Journal of Chemical Sciences

, Volume 128, Issue 5, pp 719–732 | Cite as

Dynamic ligand-based pharmacophore modeling and virtual screening to identify mycobacterial cyclopropane synthase inhibitors

  • U DEVA PRIYAKUMAREmail author


Multidrug resistance in Mycobacterium tuberculosis (M. Tb) and its coexistence with HIV are the biggest therapeutic challenges in anti-M. Tb drug discovery. The current study reports a Virtual Screening (VS) strategy to identify potential inhibitors of Mycobacterial cyclopropane synthase (CmaA1), an important M. Tb target considering the above challenges. Five ligand-based pharmacophore models were generated from 40 different conformations of the cofactors of CmaA1 taken from molecular dynamics (MD) simulations trajectories of CmaA1. The screening abilities of these models were validated by screening 23 inhibitors and 1398 non-inhibitors of CmaA1. A VS protocol was designed with four levels of screening i.e., ligand-based pharmacophore screening, structure-based pharmacophore screening, docking and absorption, distribution, metabolism, excretion and the toxicity (ADMET) filters. In an attempt towards repurposing the existing drugs to inhibit CmaA1, 6,429 drugs reported in DrugBank were considered for screening. To find compounds that inhibit multiple targets of M. Tb as well as HIV, we also chose 701 and 11,109 compounds showing activity below 1 μM range on M. Tb and HIV cell lines, respectively, collected from ChEMBL database. Thus, a total of 18,239 compounds were screened against CmaA1, and 12 compounds were identified as potential hits for CmaA1 at the end of the fourth step. Detailed analysis of the structures revealed these compounds to interact with key active site residues of CmaA1.

Graphical Abstract

The paper presents generation of dynamic ligand-based pharmacophore model for Mycobacterial cyclopropane synthase and their validation. Aiming towards drug repositioning and selection of multi-target inhibitors, selected compounds from DrugBank and ChEMBL have been screened by a four-step virtual screening using the models and 12 potential compounds are identified.


Virtual screening pharmacophore model docking tuberculosis HIV ADMET filters drug repositioning poly-pharmacology 



CC thanks Department of Science and Technology (DST), New Delhi for financial assistance through INSPIRE fellowship. UDP thanks DAE-BRNS for financial assistance. GNS thanks CSIR, New Delhi for financial support in the form of XII five year project (GENESIS).

Supplementary material

12039_2016_1069_MOESM1_ESM.pdf (702 kb)
(PDF 702 KB)


