Journal of Chemical Biology

, Volume 3, Issue 4, pp 175–187 | Cite as

Virtual screening for potential inhibitors of homology modeled Leptospira interrogans MurD ligase

  • Amineni UmamaheswariEmail author
  • Dibyabhaba Pradhan
  • Marisetty Hemanthkumar
Original Article


The life-threatening infections caused by Leptospira serovars remain a global challenge since long time. Prevention of infection by controlling environmental factors being difficult to practice in developing countries, there is a need for designing potent anti-leptospirosis drugs. ATP-dependent MurD involved in biosynthesis of peptidoglycan was identified as common drug target among pathogenic Leptospira serovars through subtractive genomic approach. Peptidoglycan biosynthesis pathway being unique to bacteria and absent in host represents promising target for antimicrobial drug discovery. Thus, MurD 3D models were generated using crystal structures of 1EEH and 2JFF as templates in Modeller9v7. Structural refinement and energy minimization of the model was carried out in Maestro 9.0 applying OPLS-AA 2001 force field and was evaluated through Procheck, ProSA, PROQ, and Profile 3D. The active site residues were confirmed from the models in complex with substrate and inhibitor. Four published MurD inhibitors (two phosphinics, one sulfonamide, and one benzene 1,3-dicarbixylic acid derivative) were queried against more than one million entries of Ligand.Info Meta-Database to generate in-house library of 1,496 MurD inhibitor analogs. Our approach of virtual screening of the best-ranked compounds with pharmacokinetics property prediction has provided 17 novel MurD inhibitors for developing anti-leptospirosis drug targeting peptidoglycan biosynthesis pathway.


Peptidoglycan biosynthesis Leptospirosis Virtual high-throughput screening MurD inhibitors 



The study was supported by grants from DBT, Ministry of Science and Technology, Government of India, New Delhi. We are grateful to Dr. B. Vengamma, Director, for providing constant support and encouragement for research at SVIMS Bioinformatics Centre, where this work has been performed. We thank Prof. S. Ramakumar, IISc., Bangalore for rendering critical valuable suggestions on the present work.


