, C.A., Lombardo, F., Dominy, B.W., Feeney, P.J.: Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 23, 3–25 (1997)

    Article  CAS  Google Scholar 

  36. Lugsanangarma, K., Pianwanit, S., Kokpol, S., Tanaka, F.: Homology modelling and molecular dynamic simulations of wild type and mutated flavodoxins from Desulfovibrio vulgaris (Miyazaki F): insight into FMN- apoprotein interactions. Mol. Simul. 37, 1164–1178 (2011)

    Article  Google Scholar 

  37. Chubb, A.J., Fitzgerald, D.J., Nolan, K.B., Moman, E.: The productive conformation of prostaglandin G2 at the peroxidase site of prostaglandin endoperoxide H synthase: docking, molecular dynamics, and site-directed mutagenesis studies. Biochemistry 45, 811–820 (2006)

    Article  CAS  PubMed  Google Scholar 

  38. Hayes, J.M., Skamnaki, V.T., Archontis, G., Lamprakis, C., Sarrou, J., Bischler, N., Skaltsounis, A.-L., Zographos, S.E., Oikonomakos, N.G.: Kinetics, in silico docking, molecular dynamics, and MM-GBSA binding studies on prototype indirubins, KT5720, and staurosporine as phosphorylase kinase ATP-binding site inhibitors: The role of water molecules examined. Proteins: Structure, Function, and Bioinformatics 79, 703–719 (2011)

    Article  CAS  Google Scholar 

  39. Li, M.H., Luo, Q., Xue, X.G., Li, Z.S.: Molecular dynamics studies of the 3D structure and planar ligand binding of a quadruplex dimer. J. Mol. Model. 17, 515–526 (2010)

    Article  PubMed  Google Scholar 

  40. Saraboji, K., Hakansson, M., Genheden, S., Diehl, C., Qvist, J., Weininger, U., Nilsson, U.J., Leffler, H., Ryde, U., Akke, M., Logan, D.T.: The carbohydrate-binding site in galectin-3 is preorganized to recognize a sugarlike framework of oxygens: ultra-high-resolution structures and water dynamics. Biochemistry 51, 296–306 (2012)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  41. Kumar, S., Frank, M., Schwartz-Albiez, R.: Understanding the specificity of human galectin-8C domain interactions with its glycan ligands based on molecular dynamics simulations. PLoS One 8, e59761 (2013)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  42. Song, J., Tan, H., Wang, M., Webb, G.I., Akutus, T.: TANGLE: two-level support vector regression approach for protein backbone torsion angle prediction from primary sequences. PLoS One 7, e30361 (2012)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  43. Dormitzer, P.R., Sun, Z.Y.J., Blixt, O., Paulson, J.C., Wagner, G., Harrison, S.C.: Specificity and affinity of sialic acid binding by the rhesus rotavirus VP8* core. J. Virol. 76, 10512–10517 (2002)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  44. McCullough, C., Wang, M., Rong, L., Caffrey, M.: Characterization of influenza hemagglutinin interactions with receptor by NMR. PLoS One 7, e33958 (2012)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  45. Blessia, T.F., Rapheal, V.S., Sharmila, D.J.S.: Molecular dynamics of sialic acid analogues and their interaction with influenza hemagglutinin. Indian journal of pharmaceutical sciences. 72, 449–457 (2010)

  46. Pyrkov, T.V., Chugunov, A.O., Krylov, N.A., Nolde, D.E., Efremov, R.G.: PLATINUM: a web tool for analysis of hydrophobic/hydrophilic organization of biomolecular complexes. Bioinformatics 25, 1201–1202 (2009)

    Article  CAS  PubMed  Google Scholar 

  47. Nurisso, A., Blanchard, B., Audfray, A., Rydner, L., Oscarson, S., Varrot, A., Imberty, A.: Role of water molecules in structure and energetics of Pseudomonas aeruginosa lectin I interacting with disaccharides. J. Biol. Chem. 285, 20316–20327 (2010)

    Article  PubMed Central  CAS  PubMed  Google Scholar 

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Acknowledgments

The authors acknowledge the financial support given by SERB (Science and Engineering Research Board, DST) Ref No. (SR/FT/LS-157/2009), Govt. of India, New Delhi.

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Correspondence to D. Jeya Sundara Sharmila.

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Blessy, J.J., Sharmila, D.J.S. Molecular modeling of methyl-α-Neu5Ac analogues docked against cholera toxin - a molecular dynamics study. Glycoconj J 32, 49–67 (2015). https://doi.org/10.1007/s10719-014-9570-6

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