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An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors
Purpose: Receptor tyrosine kinase (RTK) inhibitors are widely used pharmaceuticals in cancer therapy. Fibroblast growth factor receptors (FGFRs) are members of RTK superfamily which are highly expressed on the surface of carcinoma associate fibroblasts (CAFs). The involvement of FGFRs in different t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Tabriz University of Medical Sciences
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651062/ https://www.ncbi.nlm.nih.gov/pubmed/29071223 http://dx.doi.org/10.15171/apb.2017.049 |
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author | Jafari, Behzad Hamzeh-Mivehroud, Maryam Alizadeh, Ali Akbar Sharifi, Mehdi Dastmalchi, Siavoush |
author_facet | Jafari, Behzad Hamzeh-Mivehroud, Maryam Alizadeh, Ali Akbar Sharifi, Mehdi Dastmalchi, Siavoush |
author_sort | Jafari, Behzad |
collection | PubMed |
description | Purpose: Receptor tyrosine kinase (RTK) inhibitors are widely used pharmaceuticals in cancer therapy. Fibroblast growth factor receptors (FGFRs) are members of RTK superfamily which are highly expressed on the surface of carcinoma associate fibroblasts (CAFs). The involvement of FGFRs in different types of cancer makes them promising target in cancer therapy and hence, the identification of novel FGFR inhibitors is of great interest. In the current study we aimed to develop an alignment independent three dimensional quantitative structure-activity relationship (3D-QSAR) model for a set of 26 FGFR2 kinase inhibitors allowing the prediction of activity and identification of important structural features for these inhibitors. Methods: Pentacle software was used to calculate grid independent descriptors (GRIND) for the active conformers generated by docking followed by the selection of significant variables using fractional factorial design (FFD). The partial least squares (PLS) model generated based on the remaining descriptors was assessed by internal and external validation methods. Results: Six variables were identified as the most important probes-interacting descriptors with high impact on the biological activity of the compounds. Internal and external validations were lead to good statistical parameters (r(2) values of 0.93 and 0.665, respectively). Conclusion: The results showed that the model has good predictive power and may be used for designing novel FGFR2 inhibitors. |
format | Online Article Text |
id | pubmed-5651062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Tabriz University of Medical Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-56510622017-10-25 An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors Jafari, Behzad Hamzeh-Mivehroud, Maryam Alizadeh, Ali Akbar Sharifi, Mehdi Dastmalchi, Siavoush Adv Pharm Bull Research Article Purpose: Receptor tyrosine kinase (RTK) inhibitors are widely used pharmaceuticals in cancer therapy. Fibroblast growth factor receptors (FGFRs) are members of RTK superfamily which are highly expressed on the surface of carcinoma associate fibroblasts (CAFs). The involvement of FGFRs in different types of cancer makes them promising target in cancer therapy and hence, the identification of novel FGFR inhibitors is of great interest. In the current study we aimed to develop an alignment independent three dimensional quantitative structure-activity relationship (3D-QSAR) model for a set of 26 FGFR2 kinase inhibitors allowing the prediction of activity and identification of important structural features for these inhibitors. Methods: Pentacle software was used to calculate grid independent descriptors (GRIND) for the active conformers generated by docking followed by the selection of significant variables using fractional factorial design (FFD). The partial least squares (PLS) model generated based on the remaining descriptors was assessed by internal and external validation methods. Results: Six variables were identified as the most important probes-interacting descriptors with high impact on the biological activity of the compounds. Internal and external validations were lead to good statistical parameters (r(2) values of 0.93 and 0.665, respectively). Conclusion: The results showed that the model has good predictive power and may be used for designing novel FGFR2 inhibitors. Tabriz University of Medical Sciences 2017-09 2017-09-25 /pmc/articles/PMC5651062/ /pubmed/29071223 http://dx.doi.org/10.15171/apb.2017.049 Text en ©2017 The Authors. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. |
spellingShingle | Research Article Jafari, Behzad Hamzeh-Mivehroud, Maryam Alizadeh, Ali Akbar Sharifi, Mehdi Dastmalchi, Siavoush An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors |
title |
An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors
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title_full |
An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors
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title_fullStr |
An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors
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title_full_unstemmed |
An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors
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title_short |
An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors
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title_sort | alignment-independent 3d-qsar study of fgfr2 tyrosine kinase inhibitors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651062/ https://www.ncbi.nlm.nih.gov/pubmed/29071223 http://dx.doi.org/10.15171/apb.2017.049 |
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