  1. 1.
    Balganesh T S, Alzari P M and Cole S T 2008 Trends Pharmacol. Sci. 29 576CrossRefGoogle Scholar
  2. 2.
    WHO 2014 Global Tuberculosis Report. http// (accessed on 20/06/2015)
  3. 3.
    Zumla A, George A, Sharma V, Herbert N and Ilton B M 2013 Lancet 382 1765CrossRefGoogle Scholar
  4. 4.
    Varghese G M, Janardhanan J, Ralph R and Abraham O C 2013 Curr. Infect. Dis. Rep. 15 77CrossRefGoogle Scholar
  5. 5.
    Mdluli K, Kaneko T and Upton A 2015 Cold Spring Harb. Perspect. Med. doi: 10.1101/cshperspect.a021154
  6. 6.
    Kandel D D, Raychaudhury C and Pal D 2014 J. Mol. Model. 20 2164CrossRefGoogle Scholar
  7. 7.
    Raychaudhury C, Kandel D D and Pal D 2014 Croat. Chem. Acta 87 39CrossRefGoogle Scholar
  8. 8.
    Lamichhane G 2011 Trends Mol. Med. 17 25CrossRefGoogle Scholar
  9. 9.
    Choudhury C, Priyakumar U D and Sastry G N 2014 J. Struct. Biol. 187 38CrossRefGoogle Scholar
  10. 10.
    Choudhury C, Priyakumar U D and Sastry G N J. Chem. Inf. Model. 55 848Google Scholar
  11. 11.
    Wishart D S, Knox C, Guo A C, Shrivastava S, Hassanali M, Stothard P, Chang Z and Woolsey J 2006 Nucleic Acids Res. 34 D668CrossRefGoogle Scholar
  12. 12.
    Tobinick E L 2009 Drug News Perspect. 22 119CrossRefGoogle Scholar
  13. 13.
    Bohari M H and Sastry G N 2012 J. Mol. Model. 18 4263CrossRefGoogle Scholar
  14. 14.
    Bento A P, Gaulton A, Hersey A, Bellis L J, Chambers J, Davies M, Krüger F A, Light Y, Mak L, McGlinchey S, Nowotka M, Papadatos G, Santos R and Overington J P 2014 Nucleic Acids Res. 42 D1083CrossRefGoogle Scholar
  15. 15.
    Kinnings S L, Liu N, Buchmeier N, Tonge P J, Xie L and Bourne P. 2009 PLoS Comput. Biol. 5 e1000423CrossRefGoogle Scholar
  16. 16.
    Carlson H A, Masukawa K M, Rubins K, Bushman F D, Jorgensen W L, Lins R D, Briggs J M and McCammon J A 2000 J. Med. Chem. 43 2100CrossRefGoogle Scholar
  17. 17.
    Meagher K L and Carlson H A 2004 J. Am. Chem. Soc. 126 13276CrossRefGoogle Scholar
  18. 18.
    Meagher K L and Carlson H A 2005 Proteins Struct. Funct. Bioinf. 58 119CrossRefGoogle Scholar
  19. 19.
    Damm K L and Carlson H A 2007 J. Am. Chem. Soc. 129 8225CrossRefGoogle Scholar
  20. 20.
    Kitchen D B, Decornez H, Furr J R and Bajorath J 2004 Nat. Rev. Drug Discov. 3 935CrossRefGoogle Scholar
  21. 21.
    Kubinyi H 1997 Drug Discov. Today 2 457CrossRefGoogle Scholar
  22. 22.
    Srivastava H K and Sastry G N 2012 J. Chem. Inf. Model. 52 3088CrossRefGoogle Scholar
  23. 23.
    Carlson H A 2002 Curr. Opin. Chem. Biol. 6 447CrossRefGoogle Scholar
  24. 24.
    Srivastava H K, Choudhury C and Sastry G N 2012 Med. Chem. 8 811CrossRefGoogle Scholar
  25. 25.
    Badrinarayan P and Sastry G N 2011 Comb. Chem. High Thr. Scr. 14 840CrossRefGoogle Scholar
  26. 26.
    Badrinarayan P and Sastry G N 2012 J. Mol. Graph. Modell. 34 89CrossRefGoogle Scholar
  27. 27.
    Badrinarayan P and Sastry G N 2014 PLoS One 9 e113773CrossRefGoogle Scholar
  28. 28.
    Reddy A S, Pati S P, Kumar P P, Pradeep H N and Sastry G N 2007 Curr. Protein Pept. Sci. 8 329CrossRefGoogle Scholar
  29. 29.
    Badrinarayan P and Sastry G N 2013 Curr. Pharm. Des. 19 4714CrossRefGoogle Scholar
  30. 30.
    Selick H E, Beresford A P and Tarbit M H 2002 Drug Discov. Today 7 109CrossRefGoogle Scholar
  31. 31.
    Kubinyi H 2003 Nat. Rev. Drug Discov. 2 665CrossRefGoogle Scholar
  32. 32.
    de Waterbeemd H V and Gifford E 2003 Nat. Rev. Drug Discov. 2 192CrossRefGoogle Scholar
  33. 33.
    Oprea T I, Davis A M, Teague S J and Leeson P D 2001 J. Chem. Inf. Comput. Sci. 41 1308CrossRefGoogle Scholar
  34. 34.
    Schrödinger Release 2015-4: Maestro, version 10.4, 2015, Schrödinger, LLC, New York, NYGoogle Scholar
  35. 35.
    Dixon S L, Smondyrev A M, Knoll E H, Rao S N, Shaw D E and Friesner R A 2006 J. Comput. Aided. Mol. Des. 20 647CrossRefGoogle Scholar
  36. 36.
    Anuradha A, Trivelli X, Guérardel Y, Dover L G, Besra G S, Sacchettini J C, Reynolds R C, Coxon G D and Kremer L 2007 PLoS One 12 e1343Google Scholar
  37. 37.
    LigPrep, version, 2.5 2012 Schrödinger, LLC, New York, NYGoogle Scholar
  38. 38.
    Glide, version, 5.8 2012, Schrödinger, LLC, New York, NYGoogle Scholar
  39. 39.
    Friesner R A, Murphy R B, Repasky M P, Frye L L, Greenwood J R, Halgren T A, Sanschagrin P C and Mainz D T 2006 J. Med. Chem. 49 6177CrossRefGoogle Scholar
  40. 40.
    QikProp version 3.5 2012, Schrödinger, LLC, New York, NYGoogle Scholar
  41. 41.
    Yang S Y 2010 Drug Discov. Today 15 444CrossRefGoogle Scholar
  42. 42.
    Saha S and Sastry G N 2015 J. Phys. Chem. B 119 11121CrossRefGoogle Scholar
  43. 43.
    Mahadevi A S and Sastry G N 2013 Chem. Rev. 113 2100CrossRefGoogle Scholar
  44. 44.
    Alhamadsheh M M, Waters N C, Sachdeva S, Lee P and Reynolds K A 2008 Bioorg. Med. Chem. Lett. 18 6402CrossRefGoogle Scholar
  45. 45.
    Guüzel Ö, Maresca A, Scozzafava A, Salman A, Balaban A T and Supuran C T 2009 J. Med. Chem. 52 4063CrossRefGoogle Scholar
  46. 46.
    Shu-Feng Z, Wang L, Di Y M, Xue C C, Duan W, Li C G and Li Y 2008 Curr. Med. Chem. 15 1981CrossRefGoogle Scholar
  47. 47.
    Fardis M, Jin H, Jabri S, Cai R Z, Mish M, Tsiang M and Kim C U 2006 Bioorg. Med. Chem. Lett. 16 4031CrossRefGoogle Scholar
  48. 48.
    Artico M, Santo R D, Costi R, Novellino E, Greco G, Massa S, Tramontano E, Marongiu M E, Montis A D and Colla P L 1998 J. Med. Chem. 41 3948CrossRefGoogle Scholar
  49. 49.
    Maurin C, Lion C, Bailly F, Touati N, Vezin H, Mbemba G, Mouscadet J F, Debyser Z, Witvrouw M and Cotelle P 2010 Bioorg. Med. Chem. 18 5194CrossRefGoogle Scholar
  50. 50.
    Porcari A R, Ptak R G, Borysko K Z, Breitenbach J M, Drach J C and Townsend L B 2000 J. Med. Chem. 43 2457CrossRefGoogle Scholar

Copyright information

© Indian Academy of Sciences 2016

Authors and Affiliations

    • 1
    • 2
    • 2
    Email author
    • 1
  1. 1.Centre for Molecular ModellingIndian Institute of Chemical TechnologyHyderabadIndia
  2. 2.Centre for Computational Natural Sciences and BioinformaticsInternational Institute of Information and TechnologyHyderabadIndia

Personalised recommendations