Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors

A quantitative structure activity relationship (QSAR) analysis was performed on two series of benzoxazole-phenoxyalkyl-phenoxybutyric acids with potent PPARα activation activity using diverse descriptors. The 31 compounds were divided into a training set and a test set based on Euclidean distance....

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Detalles Bibliográficos
Autores principales:	Chen, Mei-mei, Lai, Xin-mei, Yang, Xue-mei
Formato:	Articulo
Lenguaje:	Inglés
Publicado:	2012
Materias:	Farmacia Benzoxazole-phenoxyalkyl-phenoxybutyric acids PPARα QSAR Descriptores Relación Estructura-Actividad Cuantitativa
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/20213 http://www.latamjpharm.org/resumenes/31/5/LAJOP_31_5_1_1.pdf
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-20213
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Farmacia Benzoxazole-phenoxyalkyl-phenoxybutyric acids PPARα QSAR Descriptores Relación Estructura-Actividad Cuantitativa
spellingShingle	Farmacia Benzoxazole-phenoxyalkyl-phenoxybutyric acids PPARα QSAR Descriptores Relación Estructura-Actividad Cuantitativa Chen, Mei-mei Lai, Xin-mei Yang, Xue-mei Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors
topic_facet	Farmacia Benzoxazole-phenoxyalkyl-phenoxybutyric acids PPARα QSAR Descriptores Relación Estructura-Actividad Cuantitativa
description	A quantitative structure activity relationship (QSAR) analysis was performed on two series of benzoxazole-phenoxyalkyl-phenoxybutyric acids with potent PPARα activation activity using diverse descriptors. The 31 compounds were divided into a training set and a test set based on Euclidean distance. The model was derived through multiple linear stepwise regression method and the predictive ability of the best model was validated by leave-one-out cross-validation and external validation on the test set. The best generated QSAR model explained good fits to the experimental data with approximate 80 % of the variance in the biological activity. Also, the important cross-validated squared correlation coefficient (r2 = 0.697) and the accuracy of 90 % correct predictions for the test set further confirmed that the model exhibited reliable predictive power ability. The generated QSAR model revealed that PPARα activation activity of benzoxazole-phenoxyalkyl-phenoxybutyric acids was influenced by the presence of chiral centers and hydrogen bonding donor groups and the number of positive charges and positive polar charges in the molecule, which might help in developing new PPARα agonists with better activity.
format	Articulo Articulo
author	Chen, Mei-mei Lai, Xin-mei Yang, Xue-mei
author_facet	Chen, Mei-mei Lai, Xin-mei Yang, Xue-mei
author_sort	Chen, Mei-mei
title	Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors
title_short	Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors
title_full	Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors
title_fullStr	Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors
title_full_unstemmed	Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors
title_sort	modeling pparα activation of benzoxazole-phenoxyalkyl-phenoxybutyric acids using diverse descriptors
publishDate	2012
url	http://sedici.unlp.edu.ar/handle/10915/20213 http://www.latamjpharm.org/resumenes/31/5/LAJOP_31_5_1_1.pdf
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bdutipo_str	Repositorios
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Modeling PPARα activation of Benzoxazole-Phenoxyalkyl-Phenoxybutyric acids using diverse descriptors

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