Advertisement

Journal of Computer-Aided Molecular Design

, Volume 29, Issue 6, pp 541–560 | Cite as

Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC–MurF): experimental and computational characterization

  • Andrej PerdihEmail author
  • Martina Hrast
  • Kaja Pureber
  • Hélène Barreteau
  • Simona Golič Grdadolnik
  • Darko Kocjan
  • Stanislav Gobec
  • Tom Solmajer
  • Gerhard Wolber
Article

Abstract

Bacterial resistance to the available antibiotic agents underlines an urgent need for the discovery of novel antibacterial agents. Members of the bacterial Mur ligase family MurC–MurF involved in the intracellular stages of the bacterial peptidoglycan biosynthesis have recently emerged as a collection of attractive targets for novel antibacterial drug design. In this study, we have first extended the knowledge of the class of furan-based benzene-1,3-dicarboxylic acid derivatives by first showing a multiple MurC–MurF ligase inhibition for representatives of the extended series of this class. Steady-state kinetics studies on the MurD enzyme were performed for compound 1, suggesting a competitive inhibition with respect to ATP. To the best of our knowledge, compound 1 represents the first ATP-competitive MurD inhibitor reported to date with concurrent multiple inhibition of all four Mur ligases (MurC–MurF). Subsequent molecular dynamic (MD) simulations coupled with interaction energy calculations were performed for two alternative in silico models of compound 1 in the UMA/d-Glu- and ATP-binding sites of MurD, identifying binding in the ATP-binding site as energetically more favorable in comparison to the UMA/d-Glu-binding site, which was in agreement with steady-state kinetic data. In the final stage, based on the obtained MD data novel furan-based benzene monocarboxylic acid derivatives 811, exhibiting multiple Mur ligase (MurC–MurF) inhibition with predominantly superior ligase inhibition over the original series, were discovered and for compound 10 it was shown to possess promising antibacterial activity against S. aureus. These compounds represent novel leads that could by further optimization pave the way to novel antibacterial agents.

Keywords

Bacterial Mur (MurC–MurF) ligase ATP-competitive inhibition Molecular dynamics (MD) Steady-state kinetics measurements Antibacterial agents Drug design 

Abbreviations

ESP

Electrostatic potential

GAFF

Generalized AMBER Force Field

LIE

Linear interaction energy method

LRF

Local reaction field

MIC

Minimum inhibitory concentration

RA

Residual activity

RMSD

Root-mean square distance

SAR

Structure–activity relationship

SCAAS

Surface constraint all atoms solvent

UDP

Uridine-5′-diphosphate

UMA

Uridine-5′-diphosphate-N-acetylmuramoyl-l-alanine

UMAG

Uridine-5′-diphosphate-N-acetylmuramoyl-l-alanyl-d-glutamate

UMT

Uridine-5′-diphosphate-N-acetylmuramoyl-l-alanyl-d-glutamayl-2,6-diaminopimelic acid

Notes

Acknowledgments

This work was supported by the Ministry of Higher Education, Science and Technology of the Republic of Slovenia Postdoctoral grant number: Z1-4111. The authors would like thank Dr. Jernej Zidar from the Institute of High Performance Computing (IHPC), Singapure and Barbara Pogorelčnik from the National institute of Chemistry, Slovenia, for their technical assistance with MD calculations. Dr. Sandy Favini, Dr. Carlos Contreras-Martel and Dr. Andréa Dessen from the Bacterial Pathogenicity Group at L’Institut de Biologie Structurale (IBS), Grenoble, France are acknowledged and thanked for performing several initial structural experiments on MurD, MurE and MurF enzymes. Dr. Andreja Kovač from the Faculty of Pharmacy, University of Ljubljana is acknowledged for performing initial inhibition assays of some of the novel compounds discussed in this work. Dr. Katja Kristan from Lek Pharmaceuticals is thanked for useful discussions concerning the steady-state kinetics measurements. We are grateful to Dr. Didier Blanot from the Université Paris-Sud, Orsay, France for critical reading of the manuscript.

