Molecular Diversity

, Volume 19, Issue 4, pp 855–870 | Cite as

In silico identification of targets for a novel scaffold, 2-thiazolylimino-5-benzylidin-thiazolidin-4-one

  • Poornima Iyer
  • Jahnavi Bolla
  • Vivek Kumar
  • Manjinder Singh Gill
  • M. Elizabeth SobhiaEmail author
Full-Length Paper


Thiazolidinone derivatives have been found to exhibit a wide range of pharmacological activities. 2-Thiazolylimino-5-benzylidene-thiazolidin-4-one derivatives show antibacterial activity in in vitro tests which are comparable to marketed drugs. However, the target for this scaffold remains yet to be identified. In our work, we identified seven putative targets for this scaffold using web servers such as DRAR-CPI, PharmMapper, and TarFisDock and databases such as BindingDB and ChEMBL. Each of these servers used different algorithms and scoring functions for protein target identification. Further, these targets are substantiated by molecular docking analysis. Based on the docking studies, scaffold 2-thiazolylimino-5-benzylidene-thiazolidin-4-one is observed to exhibit affinity against diverse targets, particularly, towards COX-2, acetylcholinesterase, aldose reductase, and thyroid hormone receptor alpha. This study describes an initial probability that these proteins may be targeted by this scaffold.


BindingDB DRAR-CPI PharmMapper TarFisDock  vROCS 

Supplementary material

11030_2015_9578_MOESM1_ESM.tif (48 kb)
Fig. (S1). Slanted cladogram of the aligned protein sequences (TIFF 48 KB)
11030_2015_9578_MOESM2_ESM.tif (138 kb)
Fig. (S2). Top Hits from Specs Database Screening along with their Tanimoto Combo values* (TIFF 138 KB)
11030_2015_9578_MOESM3_ESM.tif (1.3 mb)
Fig. (S3). Superposition of ligand from 2FPT (gray) on the query green) (TIFF 1,376 KB)
11030_2015_9578_MOESM4_ESM.doc (258 kb)
Fig. (S4). Multiple sequence alignment of proteins 2H77, 3DCT, and 3K8S using ClustalX. The active-site residues are represented in box (doc 258 KB)
11030_2015_9578_MOESM5_ESM.doc (100 kb)
Fig. (S5). Thiazole Series of Compounds (doc 100 KB)
11030_2015_9578_MOESM6_ESM.doc (56 kb)
Fig. (S6). Benzothiazole Series of Compounds (doc 56 KB)
11030_2015_9578_MOESM7_ESM.doc (320 kb)
Fig. (S7). Structures of core moieties present in (a) Thiazole series and (b) Benzothiazole series of compounds (doc 320 KB)
11030_2015_9578_MOESM8_ESM.doc (36 kb)
Table S1. Targets from TarFisDock (doc 37 KB)
11030_2015_9578_MOESM9_ESM.doc (37 kb)
Table S2. Targets from DRAR-CPI (doc 37 KB)
11030_2015_9578_MOESM10_ESM.doc (42 kb)
Table S3. Targets from PharmMapper (doc 42 KB)
11030_2015_9578_MOESM11_ESM.doc (40 kb)
Table S4. Targets selected from different servers based on druggability (doc 40 KB)


