Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science & Technology, Shanghai, China.
Innovation Center for AI and Drug Discovery, East China Normal University, Shanghai, 200062, China.
J Mol Model. 2024 Apr 13;30(5):131. doi: 10.1007/s00894-024-05935-y.
SHP2 is a non-receptor protein tyrosine phosphatase to remove tyrosine phosphorylation. Functionally, SHP2 is an essential bridge to connect numerous oncogenic cell-signaling cascades including RAS-ERK, PI3K-AKT, JAK-STAT, and PD-1/PD-L1 pathways. This study aims to discover novel and potent SHP2 inhibitors using a hierarchical structure-based virtual screening strategy that combines molecular docking and the fragment molecular orbital method (FMO) for calculating binding affinity (referred to as the Dock-FMO protocol). For the SHP2 target, the FMO method prediction has a high correlation between the binding affinity of the protein-ligand interaction and experimental values (R = 0.55), demonstrating a significant advantage over the MM/PBSA (R = 0.02) and MM/GBSA (R = 0.15) methods. Therefore, we employed Dock-FMO virtual screening of ChemDiv database of ∼2,990,000 compounds to identify a novel SHP2 allosteric inhibitor bearing hydroxyimino acetamide scaffold. Experimental validation demonstrated that the new compound (E)-2-(hydroxyimino)-2-phenyl-N-(piperidin-4-ylmethyl)acetamide (7188-0011) effectively inhibited SHP2 in a dose-dependent manner. Molecular dynamics (MD) simulation analysis revealed the binding stability of compound 7188-0011 and the SHP2 protein, along with the key interacting residues in the allosteric binding site. Overall, our work has identified a novel and promising allosteric inhibitor that targets SHP2, providing a new starting point for further optimization to develop more potent inhibitors.
All the molecular docking studies were employed to identify potential leads with Maestro v10.1. The protein-ligand binding affinities of potential leads were further predicted by FMO calculations at MP2/6-31G* level using GAMESS v2020 system. MD simulations were carried out with AmberTools18 by applying the FF14SB force field. MD trajectories were analyzed using VMD v1.9.3. MM/GB(PB)SA binding free energy analysis was carried out with the mmpbsa.py tool of AmberTools18. The docking and MD simulation results were visualized through PyMOL v2.5.0.
SHP2 是一种非受体酪氨酸磷酸酶,可以去除酪氨酸磷酸化。从功能上讲,SHP2 是连接包括 RAS-ERK、PI3K-AKT、JAK-STAT 和 PD-1/PD-L1 途径在内的众多致癌细胞信号通路的重要桥梁。本研究旨在使用基于层次结构的虚拟筛选策略发现新型有效的 SHP2 抑制剂,该策略结合了分子对接和片段分子轨道方法(FMO)来计算结合亲和力(称为 Dock-FMO 方案)。对于 SHP2 靶标,FMO 方法预测与蛋白-配体相互作用的结合亲和力具有很高的相关性(R=0.55),与 MM/PBSA(R=0.02)和 MM/GBSA(R=0.15)方法相比具有显著优势。因此,我们采用 Dock-FMO 对 ChemDiv 数据库中约 299 万种化合物进行虚拟筛选,以鉴定一种新型 SHP2 变构抑制剂,其骨架为羟亚氨基乙酰胺。实验验证表明,新化合物(E)-2-(羟亚氨基)-2-苯基-N-(哌啶-4-基甲基)乙酰胺(7188-0011)可有效剂量依赖性抑制 SHP2。分子动力学(MD)模拟分析揭示了化合物 7188-0011 与 SHP2 蛋白的结合稳定性,以及变构结合位点中的关键相互作用残基。总体而言,我们的工作鉴定了一种新型有效的 SHP2 变构抑制剂,为进一步优化开发更有效的抑制剂提供了新的起点。
所有分子对接研究均采用 Maestro v10.1 进行,以确定潜在的先导化合物。使用 GAMESS v2020 系统在 MP2/6-31G*水平上进一步通过 FMO 计算预测潜在先导化合物的蛋白-配体结合亲和力。通过应用 AmberTools18 中的 AmberFF14SB 力场进行 MD 模拟。使用 VMD v1.9.3 分析 MD 轨迹。使用 AmberTools18 中的 mmpbsa.py 工具进行 MM/GB(PB)SA 结合自由能分析。通过 PyMOL v2.5.0 可视化对接和 MD 模拟结果。