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3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH
Epidermal growth factor receptor (EGFR) protein tyrosine kinases (PTKs) are known for its role in cancer. Quinazoline have been reported to be the molecules of interest, with potent anticancer activity and they act by binding to ATP site of protein kinases. ATP binding site of protein kinases provid...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3979194/ https://www.ncbi.nlm.nih.gov/pubmed/24825983 |
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author | Noolvi, Malleshappa N. Patel, Harun M. |
author_facet | Noolvi, Malleshappa N. Patel, Harun M. |
author_sort | Noolvi, Malleshappa N. |
collection | PubMed |
description | Epidermal growth factor receptor (EGFR) protein tyrosine kinases (PTKs) are known for its role in cancer. Quinazoline have been reported to be the molecules of interest, with potent anticancer activity and they act by binding to ATP site of protein kinases. ATP binding site of protein kinases provides an extensive opportunity to design newer analogs. With this background, we report an attempt to discern the structural and physicochemical requirements for inhibition of EGFR tyrosine kinase. The k-Nearest Neighbor Molecular Field Analysis (kNN-MFA), a three dimensional quantitative structure activity relationship (3D- QSAR) method has been used in the present case to study the correlation between the molecular properties and the tyrosine kinase (EGFR) inhibitory activities on a series of quinazoline derivatives. kNNMFA calculations for both electrostatic and steric field were carried out. The master grid maps derived from the best model has been used to display the contribution of electrostatic potential and steric field. The statistical results showed significant correlation coefficient r(2) (q(2)) of 0.846, r(2) for external test set (pred_r2) 0.8029, coefficient of correlation of predicted data set (pred_r(2)se) of 0.6658, degree of freedom 89 and k nearest neighbor of 2. Therefore, this study not only casts light on binding mechanism between EGFR and its inhibitors, but also provides hints for the design of new EGFR inhibitors with observable structural diversity |
format | Online Article Text |
id | pubmed-3979194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-39791942014-05-13 3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH Noolvi, Malleshappa N. Patel, Harun M. J Basic Clin Pharm Original Article Epidermal growth factor receptor (EGFR) protein tyrosine kinases (PTKs) are known for its role in cancer. Quinazoline have been reported to be the molecules of interest, with potent anticancer activity and they act by binding to ATP site of protein kinases. ATP binding site of protein kinases provides an extensive opportunity to design newer analogs. With this background, we report an attempt to discern the structural and physicochemical requirements for inhibition of EGFR tyrosine kinase. The k-Nearest Neighbor Molecular Field Analysis (kNN-MFA), a three dimensional quantitative structure activity relationship (3D- QSAR) method has been used in the present case to study the correlation between the molecular properties and the tyrosine kinase (EGFR) inhibitory activities on a series of quinazoline derivatives. kNNMFA calculations for both electrostatic and steric field were carried out. The master grid maps derived from the best model has been used to display the contribution of electrostatic potential and steric field. The statistical results showed significant correlation coefficient r(2) (q(2)) of 0.846, r(2) for external test set (pred_r2) 0.8029, coefficient of correlation of predicted data set (pred_r(2)se) of 0.6658, degree of freedom 89 and k nearest neighbor of 2. Therefore, this study not only casts light on binding mechanism between EGFR and its inhibitors, but also provides hints for the design of new EGFR inhibitors with observable structural diversity Medknow Publications & Media Pvt Ltd 2010-06 2010-08-15 /pmc/articles/PMC3979194/ /pubmed/24825983 Text en Copyright: © Journal of Basic and Clinical Pharmacy http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Noolvi, Malleshappa N. Patel, Harun M. 3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH |
title | 3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH |
title_full | 3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH |
title_fullStr | 3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH |
title_full_unstemmed | 3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH |
title_short | 3D QSAR STUDIES ON A SERIES OF QUINAZOLINE DERRIVATIVES AS TYROSINE KINASE (EGFR) INHIBITOR: THE K-NEAREST NEIGHBOR MOLECULAR FIELD ANALYSIS APPROACH |
title_sort | 3d qsar studies on a series of quinazoline derrivatives as tyrosine kinase (egfr) inhibitor: the k-nearest neighbor molecular field analysis approach |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3979194/ https://www.ncbi.nlm.nih.gov/pubmed/24825983 |
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