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Molecular dynamics simulation and linear interaction energy study of d-Glu-based inhibitors of the MurD ligase

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Abstract

The biosynthetic pathway of the bacterial peptidoglycan, where MurD is an enzyme involved at the intracellular stage of its construction, represents a collection of highly selective macromolecular targets for novel antibacterial drug design. In this study as part of our investigation of the MurD bacterial target two recently discovered classes of the MurD ligase inhibitors were investigated resulting from the lead optimization phases of the N-sulfonamide d-Glu MurD inhibitors. Molecular dynamics simulations, based on novel structural data, in conjunction with the linear interaction energy (LIE) method suggested the transferability of our previously obtained LIE coefficients to further d-Glu based classes of MurD inhibitors. Analysis of the observed dynamical behavior of these compounds in the MurD active site was supported by static drug design techniques. These results complement the current knowledge of the MurD inhibitory mechanism and provide valuable support for the d-Glu paradigm of the inhibitor design.

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References

  1. Rice LB (2006) Unmet medical needs in antibacterial therapy. Biochem Pharmacol 71:991–995

    Article  CAS  Google Scholar 

  2. Brown ED, Wright GD (2005) New targets and screening approaches in antimicrobial drug discovery. Chem Rev 105:759–774

    Article  CAS  Google Scholar 

  3. Vollmer W, Blanot D, de Pedro MA (2008) Peptidoglycan structure and architecture. FEMS Microbiol Rev 32:149–167

    Article  CAS  Google Scholar 

  4. Smith CS (2006) Structure, function and dynamics in the mur family of bacterial cell wall ligases. J Mol Biol 362:640–655

    Article  CAS  Google Scholar 

  5. Bertrand JA, Auger G, Martin L, Fanchon E, Blanot D, Le Beller D, van Heijenoort J, Dideberg O (1999) Determination of the MurD mechanism through crystallographic analysis of enzyme complexes. J Mol Biol 289:579–590

    Article  CAS  Google Scholar 

  6. Anderson MS, Eveland SS, Onishi H, Pompliano DL (1996) Kinetic mechanism of the Escherichia coli UDPMurNAc-tripeptide d-alanyl-d-alanine-adding enzyme: use of a glutathione S-transferase fusion. Biochemistry 35:16264–16269

    Article  CAS  Google Scholar 

  7. Emanuele JJ Jr, Jin H, Yanchunas J Jr, Villafranca JJ (1997) Evaluation of the kinetic mechanism of Escherichia coli uridine diphosphate-N-acetylmuramate:l-alanine ligase. Biochemistry 36:7264–7271

    Article  CAS  Google Scholar 

  8. Perdih A, Hodoscek M, Solmajer T (2009) MurD ligase from E. coli: Tetrahedral intermediate formation study by hybrid quantum mechanical/molecular mechanical replica path method. Proteins: Struct Funct Bioinf 74:744–759

    Google Scholar 

  9. Bertrand JA, Fanchon E, Martin L, Chantalat L, Auger G, Blanot D, van Heijenoort J, Dideberg O (2000) “Open” structures of MurD: domain movements and structural similarities with folylpolyglutamate synthetase. J Mol Biol 301:1257–1266

    Article  CAS  Google Scholar 

  10. Perdih A, Kotnik M, Hodoscek M, Solmajer T (2007) Targeted molecular dynamics simulation studies of binding and conformational changes in E. Coli MurD. Proteins: Struct Funct Bioinf 68:243–254

    Google Scholar 

  11. Perdih A, Solmajer T (2012) MurD ligase from E. coli: C-terminal domain closing motion. Comput Theor Chem 979:73–81

    Article  CAS  Google Scholar 

  12. Zoeiby AE, Sanschagrin F, Levesque RC (2002) Structure and function of the Mur enzymes: development of novel inhibitors. Mol Microbiol 47:1–12

    Article  Google Scholar 

  13. Tanner ME, Vaganay S, van Heijenoort J, Blanot D (1996) Phosphinate inhibitors of the d-glutamic acid-adding enzyme of peptidoglycan biosynthesis. J Org Chem 61:1756–1760

    Article  CAS  Google Scholar 

  14. Kotnik M, Humljan J, Contreras-Martel C, Oblak M, Kristan K, Hervé M, Blanot D, Urleb U, Gobec S, Dessen A, Solmajer T (2007) Structural and functional characterization of enantiomeric glutamic acid derivatives as potential transition state analogue inhibitors of MurD ligase. J Mol Biol 370:107–115

    Article  CAS  Google Scholar 

  15. Perdih A, Bren U, Solmajer T (2009) Binding free-energy calculations of N-sulphonyl glutamic acid inhibitors of MurD ligase. J Mol Model 15:983–996

