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An Alignment-Independent 3D-QSAR Study of FGFR2 Tyrosine Kinase Inhibitors

Authors :
Behzad Jafari
Maryam Hamzeh-Mivehroud
Ali Akbar Alizadeh
Mehdi Sharifi
Siavoush Dastmalchi
Source :
Advanced Pharmaceutical Bulletin, Vol 7, Iss 3, Pp 409-418 (2017)
Publication Year :
2017
Publisher :
Tabriz University of Medical Sciences, 2017.

Abstract

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 (r2 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.

Details

Language :
English
ISSN :
22285881 and 22517308
Volume :
7
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Advanced Pharmaceutical Bulletin
Publication Type :
Academic Journal
Accession number :
edsdoj.bb32953117b84f9197a47793e9f1812d
Document Type :
article
Full Text :
https://doi.org/10.15171/apb.2017.049