基于网络药理学探讨牡荆苷治疗肺癌的作用机制

Network Pharmacology-Based Analysis of the Mechanism of Vitexin in the Treatment of Lung Cancer

摘要: 目的：基于网络药理学方法预测牡荆苷(Vitexin)治疗肺癌的潜在作用靶点及相关通路网络，并进一步结合分子对接从结构层面对关键候选靶点进行初步验证，为后续实验验证提供理论依据。方法：检索TCMSP、PubChem获取牡荆苷化合物资料；利用Prediction、SwissTargetPrediction和PharmMapper进行靶点预测，并通过UniProt统一基因名称。在GeneCards、OMIM、CTD数据库，以“lung cancer”为关键词，检索并汇总肺癌相关基因。药物靶点与疾病靶点取交集后，导入STRING构建PPI网络，并在Cytoscape 3.10.4中结合CytoHubba插件筛选网络核心节点。随后在R语言环境下调用clusterProfiler包，对相关靶点开展GO功能注释和KEGG通路富集分析。在此基础上，综合拓扑学排序、通路关联及靶点功能意义，选取EGFR、SRC、HSP90AA1、ESR1和PIK3R1五个候选核心靶点进行分子对接，评价牡荆苷与靶蛋白之间的结合趋势。结果：共获得牡荆苷候选靶点216个、肺癌疾病靶点700个，交集靶点为42个；其中38个靶点被纳入PPI网络分析。Degree、MCC、MNC和EPC四种算法交叉筛选后，得到SRC、HSP90AA1、EGFR、ESR1、PIK3R1、MAPK1、STAT1、MAPK8、HIF1A等9个候选核心靶点。GO分析共获得1235个显著条目，包括BP 1126条、CC 28条、MF 81条；KEGG分析共得到149条显著通路，涉及癌症通路、HIF-1、PI3K-Akt、MAPK、EGFR酪氨酸激酶抑制剂耐药及细胞凋亡等信号网络。分子对接结果显示，牡荆苷与EGFR、ESR1、PIK3R1、SRC和HSP90AA1的对接得分均低于−7 kcal/mol，其中EGFR对接得分最低(−10.10 kcal/mol)，提示其可能是牡荆苷干预肺癌候选网络中的重要结构结合节点。结论：牡荆苷与肺癌相关靶点之间呈现较明显的网络化联系，其候选作用机制可能围绕EGFR/SRC/HSP90AA1等上游节点展开，并进一步连接PI3K-Akt、MAPK、HIF-1及细胞凋亡相关通路。相关结果可为后续实验验证提供候选靶点和机制线索。

Abstract: Objective: This study aimed to predict the potential targets and related pathway network of vitexin in the treatment of lung cancer based on network pharmacology, and to perform preliminary structural verification of key candidate targets by molecular docking. Methods: Chemical information of vitexin was retrieved from TCMSP and PubChem. Potential targets were collected from Prediction, SwissTargetPrediction and PharmMapper, and gene names were standardized using UniProt. Lung cancer-related genes were obtained from GeneCards, OMIM and CTD using “lung cancer” as the search term. Shared targets between vitexin and lung cancer were used for STRING-based protein-protein interaction analysis. Cytoscape 3.10.4 and CytoHubba were then applied to identify key nodes using the Degree, MCC, MNC and EPC algorithms. GO annotation and KEGG pathway enrichment were performed in R with the clusterProfiler package, and adjusted P-value < 0.05 was used as the significance threshold. EGFR, SRC, HSP90AA1, ESR1 and PIK3R1 were selected for molecular docking according to topological ranking, pathway association and functional relevance. Results: A total of 216 candidate vitexin targets and 700 lung cancer-related targets were collected. Their intersection contained 42 targets, 38 of which were retained in the PPI network. Cross-comparison of the four CytoHubba algorithms yielded nine candidate hub targets: SRC, HSP90AA1, EGFR, ESR1, PIK3R1, MAPK1, STAT1, MAPK8 and HIF1A. GO enrichment returned 1235 significant terms, including 1126 biological process terms, 28 cellular component terms and 81 molecular function terms. KEGG enrichment identified 149 significant pathways, mainly including pathways in cancer, HIF-1 signaling, PI3K-Akt signaling, MAPK signaling, EGFR tyrosine kinase inhibitor resistance-related pathway and apoptosis pathway. Molecular docking showed that all five selected targets had docking scores lower than -7 kcal/mol, with EGFR displaying the lowest docking score (−10.10 kcal/mol). Conclusion: The predicted network and docking results suggest that vitexin may be associated with lung cancer through an EGFR/SRC/HSP90AA1-centered regulatory network, which may further connect with PI3K-Akt, MAPK, HIF-1 and apoptosis-related pathways. These results should be regarded as hypotheses derived from bioinformatics and molecular docking analyses and require further validation in molecular, cellular and animal experiments.