    Article  CAS  Google Scholar 

  16. Zidar N, Tomasic T, Sink R, Rupnik V, Kovac A, Turk S, Patin D, Blanot D, Contreras Martel C, Dessen A, Müller Premru M, Zega A, Gobec S, Peterlin Masic L, Kikelj D (2010) Discovery of novel 5-benzylidenerhodanine and 5-benzylidenethiazolidine-2,4-dione inhibitors of MurD ligase. J Med Chem 53:6584–6594

    Article  CAS  Google Scholar 

  17. Tomašić T, Zidar N, Šink R, Kovač A, Blanot D, Contreras-Martel C, Dessen A, Müller-Premru M, Zega A, Gobec S, Kikelj D, Peterlin Mašič L (2011) Structure-based design of a new series of d-glutamic acid based inhibitors of bacterial UDP-N-acetylmuramoyl-l-alanine:d-glutamate ligase (MurD). J Med Chem 54:4600–4610

  18. Sosič I, Barreteau H, Simčič M, Sink R, Cesar J, Zega A, Grdadolnik SG, Contreras-Martel C, Dessen A, Amoroso A, Joris B, Blanot D, Gobec S (2011) Second-generation sulphonamide inhibitors of d-glutamic acid-adding enzyme: activity optimisation with conformationally rigid analogues of d-glutamic acid. Eur J Med Chem 46:2880–2894

    Article  Google Scholar 

  19. Perdih A, Kovač A, Wolber G, Blanot D, Gobec S, Solmajer T (2009) Discovery of novel benzene 1,3-dicarboxylic acid inhibitors of bacterial MurD and MurE ligases by structure-based virtual screening approach. Bioorg Med Chem Lett 19:2668–2673

    Article  CAS  Google Scholar 

  20. Åqvist J, Medina C, Samuelson JE (1994) A new method for predicting binding affinity in computer-aided drug design. Protein Eng 7:385–391

    Article  Google Scholar 

  21. Åqvist J, Luzhkov VB, Brandsdal BO (2002) Ligand binding affinities from MD simulations. Acc Chem Res 35:358–365

    Article  Google Scholar 

  22. Marelius J, Kolmodin K, Feierberg I, Åqvist J (1998) A molecular dynamics program for free energy calculations and empirical valence bond simulations in biomolecular systems. J Mol Graph Model 16:213–225

    CAS  Google Scholar 

  23. Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz M Jr, Ferguson DM, Spellmeyer DC, Fox T, Caldwell JW, Kollman PA (1995) A second generation force field for the simulation of proteins, nucleic acids, and organic molecules. J Am Chem Soc 117:5179–5197

    Article  CAS  Google Scholar 

  24. Gaussian 09, Revision A.1, Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Mennucci B, Petersson GA, Nakatsuji H, Caricato M, Li X, Hratchian HP, Izmaylov AF, Bloino J, Zheng G, Sonnenberg JL, Hada M, Ehara M, Toyota K, Fukuda R, Hasegawa J, Ishida M, Nakajima T, Honda Y, Kitao O, Nakai H, Vreven T, Montgomery JA Jr, Peralta JE, Ogliaro F, Bearpark M, Heyd JJ, Brothers E, Kudin KN, Staroverov VN, Kobayashi R, Normand J, Raghavachari K, Rendell A, Burant JC, Iyengar SS, Tomasi J, Cossi M, Rega N, Millam JM, Klene M, Knox JE, Cross JB, Bakken V, Adamo C, Jaramillo J, Gomperts R, Stratmann RE, Yazyev O, Austin AJ, Cammi R, Pomelli C, Ochterski JW, Martin RL, Morokuma K, Zakrzewski VG, Voth GA, Salvador P, Dannenberg JJ, Dapprich S, Daniels AD, Farkas Ö, Foresman JB, Ortiz JV, Cioslowski J, Fox DJ, Gaussian, Inc., Wallingford CT, 2009

  25. Bayly CI, Cieplak P, Cornell WD, Kollman PA (1993) A well-behaved electrostatic potential based method using charge restrains for deriving atomic charges: the RESP model. J Phys Chem 97:10269–10280

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  27. King G, Warshel A (1989) A surface constrained all-atom solvent model for effective simulations of polar solutions. J Chem Phys 91:3647–3661

    Article  CAS  Google Scholar 

  28. Lee FS, Warshel A (1992) A local reaction field method for fast evaluation of long-range electrostatic interactions in molecular simulations. J Chem Phys 97:3100–3107

    Article  CAS  Google Scholar 

  29. Handler N, Brunhofer G, Studenik C, Leisser K, Jaeger W, Parth S, Erker T (2007) ‘Bridged’ stilbene derivatives as selective cyclooxygenase-1 inhibitors. Bioorg Med Chem 15:6109–6118