  1. 1.
    Rao VS, Srinivas K (2011) Modern drug discovery process: an in silico approach. J Bioinform Seq Anal 2:89–94. doi: 10.5897/JBSA Google Scholar
  2. 2.
    Tang Y, Zhu W, Chen K, Jiang H (2006) New technologies in computer-aided drug design: toward target identification and new chemical entity discovery. Drug Discov Today Technol 3:307–313. doi: 10.1016/j.ddtec.2006.09.004 CrossRefPubMedGoogle Scholar
  3. 3.
    Lindsay MA (2003) Target discovery. Nat Rev Drug Discov 2:831–838. doi: 10.1038/nrd1202 CrossRefPubMedGoogle Scholar
  4. 4.
    Jenkins JL, Bender A, Davies JW (2007) In silico target fishing: predicting biological targets from chemical structure. Drug Discov Today Technol 3:413–421. doi: 10.1016/j.ddtec.2006.12.008 CrossRefGoogle Scholar
  5. 5.
    Zhou H, Wu S, Zhai S, Liu A, Sun Y, Li R, Zhang Y, Ekins S, Swaan PW, Fang B (2008) Design, synthesis, cytoselective toxicity, structure-activity relationships, and pharmacophore of thiazolidinone derivatives targeting drug-resistant lung cancer cells. J Med Chem 51:1242–1251. doi: 10.1021/jm7012024 CrossRefPubMedGoogle Scholar
  6. 6.
    Vicini P, Geronikaki A, Anastasia K, Incerti M, Zani F (2006) Synthesis and antimicrobial activity of novel 2-thiazolylimino-5-arylidene-4-thiazolidinones. Bioorg Med Chem 14:3859–3864. doi: 10.1016/j.bmc.2006.01.043 CrossRefPubMedGoogle Scholar
  7. 7.
    Vicini P, Geronikaki A, Incerti M, Zani F, Dearden J, Hewitt M (2008) 2-Heteroarylimino-5-benzylidene-4-thiazolidinones analogues of 2-thiazolylimino-5-benzylidene-4-thiazolidinones with antimicrobial activity: Synthesis and structure-activity relationship. Bioorg Med Chem 16:3714–3724. doi: 10.1016/j.bmc.2008.02.001 CrossRefPubMedGoogle Scholar
  8. 8.
    Verma A, Saraf SK (2008) 4-Thiazolidinone-A biologically active scaffold. Eur J Med Chem 43:897–905. doi: 10.1016/j.ejmech.2007.07.017 CrossRefPubMedGoogle Scholar
  9. 9.
    Abhinit M, Ghodke M, Pratima NA (2009) Exploring potential of 4-thiazolidinone: a brief review. Int J Pharm Pharm Sci 1:47–64Google Scholar
  10. 10.
    Li H, Gao Z, Kang L, Zhang H, Yang K, Yu K, Luo X, Zhu W, Chen K, Shen J (2006) TarFisDock: a web server for identifying drug targets with docking approach. Nucleic Acids Res 34:W219–W224. doi: 10.1093/nar/gkl114 PubMedCentralCrossRefPubMedGoogle Scholar
  11. 11.
    Gao Z, Li H, Zhang H, Liu X, Kang L, Luo X, Zhu W, Chen K, Wang X, Jiang H (2008) PDTD: a web-accessible protein database for drug target identification. BMC Bioinform 9:104. doi: 10.1186/1471-2105-9-104 CrossRefGoogle Scholar
  12. 12.
    Luo H, Chen J, Shi L, Mikailov M, Zhu H, Wang K, He L, Yang L (2011) DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical-protein interactome. Nucleic Acids Res 39:W492–W498. doi: 10.1093/nar/gkr299 PubMedCentralCrossRefPubMedGoogle Scholar
  13. 13.
    Liu X, Ouyang S, Yu B, Liu Y, Huang K, Gong J, Zheng S, Li Z, Li H, Jiang H (2010) PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach. Nucleic Acids Res 38:W609–W614. doi: 10.1093/nar/gkq300 PubMedCentralCrossRefPubMedGoogle Scholar
  14. 14.
    Geronikaki A, Eleftheriou P, Vicini P, Alam I, Dixit A, Saxena AK (2008) 2-Thiazolylimino/heteroarylimino-5-arylidene-4-thiazolidinones as new agents with SHP-2 inhibitory action. J Med Chem 51:5221–5228. doi: 10.1021/jm8004306 CrossRefPubMedGoogle Scholar
  15. 15.
    Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A, Light Y, McGlinchey S, Michalovich D, Al-Lazikani B (2012) ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res 40:D1100–D1107. doi: 10.1093/nar/gkr777 PubMedCentralCrossRefPubMedGoogle Scholar
  16. 16.
