Literature DB >> 31338599

Theoretical studies on the selectivity mechanisms of PI3Kδ inhibition with marketed idelalisib and its derivatives by 3D-QSAR, molecular docking, and molecular dynamics simulation.

Jingyu Zhu1, Ke Ke2, Lei Xu3, Jian Jin4.   

Abstract

Phosphoinositide 3-kinases (PI3Ks) are crucial for cell proliferation, metabolism, motility, and cancer progression. Since the selective PI3Kδ inhibitor, idelalisib, was firstly approved by the FDA in 2014, large numbers of selective PI3Kδ inhibitors have been reported, but the detailed mechanisms of selective inhibition to PI3Kδ for idelalisib or its derivatives have not been well addressed. In this study, 3D-QSAR with COMFA, molecular docking, and molecular dynamic (MD) simulations was used to explore the binding modes between PI3Kδ and idelalisib derivatives. Firstly, a reliable COMFA model (q2 = 0.59, ONC = 8, r2 = 0.966) was built and the contour maps showed that the electrostatic field had more significant contribution to the bioactivities of inhibitors. Secondly, two molecular docking methods including rigid receptor docking (RRD) and induced fit docking (IFD) were employed to predict the docking poses of all the studied inhibitors and revealed the selective binding mechanisms. And then, the results of the MD simulation and the binding free energy decomposition verified that the binding of PI3Kδ/inhibitors was mainly contributed from hydrogen bonding and hydrophobic interactions and some key residues for selective binding were highlighted. Finally, based on the models developed, 14 novel inhibitors were optimized and some showed satisfactory predicted bioactivity. Taken together, the results provided by this study may facilitate the rational design of novel and selective PI3Kδ inhibitors. Graphical abstract .

Entities:  

Keywords:  3D-QSAR COMFA; Idelalisib; Molecular docking; Molecular dynamics simulations; PI3Kδ inhibitors

Year:  2019        PMID: 31338599     DOI: 10.1007/s00894-019-4129-x

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  2 in total

1.  A multi-conformational virtual screening approach based on machine learning targeting PI3Kγ.

Authors:  Jingyu Zhu; Yingmin Jiang; Lei Jia; Lei Xu; Yanfei Cai; Yun Chen; Nannan Zhu; Huazhong Li; Jian Jin
Journal:  Mol Divers       Date:  2021-06-23       Impact factor: 3.364

2.  Theoretical Exploring Selective-Binding Mechanisms of JAK3 by 3D-QSAR, Molecular Dynamics Simulation and Free Energy Calculation.

Authors:  Jingyu Zhu; Qianqian Yu; Yanfei Cai; Yun Chen; Hui Liu; Wenqing Liang; Jian Jin
Journal:  Front Mol Biosci       Date:  2020-05-27
  2 in total

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