Supplementary material

Supplementary material 1 (MPG 61967 kb)

Supplementary material 2 (MPG 59716 kb)

10822_2015_9843_MOESM3_ESM.pdf (1 mb)
Supplementary material 3 (PDF 1028 kb)

References

  1. 1.
    Silver LL (2006) Does the cell wall of bacteria remain a viable source of targets for novel antibiotics? Biochem Pharmacol 71:996–1005CrossRefGoogle Scholar
  2. 2.
    Brown ED, Wright GD (2005) New targets and screening approaches in antimicrobial drug discovery. Chem Rev 105:759–774CrossRefGoogle Scholar
  3. 3.
    Silver LL (2011) Challenges of antibacterial discovery. Clin Microbiol Rev 24:71–109CrossRefGoogle Scholar
  4. 4.
    Vollmer W, Blanot D, de Pedro MA (2008) Peptidoglycan structure and architecture. FEMS Microbiol Rev 32:149–167CrossRefGoogle Scholar
  5. 5.
    Sink R, Barreteau H, Patin D, Mengin-Lecreulx D, Gobec S, Blanot D (2013) MurD enzymes: some recent developments. Biomol Concepts 4:539–546CrossRefGoogle Scholar
  6. 6.
    van Heijenoort J (2001) Recent advances in the formation of the bacterial peptidoglycan monomer unit. Nat Prod Rep 18:503–519CrossRefGoogle Scholar
  7. 7.
    Smith CA (2006) Structure, function and dynamics in the mur family of bacterial cell wall ligases. J Mol Biol 362:640–655CrossRefGoogle Scholar
  8. 8.
    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 301:1257–1266CrossRefGoogle Scholar
  9. 9.
    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 68:243–254Google Scholar
  10. 10.
    Perdih A, Solmajer T (2012) MurD ligase from E. coli: c-terminal domain closing motion. Comput Theor Chem 979:73–81CrossRefGoogle Scholar
  11. 11.
    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 289:579–590CrossRefGoogle Scholar
  12. 12.
    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 35:16264–16269CrossRefGoogle Scholar
  13. 13.
    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 36:7264–7271CrossRefGoogle Scholar
  14. 14.
    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 74:744–759CrossRefGoogle Scholar
  15. 15.
    Bouhss A, Dementin S, van Heijenoort J, Parquet C, Blanot D (2002) MurC and MurD synthetases of peptidoglycan biosynthesis: borohydride trapping of acyl-phosphate intermediates. Methods Enzymol 354:189–196Google Scholar
  16. 16.
    Zoeiby AE, Sanschagrin F, Levesque RC (2002) Structure and function of the Mur enzymes: development of novel Inhibitors. Mol Microbiol 47:1–12CrossRefGoogle Scholar
  17. 17.
    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 46:2880–2894CrossRefGoogle Scholar
  18. 18.
    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 61:1756–1760CrossRefGoogle Scholar
  19. 19.
    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 370:107–115CrossRefGoogle Scholar
  20. 20.
    Tomašić T, Sink R, Zidar N, Fic A, Contreras-Martel C, Dessen A, Patin D, Blanot D, Müller-Premru M, Gobec S, Zega A, Kikelj D, Mašič LP (2012) Dual inhibitor of MurD and MurE ligases from Escherichia coli and Staphylococcus aureus. ACS Med Chem Lett 3:626–630CrossRefGoogle Scholar
  21. 21.
    Perdih A, Bren U, Solmajer T (2009) Binding free-energy calculations of N-sulfonyl glutamic acid inhibitors of MurD ligase. J Mol Model 15:983–996CrossRefGoogle Scholar
  22. 22.
    Perdih A, Wolber G, Solmajer T (2013) Molecular dynamics simulation and linear interaction energy study of d-Glu-based inhibitors of the MurD ligase. J Comput Aided Mol Des 27:723–738CrossRefGoogle Scholar
  23. 23.
