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In Silico Design of Potent EGFR Kinase Inhibitors using Combinatorial Libraries

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Title In Silico Design of Potent EGFR Kinase Inhibitors using
Combinatorial Libraries
 
Creator Nandi, Sisir
Bagchi, Manish C
 
Subject Structural Biology & Bioinformatics
 
Description This paper is an attempt to design 4-anilinoquinazoline compounds having promising anticancer activities against epidermal
growth factor (EGFR) kinase inhibition, using virtual combinatorial library approach. Partial least squares method has been
applied for the development of a quantitative structure–activity relationship (QSAR) model based on training and test set
approaches. The partial least squares model showed some interesting results in terms of internal and external predictability
against EGFR kinase inhibition for such type of anilinoquinazoline derivatives. In virtual screening study, out of 4860
compounds in chemical library, 158 compounds were screened and finally, 10 compounds were selected as promising EGFR
kinase inhibitors based on their predicted activities from the QSAR model. These derivatives were subjected to molecular
docking study to investigate the mode of binding with the EGFR kinase, and the two compounds (ID 3639 and 3399)
showing similar type of docking score and binding patterns with that of the existing drug molecules like erlotinib were
finally reported.
 
Publisher Taylor & Francis
 
Date 2011
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://www.eprints.iicb.res.in/1311/1/MOLECULAR_SIMULATION___37_(3)_196%2D209;2011[149].pdf
Nandi, Sisir and Bagchi, Manish C (2011) In Silico Design of Potent EGFR Kinase Inhibitors using Combinatorial Libraries. Molecular Simulation, 37 (3). pp. 196-209. ISSN 0892-7022
 
Relation http://dx.doi.org/10.1080/08927022.2010.536542
http://www.eprints.iicb.res.in/1311/