Discovery, optimization and biological evaluation for novel c-Met kinase inhibitors

Discovery, optimization and biological evaluation for novel c-Met kinase inhibitors The c-Met kinase has emerged as an attractive target for developing antitumor agents because of its close relationship with the development of many human cancers, poor clinical outcomes and even drug resistance. A series of novel c-Met kinase inhibitors have been identified with multiple workflow in this work, including virtual screening, X-ray crystallography, biological evaluation and structural optimization. The experimentally determined crystal structure of the best hit compound HL-11 in c-Met kinase domain was highly consistent with the computational prediction. Comparison of the hit compounds with different c-Met kinase inhibitory activity by molecular dynamics simulations suggested the key protein-ligand interactions for structural optimization. Based on these, structural optimization produced compound 11e with better c-Met kinase inhibitory activity and improved anti-proliferative activity. These experimental findings proved the reliability and efficiency of our in silico methods. This strategy will facilitate further lead discovery and optimization for novel c-Met kinase inhibitors. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Medicinal Chemistry Elsevier

Discovery, optimization and biological evaluation for novel c-Met kinase inhibitors

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Masson SAS
ISSN
0223-5234
eISSN
1768-3254
D.O.I.
10.1016/j.ejmech.2017.11.073
Publisher site
See Article on Publisher Site

Abstract

The c-Met kinase has emerged as an attractive target for developing antitumor agents because of its close relationship with the development of many human cancers, poor clinical outcomes and even drug resistance. A series of novel c-Met kinase inhibitors have been identified with multiple workflow in this work, including virtual screening, X-ray crystallography, biological evaluation and structural optimization. The experimentally determined crystal structure of the best hit compound HL-11 in c-Met kinase domain was highly consistent with the computational prediction. Comparison of the hit compounds with different c-Met kinase inhibitory activity by molecular dynamics simulations suggested the key protein-ligand interactions for structural optimization. Based on these, structural optimization produced compound 11e with better c-Met kinase inhibitory activity and improved anti-proliferative activity. These experimental findings proved the reliability and efficiency of our in silico methods. This strategy will facilitate further lead discovery and optimization for novel c-Met kinase inhibitors.

Journal

European Journal of Medicinal ChemistryElsevier

Published: Jan 1, 2018

References

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