  1. 1.
    Chopra I, Schofield C, Everett M, O'Neill A, Miller K, Wilcox M, Frère JM, Dawson M, Czaplewski L, Urleb U, Courvalin P (2008) Treatment of health-care-associated infections caused by Gram-negative bacteria: a consensus statement. Lancet Infect Dis 8:133–139CrossRefGoogle Scholar
  2. 2.
    World Health Organization (1999) Leptospirosis worldwide. Wkly Epidemiol Rec 74:237–242Google Scholar
  3. 3.
    Bharti AR, Nally JE, Ricaldi JN, Matthias MA, Diaz MM, Lovett MA, Levett PN, Gilman RH, Willig MR, Gotuzzo E, Vinetz JM (2003) Leptospirosis: a zoonotic disease of global importance. The Lancet Infect Dis 3:757–771CrossRefGoogle Scholar
  4. 4.
    Trueba G, Zapata S, Madrid K, Cullen P, Haake D (2004) Cell aggregation: a mechanism of pathogenic Leptospira to survive in fresh water. Int Microbiol 7:35–40Google Scholar
  5. 5.
    Levett PN (2001) Leptospirosis. Clin Microbiol Rev 14:296–326CrossRefGoogle Scholar
  6. 6.
    Guidugli F, Castro AA, Atallah (2000) Antibiotics for preventing leptospirosis. Cochrane Database Syst Rev 4:CD001305Google Scholar
  7. 7.
    Wang Z, Jin L, Wegrzyn A (2007) Leptospirosis vaccines. Microb Cell Fact 6:39CrossRefGoogle Scholar
  8. 8.
    Barreteau H, Kovac A, Boniface A, Sova M, Gobec S, Blanot D (2008) Cytoplasmic steps of peptidoglycan biosynthesis. FEMS Microbiol Rev 32:168–207CrossRefGoogle Scholar
  9. 9.
    Vollmer W, Blanot D, Pedro MA (2008) Peptidoglycan structure and architecture. FEMS Microbiol Rev 32:149–167CrossRefGoogle Scholar
  10. 10.
    Van Heijeinoot J (2001) Recent advances in the formation of bacterial peptidoglycan monomer unit. Nat Prod Rep 18:503–519CrossRefGoogle Scholar
  11. 11.
    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 354:189–196CrossRefGoogle Scholar
  12. 12.
    El Zoeiby A, Sanschagrin F, Levesque RC (2003) Structure and function of the Mur enzymes: development of novel inhibitors. Mol Microbiol 47:1–12CrossRefGoogle Scholar
  13. 13.
    Strancar K, Blanot D, Gobec S (2006) Design, synthesis and structure-activity relationships of new phosphinate inhibitors of MurD. Bioorg Med Chem Lett 16:343–348CrossRefGoogle Scholar
  14. 14.
    Humljan J, Kotnik M, Contreras-Martel C, Blanot D, Urleb U, Dessen A, Solmajer T, Gobec S (2008) Novel naphthalene-N-sulfonyl-D-glutamic acid derivatives as inhibitors of MurD, a key peptidoglycan biosynthesis enzyme. J Med Chem 51:7486–7494CrossRefGoogle Scholar
  15. 15.
    Perdih A, Kovac 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
  16. 16.
    Eswar N, Eramian D, Webb B, Shen MY, Sali A (2008) Protein structure modeling with MODELLER. Methods Mol Biol 426:145–159CrossRefGoogle Scholar
  17. 17.
    Maestro 9.0, versuib 70110, Schrodinger, New YorkGoogle Scholar
  18. 18.
    Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A (2005) Protein Identification and Analysis Tools on the ExPASy Server. In: John M. Walker (ed) The Proteomics Protocols Handbook. Humana Press, pp 571–607Google Scholar
  19. 19.
    Bryson K, McGuffin LJ, Marsden RL, Ward JJ, Sodhi JS, Jones DT (2005) Protein structure prediction servers at University College London. Nucleic Acids Res 33:W36–W38CrossRefGoogle Scholar
  20. 20.
    Sonnhammer EL, Eddy SR, Birney E, Bateman A, Durbin R (1998) Pfam: multiple sequence alignments and HMM-profiles of protein domains. Nucleic Acids Res 26:320–322CrossRefGoogle Scholar
  21. 21.
    Murzin AG, Brenner SE, Hubbard T, Chothia C (1995) SCOP: a structural classification of proteins database for the investigation of sequences and structures. J Mol Biol 247:536–540Google Scholar
  22. 22.
    Kanehisa M, Goto S (2000) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 28:27–30CrossRefGoogle Scholar
  23. 23.
    Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402CrossRefGoogle Scholar
  24. 24.
    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
  25. 25.
    Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The ClustalX windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 24:4876–4882CrossRefGoogle Scholar
  26. 26.
    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
  27. 27.
    Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr 26:283–291CrossRefGoogle Scholar
  28. 28.
    Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:W407–W410CrossRefGoogle Scholar
  29. 29.
    Wallner B, Elofsson A (2003) Can correct protein models be identified? Protein Sci 12:1073–1086CrossRefGoogle Scholar
  30. 30.
    Castrignano T, De Meo PD, Cozzetto D, Talamo IG, Tramontano A (2006) The PMDB protein model database. Nucleic Acids Res 34:D306–D309CrossRefGoogle Scholar
  31. 31.
    von Grotthuss M, Pas J, Rychlewski L (2003) Ligand-Info, searching for similar small compounds using index profiles. Bioinformatics 19:1041–1042CrossRefGoogle Scholar
  32. 32.
    Plewczynski D, Hoffmann M, von Grotthuss M, Ginalski K, Rychewski L (2007) In silico prediction of SARS protease inhibitors by virtual high throughput screening. Chem Biol Drug Des 69:269–279CrossRefGoogle Scholar
  33. 33.
    Brooks WH, Daniel KG, Sung SS, Guida WC (2008) Computational validation of the importance of absolute stereochemistry in virtual screening. J Chem Inf Model 48:639–645CrossRefGoogle Scholar
  34. 34.
    Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749CrossRefGoogle Scholar
  35. 35.
    Faine S, Adler B, Bolin C, Perolat P (1999) Appendix 2 Species and serovar list. In: Leptospira and leptospirosis, 2nd edn. Medisci, Melbourne, Australia, pp 138–139Google Scholar
  36. 36.
    Smith CS (2006) Structure, function and dynamics in the Mur family of bacterial cell wall ligases. J Mol Biol 362:640CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Amineni Umamaheswari
    • 1
    Email author
  • Dibyabhaba Pradhan
    • 1
  • Marisetty Hemanthkumar
    • 2
  1. 1.SVIMS Bioinformatics CentreSVIMS UniversityTirupatiIndia
  2. 2.Agricultural Research StationTirupatiIndia

Personalised recommendations