Journal of Molecular Modeling

, Volume 19, Issue 1, pp 179–192 | Cite as

Structural and chemical basis for enhanced affinity to a series of mycobacterial thymidine monophosphate kinase inhibitors: fragment-based QSAR and QM/MM docking studies

  • Renata V. Bueno
  • Ney R. Toledo
  • Bruno J. Neves
  • Rodolpho C. Braga
  • Carolina H. Andrade
Original Paper


Tuberculosis (TB) still remains one of the most deadly infectious diseases. Mycobacterium tuberculosis thymidine monophosphate kinase (TMPKmt) has emerged as an attractive molecular target for the design of a novel class of anti-TB agents since blocking it will affect the pathways involved in DNA replication. Aiming at shedding some light on structural and chemical features that are important for the affinity of thymidine derivatives to TMPKmt, we have employed a special fragment-based method to develop robust quantitative structure-activity relationship models for a large and chemically diverse series of thymidine-based analogues. Significant statistical parameters (r 2  = 0.94, q 2  = 0.76, r 2 pred  = 0.89) were obtained, indicating the reliability of the hologram QSAR model in predicting the biological activity of untested compounds. The 2D model was then used to predict the potency of an external test set, and the predicted values obtained from the HQSAR model were in good agreement with the experimental results. We have accordingly designed novel TMPKmt inhibitors by utilizing the fragments proposed by HQSAR analysis and predicted with good activity in the developed models. The new designed compounds also presented drug-like characteristics based on Lipinski’s rule of 5. The generated molecular recognition patterns gathered from the HQSAR analysis combined with quantum mechanics/molecular mechanics (QM/MM) docking studies, provided important insights into the chemical and structural basis involved in the molecular recognition process of this series of thymidine analogues and should be useful for the design of new potent anti-TB agents.


Fragment-based HQSAR QM/MM docking Thymidine monophosphate kinase Tuberculosis 



The authors would like to thank Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Fundação de Amparo à Pesquisa do Estado de Goiás (FAPEG) for financial support.

Supplementary material

894_2012_1527_MOESM1_ESM.doc (402 kb)
ESM 1 (DOC 401 kb)


