Medicinal Chemistry Research

, Volume 23, Issue 10, pp 4464–4481 | Cite as

Screening of potent antibacterial agents targeting Clostridium difficile virulence factor toxin B: an in silico approach

  • Vijayalakshmi Ezhilarasan
  • Ankush Jadhav
  • Archana Pan
Original Research


Toxin B is the key determinant of virulence in Clostridium difficile. Cysteine protease domain (CPD) of toxin B plays a crucial role in host cell intoxication thereby making it a potential target for drug discovery. The present study is aimed at identifying the promising lead compounds targeting C. difficile toxin B CPD. Initial screening of the compounds was done using topomer search and drug-likeness properties. The subsequent molecular docking study yielded a set of lead compounds having better docking score and binding mode of interactions compared to the known inhibitor. Molecular dynamics simulations were performed to explore the stability of protein–ligand complexes. The identified promising lead molecules can be used for the development of therapeutics targeting C. difficile toxin B.

Graphical Abstract

Large scale screening protocol for identification of novel promising lead candidates against virulence factor (toxin B) of Clostridium difficile.


Human pathogen Therapeutic target Topomer search Drug-likeness Docking MD simulation 



The author V.E. is grateful to Pondicherry University, India, for the pre-doctoral fellowship and A.J. is thankful to the University Grant Commission (UGC), New Delhi, Govt. of India, for providing research fellowship. Authors are grateful to A. Murali, Pondicherry University, Pondicherry, India and Aditya Sharma, Department of Genetics, University of Delhi, South Campus, New Delhi, India for critical reading of the manuscript and providing valuable suggestions. Authors are also thankful to Kannan M., Pondicherry University, Pondicherry, for his valuable suggestions to analysis ‘conformational changes in protein during MD simulation’.

Supplementary material

44_2014_1017_MOESM1_ESM.pdf (1.7 mb)
Fig. S1Chemical structural information of all 475 screened potential lead compounds. (PDF 1700 kb)
44_2014_1017_MOESM2_ESM.pdf (1.2 mb)
Fig. S2Chemical structure, 3D and 2D docking interactions of all 31 identified lead compounds in the active site of toxin B CPD. (PDF 1217 kb)
44_2014_1017_MOESM3_ESM.tif (9.9 mb)
Fig. S3Superimposition of all 31 identified promising lead compounds and reference inhibitor into the active site of toxin B CPD. Protein is shown in surface and ligand in stick representation with pink and element colour code, respectively. (TIFF 10088 kb)
44_2014_1017_MOESM4_ESM.tif (3.7 mb)
Fig. S4Final conformation of the binding site of four lead compounds, namely Akos_505 (1), Ambinter_1332 (2), Biocyc_473 (3), DrugBank_89 (4) and reference inhibitor (5) after 25 ns of molecular dynamics simulation. Respective 2D interactions are shown in the right panel. (TIFF 3789 kb)
44_2014_1017_MOESM5_ESM.tif (140 kb)
Fig. S5The three dimensional structure of toxin B CPD with the structural components of active site (α2-Helix, β10-strand and loops) (TIFF 141 kb)
44_2014_1017_MOESM6_ESM.jpg (194 kb)
Fig. S6Conformational changes of β10-strand at each 1 ns interval up to 25 ns during MD simulation for Akos-505 (a), Ambinter-1332 (JPEG 195 kb)
44_2014_1017_MOESM7_ESM.jpg (189 kb)
Fig. S6Conformational changes of β10-strand at each 1 ns interval up to 25 ns during MD simulation for Akos-505 (b), Biocyc-473 (JPEG 189 kb)
44_2014_1017_MOESM8_ESM.jpg (93 kb)
Fig. S6Conformational changes of β10-strand at each 1 ns interval up to 25 ns during MD simulation for Akos-505 (c), DrugBank-89 (JPEG 94 kb)
44_2014_1017_MOESM9_ESM.jpg (199 kb)
Fig. S6Conformational changes of β10-strand at each 1 ns interval up to 25 ns during MD simulation for Akos-505 (d) and reference inhibitor (e). (JPEG 199 kb)
44_2014_1017_MOESM10_ESM.tif (2.2 mb)
Fig. S7Backbone Hydrogen bonds between β10 and β11-strand. Both strands and ligand are shown in stick representation with brown and cyan colour, respectively, whereas hydrogen bond is shown in red dotted lines. (TIFF 2270 kb)
44_2014_1017_MOESM11_ESM.tif (354 kb)
Fig. S8Area and volume of the toxin B CPD active site are shown in the column chart. Blue and red colour represents before and after simulation, respectively (TIFF 354 kb)
44_2014_1017_MOESM12_ESM.tif (2.3 mb)
Fig. S9U shaped ligand orientation of Akos-505 (a), Ambinter-1332 (b), Biocyc-473 (c), DrugBank-89 (d) and reference inhibitor (e) formed during the period of simulation (TIFF 2306 kb)
44_2014_1017_MOESM13_ESM.pdf (840 kb)
Table S1Screened 475 potential lead compounds and reference inhibitor with their compound ID, G_score and G_energy and different QikProp descriptors (PDF 841 kb)


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Vijayalakshmi Ezhilarasan
    • 1
  • Ankush Jadhav
    • 1
  • Archana Pan
    • 1
  1. 1.Centre for Bioinformatics, School of Life SciencesPondicherry UniversityPondicherryIndia

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