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使用虚拟筛选、FMO 计算和分子动力学模拟发现新型 SHP2 别构抑制剂。

Discovery of a novel SHP2 allosteric inhibitor using virtual screening, FMO calculation, and molecular dynamic simulation.

机构信息

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.

出版信息

J Mol Model. 2024 Apr 13;30(5):131. doi: 10.1007/s00894-024-05935-y.

Abstract

CONTEXT

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.

METHODS

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.

摘要

背景

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。

方法

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。

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