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  31. Christ CD, Mark AE, van Gunsteren WF (2010) Basic ingredients of free energy calculations: a review. J Comput Chem 31:1569–1582

    CAS  Google Scholar 

  32. Chen X, Tropsha A (2006) Calculation of the relative binding affinity of enzyme inhibitors using the generalized linear response method. J Chem Theory Comput 2:1435–1443

    Article  CAS  Google Scholar 

  33. Carlson J, Boukharta L, Aquist J (2008) Combining docking, molecular dynamics and the linear interaction energy method to predict binding modes and affinities for non-nucleoside inhibitors to HIV-1 reverse transcriptase. J Med Chem 51:2648–2656

    Article  Google Scholar 

  34. Kolb P, Huang D, Dey F, Caflisch A (2008) Discovery of kinase inhibitors by high-throughput docking and scoring based on a transferable linear interaction energy model. J Med Chem 51:1179–1188

    Article  CAS  Google Scholar 

  35. Bortolato A, Moro S (2007) In silico binding free energy predictability by using the linear interaction energy (LIE) method: bromobenzimidazole CK2 inhibitors as a case study. J Chem Inf Model 47:572–582

    Article  CAS  Google Scholar 

  36. Bren M, Florián J, Mavri J, Bren U (2007) Do all pieces make a whole? Thiele cumulants and the free energy decomposition. Theor Chem Acc 117:535–540

    Article  CAS  Google Scholar 

  37. Baell JB, Holloway GA (2010) New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J Med Chem 53:2719–2740

    Article  CAS  Google Scholar 

  38. Mendgen T, Steuer C, Klein CD (2011) Privileged scaffolds or promiscuous binders—a comparative study on rhodanines and related heterocycles in medicinal chemistry. J Med Chem 55:743–753

    Article  Google Scholar 

  39. McGovern SL, Stoichet BK (2003) Kinase inhibitors: not just for kinases anymore. J Med Chem 46:1478–1783

    Article  CAS  Google Scholar 

  40. Baum B, Muley L, Smolinski M, Heine A, Hangauer D, Klebe G (2010) Non-additivity of functional group contributions in protein-ligand binding: a comprehensive study by crystallography and isothermal titration calorimetry. J Mol Biol 397:1042–1054

    Article  CAS  Google Scholar 

  41. Patel Y, Gillet VJ, Howe T, Pastor J, Oyarzabal J, Willett P (2008) Assessment of additive/nonadditive effects in structure-activity relationships: implications for iterative drug design. J Med Chem 51:7552–7562

    Article  CAS  Google Scholar 

  42. Kuhn B, Fuchs JE, Reutlinger M, Stahl M, Taylor NR (2011) Rationalizing tight ligand binding through cooperative interaction networks. J Chem Inf Model 51:3180–3198

    Article  CAS  Google Scholar 

  43. Goodford PJ (1985) A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J Med Chem 28:857–864

    Article  Google Scholar 

  44. Kollman PA (1993) Free energy calculations: applications to chemical and biochemical phenomena. Chem Rev 93:2395–2417

    Article  CAS  Google Scholar 

  45. Wolber G, Langer T (2005) LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. J Chem Inf Model 45:160–169

    Article  CAS  Google Scholar 

  46. Wolber G, Dornhofer A, Langer T (2006) Efficient overlay of small organic molecules using 3D pharmacophores. J Comput Aided Mol Design 20:773–788

    Article  CAS  Google Scholar 

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Acknowledgments

This work was supported by the postdoctoral grant of the Ministry of Higher Education, Science and Technology of the Republic of Slovenia (Grant Number: Z1-4111).The authors would like thank Dr. Jernej Zidar and Barbara Pogorelčnik from the National institute of Chemistry, Slovenia, for their helpful technical assistance and Dr. Yasmin Aristei from Molecular Discovery Ltd. for GRID map calculations. Dr. Urban Bren from the National Institute of Chemistry, Ljubljana is acknowledged for introducing us to LIE methodology in our previous binding study of MurD inhibitors.

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Authors and Affiliations

  1. National Institute of Chemistry, Hajdrihova 19, 1001, Ljubljana, Slovenia

    Andrej Perdih & Tom Solmajer

  2. Institute of Pharmacy, Freie Universität Berlin, Königin Luise-Strasse 2+4, 14195, Berlin, Germany

    Andrej Perdih & Gerhard Wolber

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  1. Andrej Perdih
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Correspondence to Andrej Perdih.

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Perdih, A., Wolber, G. & Solmajer, T. Molecular dynamics simulation and linear interaction energy study of d-Glu-based inhibitors of the MurD ligase. J Comput Aided Mol Des 27, 723–738 (2013). https://doi.org/10.1007/s10822-013-9673-3

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  • DOI: https://doi.org/10.1007/s10822-013-9673-3

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