Journal: Journal of Pharmacy Research

Article Id: JPRS-PC-0000108
Title: Artemisinin analogues selection in linear and non-linear QSAR
Category: Pharmaceutical Chemistry
Section: Research Article
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    Artificial neural networks (ANNs) and multiple linear regressions (MLR) controlled non-linear and linear quantitative structure activity relationship (QSAR) models were established for a set of (32) Artemisinin derivative (ART). QSAR models derived from MLR and ANN yielded appreciable internal and external predictability. Using the pertinent descriptors calculate from this study that the activity dependent especially on substituent R and hydrogen liaison du substituent R2 by different descriptors coding for same structural properties and energies and associated properties of the molecules are identified and discussed as overlapping structure features in linear and non-linear QSAR models. The independent variables selected in relation with concentration of 50% inhibition are BHA(R), W(R), and WM (R2), processed by leave one-out cross validation and Y-scrambling technique. The test set (N=6) presented an external prediction power of 94%: In conclusion these overlapping features may reveal fundamental structural properties which convert a linear relationship to non-linear and better identifications of bio-chemical aspects of QSAR models to medicinal chemists.

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    Author(s) Name:

    M. Lazar1*, A. Mouzdahir, 2 M. Badia3 and M. Zahouily1

    Affiliation(s) Name:


    1Department of chemistry, Laboratory of Materials, catalysis and development of natural resources (URAC24) University of Hassan II–Mohammedia, Faculty of sciences and Technologies. B.P.146 (20650) Mohammedia, Morocco.
    2Department of chemistry, Laboratory of Bioorganic Chemistry University of Chouaïb Doukkali, Faculty of Sciences El Jadida.: Road Ben Maâchou B.P.: 20, (24000), El Jadida, Morocco.
    3Ecole Royale de l’air, Marrakech, Morocco. Mechanic of Department,3Ecole Royale de l’air, Marrakech, Morocco. Mechanic of Department, ERA, BEFRA Marrakech 4000, Morocco.

    *Corresponding author.
    M. Lazar
    Department of chemistry,
    Laboratory of Materials,
    catalysis and development of natural resources (URAC24) University of Hassan II–Mohammedia, Faculty of sciences and Technologies. B.P.146 (20650) Mohammedia, Morocco.
    E-mail: mo_lazar@yahoo.fr


    Received on:07-11-2013; Revised on: 26-12-2013; Accepted on:11-12-2013

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    Author:

    M. Lazar1*, A. Mouzdahir, 2 M. Badia3 and M. Zahouily1

    Title:Artemisinin analogues selection in linear and non-linear QSAR
    Journal:Journal of Pharmacy Research
    Vol(issue):8 (February)
    Year:2014
    Page No: (118-122)
  • Experimental Methods Keywords

    Methodology:Multiple Linear Regression
    Research Materials:Artemisinin derivatives

Keywords

Artemisinin derivatives Multiple Linear Regression Structure-Activity Relationships Artificial Neural Network.

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