Molecular modelling study on pyrrolo2,3-bpyridine derivatives as c-Met kinase inhibitors: a combined approach using molecular docking, 3D-QSAR modelling and molecular dynamics simulation

(2020) Molecular modelling study on pyrrolo2,3-bpyridine derivatives as c-Met kinase inhibitors: a combined approach using molecular docking, 3D-QSAR modelling and molecular dynamics simulation. Molecular Simulation. pp. 1265-1280. ISSN 0892-7022

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Abstract

Mesenchymal-epithelial transition factor (c-Met), also known as hepatocyte growth factor receptor (HGFR) is a unique member of receptor tyrosine kinase (RTKs) family. Dysregulation of c-Met/HGF signalling pathway is validated in a variety of human proliferative diseases. Therefore, targeting c-Met has become a promising strategy in anti-proliferative drug discovery. In this work, an integrated computational approaches were performed on 67 c-Met inhibitors to explore the structural requirements for their activity. Molecular docking was performed to elucidate their binding mode in c-Met active site. Subsequently, 3D-QSAR models were constructed using comparative molecular filed analysis (CoMFAq(2)= 0.692,r(2)= 0.912 andr(pred)(2)= 0.897) and comparative molecular similarity indices analysis (CoMSIAq(2)= 0.751,r(2)= 0.946 andr(pred)(2)= 0.944) techniques. The CoMSIA map analysis showed that hydrophobic contours play key role for inhibitory activity. According to docking and 3D-QSAR results, A total of 31 novel c-Met inhibitors with predicted improved activity were designed. A 100 ns molecular dynamics simulation and binding free energy calculations using the MM-PBSA method revealed the stability of the designed compoundD12inside the c-Met active site. In summary , the results of our study could provide significant insight for future design and development of novel c-Met kinase inhibitors.

Item Type: Article
Keywords: C-Met kinase 3D-QSAR molecular docking molecular dynamics simulation MM-PBSA HEPATOCYTE GROWTH-FACTOR SCATTER-FACTOR BEARING MOIETY VALIDATION DISCOVERY RECEPTOR DESIGN PREDICTION BINDING
Subjects: QV Pharmacology
Divisions: Bioinformatics Research Center
Faculty of Pharmacy and Pharmaceutical Sciences > گروه شیمی دارویی
Page Range: pp. 1265-1280
Journal or Publication Title: Molecular Simulation
Journal Index: ISI
Volume: 46
Number: 16
Identification Number: https://doi.org/10.1080/08927022.2020.1810853
ISSN: 0892-7022
Depositing User: Zahra Otroj
URI: http://eprints.mui.ac.ir/id/eprint/13718

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