Journal of Computer-Aided Molecular Design

, Volume 25, Issue 3, pp 263–274 | Cite as

Structure-guided fragment-based in silico drug design of dengue protease inhibitors

  • Tim Knehans
  • Andreas Schüller
  • Danny N. Doan
  • Kassoum Nacro
  • Jeffrey Hill
  • Peter Güntert
  • M. S. Madhusudhan
  • Tanja Weil
  • Subhash G. Vasudevan


An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC50 = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC50 = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.


Dengue virus NS2B-NS3 protease West Nile virus Protease inhibitor Fragment-based drug design (FBDD) Homology modeling 



We are grateful to Mr. Kok Soon Lai and Ms. Si Fang Wang for expert technical assistance. The National Cancer Institute is thanked for providing three compounds free of charge. Funding was provided by Duke-NUS Signature Research Program (funded by the Agency for Science, Technology and Research, Singapore and the Ministry of Health, Singapore) as a startup grant to SV.

Supplementary material

10822_2011_9418_MOESM1_ESM.pdf (198 kb)
Supplementary material 1 (PDF 198 kb)


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Tim Knehans
    • 1
    • 2
  • Andreas Schüller
    • 2
  • Danny N. Doan
    • 2
  • Kassoum Nacro
    • 3
  • Jeffrey Hill
    • 3
  • Peter Güntert
    • 1
  • M. S. Madhusudhan
    • 4
  • Tanja Weil
    • 5
  • Subhash G. Vasudevan
    • 2
  1. 1.Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance and Frankfurt Institute for Advanced StudiesJ.W. Goethe-UniversityFrankfurt am MainGermany
  2. 2.Program in Emerging Infectious DiseasesDuke-NUS Graduate Medical SchoolSingaporeSingapore
  3. 3.Experimental Therapeutic CentreAgency for Science, Technology and Research (A*STAR)SingaporeSingapore
  4. 4.Bioinformatics InstituteAgency for Science, Technology and Research (A*STAR)SingaporeSingapore
  5. 5.Institute of Organic Chemistry III/Macromolecular ChemistryUniversity of UlmUlmGermany

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