  1. 1.
    WHO (2010) Global tuberculosis control. WHO/HTM/TB/2010.7.Google Scholar
  2. 2.
    Andrade CH, Salum LDB, Mesquita Pasqualoto KF, Ferreira EI, Andricopulo AD (2008) Three-dimensional quantitative structure-activity relationships for a large series of potent antitubercular agents. Lett Drug Des Discov 5:377–387. doi: 10.2174/157018008785777289 CrossRefGoogle Scholar
  3. 3.
    Andrade CH, Pasqualoto KFM, Zaim MH, Ferreira EI (2008) Abordagem racional no planejamento de novos tuberculostáticos: inibidores da InhA, enoil-ACP redutase do M. tuberculosis. Rev Bras Cienc Farm 44. doi: 10.1590/S1516-93322008000200002
  4. 4.
    Burki T (2010) Tuberculosis-resistance, funding, and drugs. Lancet Infect Dis 10:297–298CrossRefGoogle Scholar
  5. 5.
    Dorman SE, Chaisson RE (2007) From magic bullets back to the magic mountain: the rise of extensively drug-resistant tuberculosis. Nat Med 13:295–298. doi: 10.1038/nm0307-295 CrossRefGoogle Scholar
  6. 6.
    Munier-Lehmann H, Chaffotte A, Pochet S, Labesse G (2001) Thymidylate kinase of Mycobacterium tuberculosis: a chimera sharing properties common to eukaryotic and bacterial enzymes. Protein Sci 10:1195–1205. doi: 10.1110/ps.45701 CrossRefGoogle Scholar
  7. 7.
    Ostermann N, Schlichting I, Brundiers R, Konrad M, Reinstein J, Veit T, Goody RS, Lavie A (2000) Insights into the phosphoryltransfer mechanism of human thymidylate kinase gained from crystal structures of enzyme complexes along the reaction coordinate. Structure 8:629–642. doi: 10.1016/S0969-2126(00)00149-0 CrossRefGoogle Scholar
  8. 8.
    de la Sierra L, Munier-Lehmann H, Gilles AM, Bârzu O, Delarue M (2001) X-ray structure of TMP kinase from Mycobacterium tuberculosis complexed with TMP at 1.95 A resolution. J Mol Biol 311:87–100. doi: 10.1006/jmbi.2001.4843 CrossRefGoogle Scholar
  9. 9.
    Familiar O, Munier-Lehmann H, Aínsa JA, Camarasa M-J, Pérez-Pérez M-J (2010) Design, synthesis and inhibitory activity against Mycobacterium tuberculosis thymidine monophosphate kinase of acyclic nucleoside analogues with a distal imidazoquinolinone. Eur J Med Chem 45:5910–5918. doi: 10.1016/j.ejmech.2010.09.056 CrossRefGoogle Scholar
  10. 10.
    Familiar O, Munier-Lehmann H, Negri A, Gago F, Douguet D, Rigouts L, Hernández A-I, Camarasa M-J, Pérez-Pérez M-J (2008) Exploring acyclic nucleoside analogues as inhibitors of Mycobacterium tuberculosis thymidylate kinase. Chem Med Chem 3:1083–1093. doi: 10.1002/cmdc.200800060 Google Scholar
  11. 11.
    Van Daele I, Munier-Lehmann H, Froeyen M, Balzarini J, Van Calenbergh S (2007) Rational design of 5′-thiourea-substituted alpha-thymidine analogues as thymidine monophosphate kinase inhibitors capable of inhibiting mycobacterial growth. J Med Chem 50:5281–5292. doi: 10.1021/jm0706158 CrossRefGoogle Scholar
  12. 12.
    Van Daele I, Munier-Lehmann H, Hendrickx PMS, Marchal G, Chavarot P, Froeyen M, Qing L, Martins JC, Van Calenbergh S (2006) Synthesis and biological evaluation of bicyclic nucleosides as inhibitors of M. tuberculosis thymidylate kinase. Chem Med Chem 1:1081–1090. doi: 10.1002/cmdc.200600028 Google Scholar
  13. 13.
    Vanheusden V, Munier-Lehmann H, Froeyen M, Dugué L, Heyerick A, De Keukeleire D, Pochet S, Busson R, Herdewijn P, van Calenbergh S (2003) 3′-C-branched-chain-substituted nucleosides and nucleotides as potent inhibitors of Mycobacterium tuberculosis thymidine monophosphate kinase. J Med Chem 46:3811–3821. doi: 10.1021/jm021108n CrossRefGoogle Scholar
  14. 14.
    Vanheusden V, Munier-Lehmann H, Pochet S, Herdewijn P, van Calenbergh S (2002) Synthesis and evaluation of thymidine-5′-O-monophosphate analogues as inhibitors of Mycobacterium tuberculosis thymidylate kinase. Bioorg Med Chem Lett 12:2695–2698CrossRefGoogle Scholar
  15. 15.
    Vanheusden V, Munier-Lehmann H, Froeyen M, Busson R, Rozenski J, Herdewijn P, Van Calenbergh S (2004) Discovery of bicyclic thymidine analogues as selective and high-affinity inhibitors of Mycobacterium tuberculosis thymidine monophosphate kinase. J Med Chem 47:6187–6194. doi: 10.1021/jm040847w CrossRefGoogle Scholar
  16. 16.
    Vanheusden V, Rompaeya PV, Munier-Lehmannb H, Pochetc S, Herdewijnd P, Calenbergh SV (2003) Thymidine and thymidine-5-O-monophosphate analogues as inhibitors of Mycobacterium tuberculosis thymidylate kinase. Bioorg Med Chem Lett 13:3045–3048. doi: 10.1016/S0960-894X(03)00643-7 CrossRefGoogle Scholar
