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Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method

The epidermal growth factor receptor (EGFR) protein tyrosine kinase (PTK) is an important protein target for anti-tumor drug discovery. To identify potential EGFR inhibitors, we conducted a quantitative structure–activity relationship (QSAR) study on the inhibitory activity of a series of quinazolin...

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Detalles Bibliográficos
Autores principales: Du, Hongying, Hu, Zhide, Bazzoli, Andrea, Zhang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141047/
https://www.ncbi.nlm.nih.gov/pubmed/21811593
http://dx.doi.org/10.1371/journal.pone.0022367
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author Du, Hongying
Hu, Zhide
Bazzoli, Andrea
Zhang, Yang
author_facet Du, Hongying
Hu, Zhide
Bazzoli, Andrea
Zhang, Yang
author_sort Du, Hongying
collection PubMed
description The epidermal growth factor receptor (EGFR) protein tyrosine kinase (PTK) is an important protein target for anti-tumor drug discovery. To identify potential EGFR inhibitors, we conducted a quantitative structure–activity relationship (QSAR) study on the inhibitory activity of a series of quinazoline derivatives against EGFR tyrosine kinase. Two 2D-QSAR models were developed based on the best multi-linear regression (BMLR) and grid-search assisted projection pursuit regression (GS-PPR) methods. The results demonstrate that the inhibitory activity of quinazoline derivatives is strongly correlated with their polarizability, activation energy, mass distribution, connectivity, and branching information. Although the present investigation focused on EGFR, the approach provides a general avenue in the structure-based drug development of different protein receptor inhibitors.
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spelling pubmed-31410472011-08-02 Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method Du, Hongying Hu, Zhide Bazzoli, Andrea Zhang, Yang PLoS One Research Article The epidermal growth factor receptor (EGFR) protein tyrosine kinase (PTK) is an important protein target for anti-tumor drug discovery. To identify potential EGFR inhibitors, we conducted a quantitative structure–activity relationship (QSAR) study on the inhibitory activity of a series of quinazoline derivatives against EGFR tyrosine kinase. Two 2D-QSAR models were developed based on the best multi-linear regression (BMLR) and grid-search assisted projection pursuit regression (GS-PPR) methods. The results demonstrate that the inhibitory activity of quinazoline derivatives is strongly correlated with their polarizability, activation energy, mass distribution, connectivity, and branching information. Although the present investigation focused on EGFR, the approach provides a general avenue in the structure-based drug development of different protein receptor inhibitors. Public Library of Science 2011-07-21 /pmc/articles/PMC3141047/ /pubmed/21811593 http://dx.doi.org/10.1371/journal.pone.0022367 Text en Du et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Du, Hongying
Hu, Zhide
Bazzoli, Andrea
Zhang, Yang
Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method
title Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method
title_full Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method
title_fullStr Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method
title_full_unstemmed Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method
title_short Prediction of Inhibitory Activity of Epidermal Growth Factor Receptor Inhibitors Using Grid Search-Projection Pursuit Regression Method
title_sort prediction of inhibitory activity of epidermal growth factor receptor inhibitors using grid search-projection pursuit regression method
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141047/
https://www.ncbi.nlm.nih.gov/pubmed/21811593
http://dx.doi.org/10.1371/journal.pone.0022367
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