    Eleftheriou P, Geronikaki A, Hadjipavlou-Litina D, Vicini P, Filz O, Filimonov D, Poroikov V, Chaudhaery SS, Roy KK, Saxena A (2011) Fragment-based design, docking, synthesis, biological evaluation and structure-activity relationships 2-benzo/benzisothiazolimino-5-aryliden-4-thiazolidinones as cycloxygenase/ lipoxygenase inhibitors. Eur J Med Chem 47:111–124. doi: 10.1016/j.ejmech.2011.10.029 CrossRefPubMedGoogle Scholar
  17. 17.
    Geronikaki AA, Lagunin AA, Hadjipavlou-Litina DI, Eleftheriou PT, Filimonov DA, Poroikov VV, Alam I, Saxena AK (2008) Computer-aided discovery of anti-inflammatory thiazolidinones with dual cyclooxygenase/ lipoxygenase inhibition. J Med Chem 51:1601–1609. doi: 10.1021/jm701496h CrossRefPubMedGoogle Scholar
  18. 18.
    Maestro, Version 9.0 (2009) Schrödinger, LLC, New YorkGoogle Scholar
  19. 19.
    Glide, Version 5.5 (2009) Schrödinger, LLC, New YorkGoogle Scholar
  20. 20.
    Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Daniel T, Repasky MP, Knoll EH, Shelley M, Perry JK (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
  21. 21.
    Verdonk ML, Cole JC, Hartshorn MJ, Murray CW, Taylor RD (2003) Improved protein-ligand docking using GOLD. Proteins Struct Funct Bioinform 52:609–623. doi: 10.1002/prot.10465 CrossRefGoogle Scholar
  22. 22.
    DeLano WL (2001) Pymol: an open source molecular graphics. CCP4 Newsl On Protein Crystallogr 40:82–92Google Scholar
  23. 23.
    Laurie ATR, Jackson RM (2005) Q-SiteFinder: an energy-based method for the prediction of protein—ligand binding sites. Bioinformatics 21:1908–1916. doi: 10.1093/bioinformatics/bti315 CrossRefPubMedGoogle Scholar
  24. 24.
    ROCS, Version 3.0.0 (2009) OpenEye Scientific Software, Santa Fe, NMGoogle Scholar
  25. 25.
    Fontaine F, Bolton E, Borodina Y, Bryant SH (2007) Fast 3D shape screening of large chemical databases through alignment-recycling. Chem Cent J 1:1–14. doi: 10.1186/1752-153X-1-12 CrossRefGoogle Scholar
  26. 26.
    Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R (2007) Clustal W and clustal X version 2.0. Bioinformatics 23:2947–2948. doi: 10.1093/bioinformatics/btm404 CrossRefPubMedGoogle Scholar
  27. 27.
    Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The CLUSTAL\_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25:4876–4882. doi: 10.1093/nar/25.24.4876 PubMedCentralCrossRefPubMedGoogle Scholar
  28. 28.
    Kotera M, McDonald AG, Boyce S, Tipton KF (2008) Functional group and substructure searching as a tool in metabolomics. PLoS ONE 3:e1537. doi: 10.1371/journal.pone.0001537 PubMedCentralCrossRefPubMedGoogle Scholar
  29. 29.
    Stobaugh RE (1985) Chemical substructure searching. J Chem Inf Comput Sci 25:271–275. doi: 10.1021/ci00047a025 CrossRefGoogle Scholar
  30. 30.
    Keller TH, Pichota A, Yin Z (2006) A practical view of ‘druggability’. Curr Opin Chem Biol 10:357–361. doi: 10.1016/j.cbpa.2006.06.014 CrossRefPubMedGoogle Scholar
  31. 31.
    LigPrep, Version 2.3 (2009) Schrödinger, LLC, New YorkGoogle Scholar
  32. 32.
    QikProp, Version, 3.2 (2009) Schrödinger, LLC, New YorkGoogle Scholar
  33. 33.
    Chen XP, Du GH (2007) Target validation: a door to drug discovery. Drug Discov Ther 1:23–29PubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Poornima Iyer
    • 1
  • Jahnavi Bolla
    • 1
  • Vivek Kumar
    • 1
  • Manjinder Singh Gill
    • 2
  • M. Elizabeth Sobhia
    • 1
    Email author
  1. 1.Department of PharmacoinformaticsNational Institute of Pharmaceutical Education and ResearchMohaliIndia
  2. 2.Department of Pharmaceutical Technology – Process ChemistryNational Institute of Pharmaceutical Education and ResearchMohaliIndia

Personalised recommendations