Wujieti Baerlike, Hao Mingtian, Liu Erxia, Zhou Luqi, Wang Huanchao, Zhang Yu, Cui Wei, Chen Bozhen
School of Chemical Sciences, University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing 100049, China.
Molecules. 2024 Dec 24;30(1):14. doi: 10.3390/molecules30010014.
The src-homology 2 domain-containing phosphatase 2 (SHP2) is a human cytoplasmic protein tyrosine phosphatase that plays a crucial role in cellular signal transduction. Aberrant activation and mutations of SHP2 are associated with tumor growth and immune suppression, thus making it a potential target for cancer therapy. Initially, researchers sought to develop inhibitors targeting SHP2's catalytic site (protein tyrosine phosphatase domain, PTP). Due to limitations such as conservativeness and poor membrane permeability, SHP2 was once considered a challenging drug target. Nevertheless, with the in-depth investigations into the conformational switch mechanism from SHP2's inactive to active state and the emergence of various SHP2 allosteric inhibitors, new hope has been brought to this target. In this study, we investigated the interaction models of various allosteric inhibitors with SHP2 using molecular dynamics simulations. Meanwhile, we explored the free energy landscape of SHP2 activation using enhanced sampling technique (meta-dynamics simulations), which provides insights into its conformational changes and activation mechanism. Furthermore, to biophysically interpret high-dimensional simulation trajectories, we employed interpretable machine learning methods, specifically extreme gradient boosting (XGBoost) with Shapley additive explanations (SHAP), to comprehensively analyze the simulation data. This approach allowed us to identify and highlight key structural features driving SHP2 conformational dynamics and regulating the activity of the allosteric inhibitor. These studies not only enhance our understanding of SHP2's conformational switch mechanism but also offer crucial insights for designing potent allosteric SHP2 inhibitors and addressing drug resistance issues.
含Src同源2结构域的磷酸酶2(SHP2)是一种人类细胞质蛋白酪氨酸磷酸酶,在细胞信号转导中起关键作用。SHP2的异常激活和突变与肿瘤生长和免疫抑制相关,因此使其成为癌症治疗的潜在靶点。最初,研究人员试图开发针对SHP2催化位点(蛋白酪氨酸磷酸酶结构域,PTP)的抑制剂。由于保守性和膜通透性差等局限性,SHP2曾被认为是一个具有挑战性的药物靶点。然而,随着对SHP2从无活性状态到活性状态的构象转换机制的深入研究以及各种SHP2变构抑制剂的出现,这个靶点带来了新的希望。在本研究中,我们使用分子动力学模拟研究了各种变构抑制剂与SHP2的相互作用模型。同时,我们使用增强采样技术(元动力学模拟)探索了SHP2激活的自由能景观,这为其构象变化和激活机制提供了见解。此外,为了从生物物理学角度解释高维模拟轨迹,我们采用了可解释的机器学习方法,特别是带有Shapley加性解释(SHAP)的极端梯度提升(XGBoost),以全面分析模拟数据。这种方法使我们能够识别并突出驱动SHP2构象动力学和调节变构抑制剂活性的关键结构特征。这些研究不仅加深了我们对SHP2构象转换机制的理解,还为设计有效的SHP2变构抑制剂和解决耐药性问题提供了关键见解。