    Perdih A, Hrast M, Barreteau H, Gobec S, Wolber G, Solmajer T (2014) Inhibitor design strategy based on an enzyme structural flexibility: a case of bacterial MurD ligase. J Chem Inf Model 54:1451–1466CrossRefGoogle Scholar
  24. 24.
    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 19:2668–2673CrossRefGoogle Scholar
  25. 25.
    McGovern SL, Stoichet BK (2003) Kinase inhibitors: not just for kinases anymore. J Med Chem 46:1478–1483CrossRefGoogle Scholar
  26. 26.
    Catalyst; Accelrys Software: San DiegoGoogle Scholar
  27. 27.
    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 45:160–169CrossRefGoogle Scholar
  28. 28.
    Kirchmair J, Markt P, Distinto S, Wolber G, Langer T (2008) Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection—what can we learn from earlier mistakes? J Comput Aided Mol Des 22:213–228CrossRefGoogle Scholar
  29. 29.
    Cereto-Massague A, Guasch L, Valls C, Mulero M, Pujadas G, Garcia-Vallve S (2012) DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets. Bioinformatics 28:1661–1662CrossRefGoogle Scholar
  30. 30.
    Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727–748CrossRefGoogle Scholar
  31. 31.
    Perdih A, Hrast M, Barreteau H, Gobec S, Wolber G, Solmajer T (2014) Benzene-1,3-dicarboxylic acid 2,5-dimethylpyrrole derivatives as multiple inhibitors of bacterial Mur ligases (MurC–MurF). Bioorg Med Chem 22:4124–4134CrossRefGoogle Scholar
  32. 32.
    Bochner BR, Ames BN (1982) Complete analysis of cellular nucleotides by two-dimensional thin layer chromatography. J Biol Chem 257:9759–9769Google Scholar
  33. 33.
    Lasko DR, Wang DIC (1996) On-line monitoring of intracellular ATP concentrations in Escherichia coli fermentations. Biotechnol Bioeng 52:364–372CrossRefGoogle Scholar
  34. 34.
    Gribble FM, Loussouarn G, Tucker SJ, Zhao C, Nichols CG, Ashcroft FM (2000) A novel method for measurement of submembrane ATP concentration. J Biol Chem 275:30046–30049CrossRefGoogle Scholar
  35. 35.
    Beis I, Newsholme EA (1975) The contents of adenine nucleotides, phosphagens and some glycolytic intermediates in resting muscles from vertebrates and invertebrates. Biochem J 152:23–32Google Scholar
  36. 36.
    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 16:213–225CrossRefGoogle Scholar
  37. 37.
    Åqvist J, Medina C, Samuelson JE (1994) A new method for predicting binding affinity in computer-aided drug design. Protein Eng 7:385–391CrossRefGoogle Scholar
  38. 38.
    Åqvist J, Luzhkov VB, Brandsdal BO (2002) Ligand Binding Affinities from MD simulations. Acc Chem Res 35:358–365CrossRefGoogle Scholar
  39. 39.
    Wermuth C-G (ed) (2008) The practice of medicinal chemistry, 3rd edn. Academic Press, New YorkGoogle Scholar
  40. 40.
    Sinko W, Wang Y, Zhu W, Zhang Y, Feixas F, Cox CL, Mitchell DA, Oldfield E, McCammon JA (2014) Undecaprenyl diphosphate synthase inhibitors: antibacterial drug leads. J Med Chem 57:5693–5701CrossRefGoogle Scholar
  41. 41.
    Brvar M, Perdih A, Hodnik V, Renko M, Anderluh G, Jerala R, Solmajer T (2012) In silico discovery and biophysical evaluation of novel 5-(2-hydroxybenzylidene) rhodanine inhibitors of DNA gyrase B. Bioorg Med Chem 20:2572–2580CrossRefGoogle Scholar
  42. 42.
    Xu Y, Brenning B, Clifford A, Vollmer D, Bearss J, Jones C, McCarthy V, Shi C, Wolfe B, Aavula B, Warner S, Bearss DJ, McCullar MV, Schuch R, Pelzek A, Bhaskaran SS, Stebbins CE, Goldberg AR, Fischetti VA, Vankayalapati H (2013) Discovery of novel putative inhibitors of UDP-GlcNAc 2-epimerase as potent antibacterial agents. ACS Med Chem Lett 4:1142–1147CrossRefGoogle Scholar