  17. 17.
    Van Calenbergh S, Pochet S, Munier-Lehmann H (2012) Drug design and identification of potent leads against mycobacterium tuberculosis thymidine monophosphate kinase. Curr Top Med Chem 12:694–705CrossRefGoogle Scholar
  18. 18.
    Aparna V, Jeevan J, Ravi M, Desiraju GR, Gopalakrishnan B (2006) 3D-QSAR studies on antitubercular thymidine monophosphate kinase inhibitors based on different alignment methods. Bioorg Med Chem Lett 16:1014–1020. doi: 10.1016/j.bmcl.2005.10.086 CrossRefGoogle Scholar
  19. 19.
    Andrade CH, Pasqualoto KFM, Ferreira EI, Hopfinger AJ (2009) Rational design and 3D-pharmacophore mapping of 5′-thiourea-substituted alpha-thymidine analogues as mycobacterial TMPK inhibitors. J Chem Inf Model 49:1070–1078. doi: 10.1021/ci8004622 CrossRefGoogle Scholar
  20. 20.
    Andrade CH, Pasqualoto KFM, Ferreira EI, Hopfinger AJ (2010) 3D-Pharmacophore mapping of thymidine-based inhibitors of TMPK as potential antituberculosis agents. J Comput Aided Mol Des 24:157–172. doi: 10.1007/s10822-010-9323-y CrossRefGoogle Scholar
  21. 21.
    Salum LB, Diasb LC, Andricopulo AD (2009) Structural and chemical basis for anticancer activity of a series of beta-Tubulin ligands: molecular modeling and 3D QSAR studies. J Braz Chem Soc 20:693–703CrossRefGoogle Scholar
  22. 22.
    Salum LB, Valadares NF (2010) Fragment-guided approach to incorporating structural information into a CoMFA study: BACE-1 as an example. J Comput Aided Mol Des 24:803–817. doi: 10.1007/s10822-010-9375-z CrossRefGoogle Scholar
  23. 23.
    Blondin C, Serina L, Wiesmüller L, Gilles AM, Bârzu O (1994) Improved spectrophotometric assay of nucleoside monophosphate kinase activity using the pyruvate kinase/lactate dehydrogenase coupling system. Anal Biochem 220:219–221. doi: 10.1006/abio.1994.1326 CrossRefGoogle Scholar
  24. 24.
    Young DC (2009) Computational drug design: a guide for computational and medicinal chemists. Wiley, HobokenGoogle Scholar
  25. 25.
    Andrade CH, Pasqualoto KFM, Ferreira EI, Hopfinger AJ (2010) 4D-QSAR: perspectives in drug design. Molecules 15:3281–3294. doi: 10.3390/molecules15053281 CrossRefGoogle Scholar
  26. 26.
    Jakalian A, Jack DB, Bayly CI (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem 23:1623–1641. doi: 10.1002/jcc.10128 CrossRefGoogle Scholar
  27. 27.
    Salum LB, Andricopulo AD (2009) Fragment-based QSAR: perspectives in drug design. Mol Divers 13:277–285. doi: 10.1007/s11030-009-9112-5 CrossRefGoogle Scholar
  28. 28.
    Cho AE, Guallar V, Berne BJ, Friesner R (2005) Importance of accurate charges in molecular docking: quantum mechanical/molecular mechanical (QM/MM) approach. J Comput Chem 26:915–931. doi: 10.1002/jcc.20222 CrossRefGoogle Scholar
  29. 29.
    Shelley JC, Cholleti A, Frye LL, Greenwood JR, Timlin MR, Uchimaya M (2007) Epik: a software program for pK(a) prediction and protonation state generation for drug-like molecules. J Comput Aided Mol Des 21:681–691. doi: 10.1007/s10822-007-9133-z CrossRefGoogle Scholar
  30. 30.
    Banks JL, Beard HS, Cao Y, Cho AE, Damm W, Farid R, Felts AK, Halgren TA, Mainz DT, Maple JR, Murphy R, Philipp DM, Repasky MP, Zhang LY, Berne BJ, Friesner RA, Gallicchio E, Levy RM (2005) Integrated modeling program, applied chemical theory (IMPACT). J Comput Chem 26:1752–1780. doi: 10.1002/jcc.20292 CrossRefGoogle Scholar
  31. 31.
    Van Calenbergh S (2006) Structure-aided design of inhibitors of Mycobacterium tuberculosis thymidylate kinase. Verh K Acad Geneeskd Belg 68:223–248Google Scholar
  32. 32.
    Eldridge MD, Murray CW, Auton TR, Paolini GV, Mee RP (1997) Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. J Comput Aided Mol Des 11:425–445CrossRefGoogle Scholar
  33. 33.
    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 47:1739–1749. doi: 10.1021/jm0306430 CrossRefGoogle Scholar
  34. 34.
    Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46:3–26CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Renata V. Bueno
    • 1
  • Ney R. Toledo
    • 1
  • Bruno J. Neves
    • 1
  • Rodolpho C. Braga
    • 1
  • Carolina H. Andrade
    • 1
  1. 1.Laboratório de Planejamento de Fármacos e Estudos de Metabolismo por Modelagem Molecular (LabMol), Faculdade de FarmáciaUniversidade Federal de GoiásGoianiaBrazil

Personalised recommendations