Abstract
The emergence of multidrug resistance of the currently available antimalarial drugs has led to the need of the discovery and development of new antimalarial compounds. In the present study, we have used a novel group based quantitative structure-activity relationship (G-QSAR) approach, which allows to establish a correlation of chemical group variation at different molecular sites of interest with the biological activity, using a series of 53 antimalarial endochin analogs. In our previous work, we developed QSAR models for this data set using different chemometric tools and tried to emphasize on importance of descriptor thinning and noise reduction prior to feature selection step. In the present paper, we have tried to select optimal subset of variables using a new strategy for the development of robust G-QSAR models. Starting with an initial pool of 6395 descriptors, we have finally used 51 descriptors for model development using genetic methods. The best model showed encouraging values for internal.....
Keywords: Antimalarials, Endochin, GFA, G/PLS, G-QSAR, QSAR, TM-90-C2B.
Current Computer-Aided Drug Design
Title:Exploration of Important Sites of Antimalarial Endochins for Optimum Structural Modification Using Group-Based QSAR (G-QSAR) Modeling
Volume: 9 Issue: 3
Author(s): Probir Kumar Ojha and Kunal Roy
Affiliation:
Keywords: Antimalarials, Endochin, GFA, G/PLS, G-QSAR, QSAR, TM-90-C2B.
Abstract: The emergence of multidrug resistance of the currently available antimalarial drugs has led to the need of the discovery and development of new antimalarial compounds. In the present study, we have used a novel group based quantitative structure-activity relationship (G-QSAR) approach, which allows to establish a correlation of chemical group variation at different molecular sites of interest with the biological activity, using a series of 53 antimalarial endochin analogs. In our previous work, we developed QSAR models for this data set using different chemometric tools and tried to emphasize on importance of descriptor thinning and noise reduction prior to feature selection step. In the present paper, we have tried to select optimal subset of variables using a new strategy for the development of robust G-QSAR models. Starting with an initial pool of 6395 descriptors, we have finally used 51 descriptors for model development using genetic methods. The best model showed encouraging values for internal.....
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Cite this article as:
Ojha Kumar Probir and Roy Kunal, Exploration of Important Sites of Antimalarial Endochins for Optimum Structural Modification Using Group-Based QSAR (G-QSAR) Modeling, Current Computer-Aided Drug Design 2013; 9 (3) . https://dx.doi.org/10.2174/15734099113099990019
DOI https://dx.doi.org/10.2174/15734099113099990019 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |
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