  43. 43.
    Tomasić T, Masic LP (2009) Rhodanine as a privileged scaffold in drug discovery. Curr Med Chem 16(13):1596–1629CrossRefGoogle Scholar
  44. 44.
    Baell J, Walters MA (2014) Chemistry: chemical con artists foil drug discovery. Nature 513:481–483CrossRefGoogle Scholar
  45. 45.
    Mariner KR, Trowbridge R, Agarwal AK, Miller K, O’Neill AJ, Fishwick CW, Chopra I (2010) Furanyl-rhodanines are unattractive drug candidates for development as inhibitors of bacterial RNA polymerase. Antimicrob Agents Chemother 54:4506–4509CrossRefGoogle Scholar
  46. 46.
    Tomasić T, Masic LP (2012) Rhodanine as a scaffold in drug discovery: a critical review of its biological activities and mechanisms of target modulation. Expert Opin Drug Discov 7:549–560CrossRefGoogle Scholar
  47. 47.
    Ramirez MA, Borja NL (2008) Epalrestat: an aldose reductase inhibitor for the treatment of diabetic neuropathy. Pharmacotherapy 5:646–655CrossRefGoogle Scholar
  48. 48.
    Wolber G, Dornhofer A, Langer T (2006) Efficient overlay of small organic molecules using 3D pharmacophores. J Comput Aided Mol Des 20:773–788CrossRefGoogle Scholar
  49. 49.
    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 117:5179–5197CrossRefGoogle Scholar
  50. 50.
    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 Jr JA, 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 (2009) Gaussian, Inc., Wallingford, CTGoogle Scholar
  51. 51.
    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 97:10269–10280CrossRefGoogle Scholar
  52. 52.
    Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935CrossRefGoogle Scholar
  53. 53.
    King G, Warshel A (1989) A surface constrained all-atom solvent model for effective simulations of polar solutions. J Chem Phys 91:3647–3661CrossRefGoogle Scholar
  54. 54.
    Lee FS, Warshel A (1992) A local reaction field method for fast evaluation of long-range electrostatic interactions in molecular simulations. J Chem Phys 97:3100–3107CrossRefGoogle Scholar
  55. 55.
    Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph 14:33–38CrossRefGoogle Scholar
  56. 56.
    Auger G, Martin L, Bertrand J, Ferrari P, Fanchon E, Vaganay S, Petillot Y, van Heijenoort J, Blanot D, Dideberg O (1998) Large-scale preparation, purification, and crystallization of UDP-N-acetylmuramoyl-l-alanine: d-glutamate ligase from Escherichia coli. Prot Express Purif 13:23–29CrossRefGoogle Scholar
  57. 57.
    Lanzetta PA, Alvarez LJ, Reinach PS, Candia O (1979) An improved assay for nanomole amounts of inorganic phosphate. Anal Biochem 100:95–97CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andrej Perdih
    • 1
    • 2
    Email author
  • Martina Hrast
    • 3
  • Kaja Pureber
    • 1
    • 4
  • Hélène Barreteau
    • 5
  • Simona Golič Grdadolnik
    • 1
    • 4
  • Darko Kocjan
    • 1
    • 4
  • Stanislav Gobec
    • 3
  • Tom Solmajer
    • 1
  • Gerhard Wolber
    • 2
  1. 1.National Institute of ChemistryLjubljanaSlovenia
  2. 2.Institute of PharmacyFreie Universität BerlinBerlinGermany
  3. 3.Faculty of PharmacyUniversity of LjubljanaLjubljanaSlovenia
  4. 4.EN-FIST Centre of ExcellenceLjubljanaSlovenia
  5. 5.Laboratoire des Enveloppes Bactériennes et Antibiotiques, IBBMCUniversité Paris-SudOrsayFrance

Personalised recommendations