Insight into the selective mechanism of phosphoinositide 3‐kinase γ with benzothiazole and thiazolopiperidine γ‐specific inhibitors by in silico approaches

• Published in: Chemical biology & drug design Vol. 93; no. 5; pp. 818 - 831
• Main Authors: Zhu, Jingyu, Li, Kan, Xu, Lei, Jin, Jian
• Format: Journal Article
• Language: English
• Published: England 01.05.2019
• Subjects: Benzothiazoles - chemistry; Benzothiazoles - metabolism; Binding Sites; Catalytic Domain; Class Ib Phosphatidylinositol 3-Kinase - chemistry; Class Ib Phosphatidylinositol 3-Kinase - metabolism; Enzyme Inhibitors - chemistry; Enzyme Inhibitors - metabolism; Humans; Ligands; MM‐GBSA; molecular docking; Molecular Docking Simulation; molecular dynamic simulation; Molecular Dynamics Simulation; PI3Kγ; Piperidines - chemistry; Piperidines - metabolism; selective inhibitor; Thermodynamics; selective inhibitor; molecular docking; PI3Kγ; molecular dynamic simulation; MM-GBSA
• ISSN: 1747-0277; 1747-0285; 1747-0285
• DOI: 10.1111/cbdd.13469

The phosphoinositide 3‐kinase γ (PI3Kγ) has been verified to be a potential drug target for the treatments of various human physical disorders. Although received lots of attention, the development of PI3Kγ‐selective inhibitors is still a challenging subject because of its unique protein structural features. Aiming to uncover the interaction mechanism between the selective inhibitors and PI3Kγ, a series of benzothiazole and thiazolopiperidine PI3Kγ isoform‐selective inhibitors were studied with an integrated in silico strategy by combining molecular docking, molecular dynamic simulations, binding free energy calculations, and decomposition analysis. Firstly, three molecular docking models, including rigid receptor docking, induced fit docking (IFD), and quantum mechanical‐polarized ligand docking, were respectively, built, and the IFD preliminarily predicted the docking poses of all studied inhibitors and roughly analyzed the binding mechanism. Secondly, four binding complexes with representative inhibitors were selected to perform molecular dynamic simulations and free energy calculations. The predicted binding energies were consistent with the experimental bioactivities and different binding patterns between potent and weak inhibitors were uncovered. Finally, through the Molecular Mechanics/Generalized Born Surface Area binding free energy decomposition, residue–inhibitor interactions spectra were obtained and several key residues contributing to favorable binding were highlighted, which provides valuable information for rational PI3Kγ inhibitor design and modification. A computational strategy, which combines molecular docking, molecular dynamics simulations, free energy calculations, was employed to explore the binding mechanisms of γ‐selective inhibitors to phosphoinositide 3‐kinases γ (PI3Kγ). Several key residues contributing to PI3Kγ‐specific binding were highlighted, which provides valuable information for rational PI3Kγ‐selective inhibitor design.