Journal of Computer-Aided Molecular Design

, Volume 25, Issue 4, pp 349–369 | Cite as

Docking and quantitative structure–activity relationship studies for 3-fluoro-4-(pyrrolo[2,1-f][1,2,4]triazin-4-yloxy)aniline, 3-fluoro-4-(1H-pyrrolo[2,3-b]pyridin-4-yloxy)aniline, and 4-(4-amino-2-fluorophenoxy)-2-pyridinylamine derivatives as c-Met kinase inhibitors

  • Julio CaballeroEmail author
  • Miguel Quiliano
  • Jans H. Alzate-Morales
  • Mirko Zimic
  • Eric Deharo


We have performed docking of 3-fluoro-4-(pyrrolo[2,1-f][1,2,4]triazin-4-yloxy)aniline (FPTA), 3-fluoro-4-(1H-pyrrolo[2,3-b]pyridin-4-yloxy)aniline (FPPA), and 4-(4-amino-2-fluorophenoxy)-2-pyridinylamine (AFPP) derivatives complexed with c-Met kinase to study the orientations and preferred active conformations of these inhibitors. The study was conducted on a selected set of 103 compounds with variations both in structure and activity. Docking helped to analyze the molecular features which contribute to a high inhibitory activity for the studied compounds. In addition, the predicted biological activities of the c-Met kinase inhibitors, measured as IC50 values were obtained by using quantitative structure–activity relationship (QSAR) methods: Comparative molecular similarity analysis (CoMSIA) and multiple linear regression (MLR) with topological vectors. The best CoMSIA model included steric, electrostatic, hydrophobic, and hydrogen bond-donor fields; furthermore, we found a predictive model containing 2D-autocorrelation descriptors, GETAWAY descriptors (GETAWAY: Geometry, Topology and Atom-Weight AssemblY), fragment-based polar surface area (PSA), and MlogP. The statistical parameters: cross-validate correlation coefficient and the fitted correlation coefficient, validated the quality of the obtained predictive models for 76 compounds. Additionally, these models predicted adequately 25 compounds that were not included in the training set.


c-Met kinase inhibitors Molecular docking Quantitative structure–activity relationships CoMSIA Topological descriptors 



J.C. thanks “Becas Universidad de Talca” for financial support through a doctoral fellowship. M.Q. and E.D. gratefully acknowledge the Institut de Recherche pour le Développement (UMR 152 IRD-UPS) for financial support. J.H.A.M. acknowledges the financial support through project FONDECYT No 11100177.

Supplementary material

10822_2011_9425_MOESM1_ESM.doc (3.3 mb)
Supplementary material 1 (DOC 3396 kb)


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Julio Caballero
    • 1
    Email author
  • Miguel Quiliano
    • 2
  • Jans H. Alzate-Morales
    • 1
  • Mirko Zimic
    • 2
  • Eric Deharo
    • 3
    • 4
  1. 1.Centro de Bioinformática y Simulación Molecular, Facultad de Ingeniería en BioinformáticaUniversidad de TalcaTalcaChile
  2. 2.Bioinformatics Unit-Drug Design Group, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y FilosofíaUniversidad Peruana Cayetano HerediaLimaPerú
  3. 3.UPS, UMR 152 (Laboratoire de Pharmacochimie des Substances Naturelles et Pharmacophores Redox)Université de ToulouseToulouse cedex 9France
  4. 4.IRD; UMR-152LimaPerú

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