Chen Peng-Yu, Han Lin-Tao
Faculty of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China.
Key Laboratory of Traditional Chinese Medicine Resources and Prescription, Ministry of Education, Wuhan, China.
Front Chem. 2023 Jan 9;10:1060500. doi: 10.3389/fchem.2022.1060500. eCollection 2022.
Evodiae Fructus (EF) is the dried, near ripe fruit of (Juss.) Benth in . Numerous studies have demonstrated its anti-liver cancer properties. However, the molecular mechanism of Evodiae fructus against liver cancer and its structure-activity connection still require clarification. We utilized network pharmacology and a QSAR (2- and 3-dimensional) model to study the anti-liver cancer effect of Evodiae fructus. First, by using network pharmacology to screen the active substances and targets of Evodiae fructus, we investigated the signaling pathways involved in the anti-liver cancer actions of Evodiae fructus. The 2D-QSAR pharmacophore model was then used to predict the pIC50 values of compounds. The hiphop method was used to create an ideal 3D-QSAR pharmacophore model for the prediction of Evodiae fructus compounds. Finally, molecular docking was used to validate the rationality of the pharmacophore, and molecular dynamics was used to disclose the stability of the compounds by assessing the trajectories in 10 ns using RMSD, RMSF, Rg, and hydrogen bonding metrics. In total, 27 compounds were acquired from the TCMSP and TCM-ID databases, and 45 intersection targets were compiled using Venn diagrams. Network integration analysis was used in this study to identify SRC as a primary target. Key pathways were discovered by KEGG pathway analysis, including PD-L1 expression and PD-1 checkpoint pathway, EGFR tyrosine kinase inhibitor resistance, and ErbB signaling pathway. Using a 2D-QSAR pharmacophore model and the MLR approach to predict chemical activity, ten highly active compounds were found. Two hydrophobic features and one hydrogen bond acceptor feature in the 3D-QSAR pharmacophore model were validated by training set chemicals. The results of molecular docking revealed that 10 active compounds had better docking scores with SRC and were linked to residues hydrogen and hydrophobic bonds. Molecular dynamics was used to show the structural stability of obacunone, beta-sitosterol, and sitosterol. Pharmacophore 01 has high selectivity and the ability to distinguish active and inactive compounds, which is the optimal model for this study. Obacunone has the optimal binding ability with SRC. The pharmacophore model proposed in this study provides theoretical support for further screening effective anti-cancer Chinese herbal compounds and optimizing the compound structure.
吴茱萸是芸香科植物吴茱萸（Evodia rutaecarpa (Juss.) Benth.）将近成熟的干燥果实。众多研究已证实其具有抗肝癌特性。然而，吴茱萸抗肝癌的分子机制及其构效关系仍有待阐明。我们利用网络药理学和定量构效关系（二维和三维）模型来研究吴茱萸的抗肝癌作用。首先，通过网络药理学筛选吴茱萸的活性物质和靶点，我们研究了吴茱萸抗肝癌作用涉及的信号通路。然后使用二维定量构效关系药效团模型预测化合物的半数抑制浓度负对数（pIC50）值。采用嘻哈方法创建理想的三维定量构效关系药效团模型以预测吴茱萸化合物。最后，使用分子对接验证药效团的合理性，并通过使用均方根偏差（RMSD）、均方根波动（RMSF）、回旋半径（Rg）和氢键指标评估10纳秒内的轨迹，利用分子动力学揭示化合物的稳定性。总共从中药系统药理学数据库（TCMSP）和中药鉴定数据库（TCM-ID）中获取了27种化合物，并使用维恩图汇总了45个交集靶点。本研究采用网络整合分析确定原癌基因酪氨酸蛋白激酶（SRC）为主要靶点。通过京都基因与基因组百科全书（KEGG）通路分析发现了关键通路，包括程序性死亡配体1（PD-L1）表达和程序性死亡受体1（PD-1）检查点通路、表皮生长因子受体（EGFR）酪氨酸激酶抑制剂耐药性以及表皮生长因子受体2（ErbB）信号通路。使用二维定量构效关系药效团模型和多元线性回归（MLR）方法预测化学活性，发现了10种高活性化合物。通过训练集化学物质验证了三维定量构效关系药效团模型中的两个疏水特征和一个氢键受体特征。分子对接结果表明，10种活性化合物与SRC具有更好的对接分数，并通过氢键和疏水键与残基相连。分子动力学用于展示奥巴库酮、β-谷甾醇和谷甾醇的结构稳定性。药效团01具有高选择性以及区分活性和非活性化合物的能力，是本研究的最佳模型。奥巴库酮与SRC具有最佳结合能力。本研究提出的药效团模型为进一步筛选有效的抗癌中草药化合物和优化化合物结构提供了理论支持。
