Repository logo
 

Identification of Potential p38γ Inhibitors via In Silico Screening, In Vitro Bioassay and Molecular Dynamics Simulation Studies.

Published version

Published version
Peer-reviewed

Repository DOI


Change log

Authors

Cheng, Zixuan 
Hwang, Siaw San 
Chee, Xavier Wezen 

Abstract

Protein kinase p38γ is an attractive target against cancer because it plays a pivotal role in cancer cell proliferation by phosphorylating the retinoblastoma tumour suppressor protein. Therefore, inhibition of p38γ with active small molecules represents an attractive alternative for developing anti-cancer drugs. In this work, we present a rigorous and systematic virtual screening framework to identify potential p38γ inhibitors against cancer. We combined the use of machine learning-based quantitative structure activity relationship modelling with conventional computer-aided drug discovery techniques, namely molecular docking and ligand-based methods, to identify potential p38γ inhibitors. The hit compounds were filtered using negative design techniques and then assessed for their binding stability with p38γ through molecular dynamics simulations. To this end, we identified a promising compound that inhibits p38γ activity at nanomolar concentrations and hepatocellular carcinoma cell growth in vitro in the low micromolar range. This hit compound could serve as a potential scaffold for further development of a potent p38γ inhibitor against cancer.

Description

Peer reviewed: True

Keywords

QSAR modelling, binding interaction, molecular dynamic simulations, p38γ, virtual screening, Antineoplastic Agents, Biological Assay, Drug Discovery, Ligands, Molecular Docking Simulation, Molecular Dynamics Simulation, Quantitative Structure-Activity Relationship, Mitogen-Activated Protein Kinase 12

Journal Title

Int J Mol Sci

Conference Name

Journal ISSN

1422-0067
1422-0067

Volume Title

Publisher

MDPI AG