Li Kan, Zhu Jingyu, Xu Lei, Jin Jian
School of Pharmaceutical Sciences, Jiangnan University, Wuxi, 214122, P. R. China.
Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, 213001, P. R. China.
Chem Biodivers. 2019 Jul;16(7):e1900105. doi: 10.1002/cbdv.201900105. Epub 2019 Jun 21.
Phosphoinositide 3-kinase gamma (PI3Kγ) draws an increasing attention due to its link with deadly cancer, chronic inflammation and allergy. But the development of PI3Kγ selective inhibitors is still a challenging endeavor because of the high sequence homology with the other PI3K isoforms. In order to acquire valuable information about the interaction mechanism between potent inhibitors and PI3Kγ, a series of PI3Kγ isoform-selective inhibitors were analyzed by a systematic computational method, combining 3D-QSAR, molecular docking, molecular dynamic (MD) simulations, free energy calculations and decomposition. The general structure-activity relationships were revealed and some key residues relating to selectivity and high activity were highlighted. It provides precious guidance for rational virtual screening, modification and design of selective PI3Kγ inhibitors. Finally, ten novel inhibitors were optimized and P10 showed satisfactory predicted bioactivity, demonstrating the feasibility to develop potent PI3Kγ inhibitors through this computational modeling and optimization.
磷酸肌醇3-激酶γ（PI3Kγ）因其与致命癌症、慢性炎症和过敏的关联而受到越来越多的关注。但由于PI3Kγ与其他PI3K亚型具有高度的序列同源性，开发PI3Kγ选择性抑制剂仍然是一项具有挑战性的工作。为了获取有关强效抑制剂与PI3Kγ之间相互作用机制的有价值信息，采用系统计算方法，结合3D-QSAR、分子对接、分子动力学（MD）模拟、自由能计算和分解，对一系列PI3Kγ亚型选择性抑制剂进行了分析。揭示了一般的构效关系，并突出了一些与选择性和高活性相关的关键残基。它为合理的虚拟筛选、修饰和设计选择性PI3Kγ抑制剂提供了宝贵的指导。最后，对10种新型抑制剂进行了优化，P10表现出令人满意的预测生物活性，证明了通过这种计算建模和优化开发强效PI3Kγ抑制剂的可行性。
