Comparative QSAR Analysis of 3,5-bis (Arylidene)-4-Piperidone Derivatives: the Development of Predictive Cytotoxicity Models

Authors

  • Bahram Hemateenejad Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz 71345, Iran
  • Jonathan R. Dimmock Drug Design and Discovery Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, 110 Science Place, Saskatoon, Saskatchewan S7N 5C9, Canada
  • Najmeh Edraki Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz 71345, Iran
  • ramin miri 1) Faculty of Pharmacy, Shiraz University of Medical Sciences, P. O. Box: 71145-1149, Shiraz, IRAN 2) Medicinal & Natural Products Chemistry Research Center, Shiraz University of Medical Sciences,
  • Umashankar Das Drug Design and Discovery Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, 110 Science Place, Saskatoon, Saskatchewan S7N 5C9, Canada
Abstract:

1-[4-(2-Alkylaminoethoxy)phenylcarbonyl]-3,5-bis(arylidene)-4-piperidones are a novel class of potent cytotoxic agents. These compounds demonstrate low micromolar to submicromolar IC50 values against human Molt 4/C8 and CEM T-lymphocytes and murine leukemia L1210 cells. In this study, a comparative QSAR investigation was performed on a series of 3,5-bis(arylidene)-4-piperidones using different chemometric tools to develop the best predictive models for further development of analogs with improved cytotoxicity. All the QSAR models were validated by internal validation tests. The QSAR models obtained by GA-PLS method were considered the best as compared to MLR method. The best QSAR model obtained by GA-PLS analysis on L1210, CEM and Molt4/C8 demonstrated good predictively with R2pred values ranging from 0.94-0.80. Molecular density, topological (X2A) and geometrical indices of the molecules were found to be the most important factors for determining cytotoxic properties.

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comparative qsar analysis of 3,5-bis (arylidene)-4-piperidone derivatives: the development of predictive cytotoxicity models

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Journal title

volume 15  issue 2

pages  425- 437

publication date 2016-06-01

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