Future Journal of Pharmaceutical Sciences (Dec 2017)

Combretastatin A-4 based thiophene derivatives as antitumor agent: Development of structure activity correlation model using 3D-QSAR, pharmacophore and docking studies

  • Vijay K. Patel,
  • Avineesh Singh,
  • Deepak K. Jain,
  • Preeti Patel,
  • Ravichandran Veerasamy,
  • Prabodh C. Sharma,
  • Harish Rajak

DOI
https://doi.org/10.1016/j.fjps.2017.03.003
Journal volume & issue
Vol. 3, no. 2
pp. 71 – 78

Abstract

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The structure and ligand based synergistic approach is being applied to design ligands more correctly. The present report discloses the combination of structure and ligand based tactics i.e., molecular docking, energetic based pharmacophore, pharmacophore and atom based 3D-QSAR modeling for the analysis of thiophene derivatives as anticancer agent. The main purpose of using structure and ligand based synergistic approach is to ascertain a correlation between structure and its biological activity. Thiophene derivatives have been found to possess cytotoxic activity in several cancer cell lines and its mechanism of action basically involves the binding to the colchicine site on β-tubulin. The structure based approach (molecular docking) was performed on a series of thiophene derivatives. All the structures were docked to colchicine binding site of β tubulin for examining the binding affinity of compounds for antitumor activity. The pharmacophore and atom based 3D-QSAR modeling was accomplished on a series of thiophene (32 compounds) analogues. Five-point common pharmacophore hypotheses (AAAAR.38) were selected for alignment of all compounds. The atom based 3D-QSAR models were developed by selection of 23 compounds as training set and 9 compounds as test set, demonstrated good partial least squares statistical results. The generated common pharmacophore hypothesis and 3D-QSAR models were validated further externally by measuring the activity of database compounds and assessing it with actual activity. The common pharmacophore hypothesis AAAAR.38 resulted in a 3D-QSAR model with excellent PLSs data for factor two characterized by the best predication coefficient Q2 (cross validated r2) (0.7213), regression R2 (0.8311), SD (0.3672), F (49.2), P (1.89E-08), RMSE (0.3864), Stability (0.8702), Pearson-r (0.8722). The results of these molecular modeling studies i.e., molecular docking, energetic based pharmacophore, pharmacophore and atom based 3D-QSAR modeling would be fruitful to improve the pharmacophore for design of novel combretastatin A-4 based thiophenes for anticancer activity.

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