Identification of Potential MEK1 Inhibitors by Pharmacophore-based Virtual Screening and MD Simulations
Huanhuan Shi, Lu Zhou, Guangkai Bao, Qianying Yi, Suwen Zhou, Yahui Tian and Xiaoli LiAffiliation:
College of Chemical Engineering, Sichuan University, Sichuan, Chengdu, 610065, China.
AbstractMEK proteins play a critical role in tumor proliferation, differentiation, and survival. Hence MEK1 inhibitors are of particular importance in the treatment of related diseases. The present study describes pharmacophore-based 3DQSAR model generation based on 82 known inhibitors of MEK1 allosteric binding cavity. The best pharmacophore model developed consisted of four features, namely AHHR. The model was used as a query to screen the databases of almost 1.3 million compounds. Finally, 8 hits were indentified and the docking study manifested that these compounds interacted with MEK1 well. Finally, 10 ns MD simulations of the obtained ligand-receptor system were performed. The stable binding mode of the system was determined. Our results showed that the identified 8 hits would be useful for the development of potent MEK1 agents.
3D-QSAR, Allosteric binding cavity, MD simulations, MEK1, Molecular docking, Virtual screening.
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