基于网络药理学和分子对接探讨六味地黄丸治疗卵巢早衰的作用机制

doi:10.5246/jcps.2024.09.060

摘要/Abstract

摘要：

卵巢早衰是妇科常见疾病, 严重影响患者的心身健康, 六味地黄丸是中药复方, 对卵巢早衰具有积极作用。然而六味地黄丸的作用机制尚不清楚。因此, 本研究旨在通过网络药理学和分子对接技术揭示六味地黄丸治疗卵巢早衰的可能分子机制。首先, 在TCMSP中筛选六味地黄丸的成分和靶点; 并通过Disgenet、TTD、Drugbank、GeneCards、OMIM、PharmGKB数据库检索POF相关靶点; 将两者通过R语言、Cytoscapes和STRING进行汇总分析, 筛选出中药靶基因与疾病相关基因并构建中药调控网络和PPI网络图, 通过Metascape数据库对数据进行GO和KEGG富集分析; 最后, 以核心基因的蛋白受体和对应活性成分配体进行分子对接。共筛选出六味地黄丸49个成分和189个(去重复后)预测靶点, 卵巢早衰靶点4524个(去重复后); 通过比对六味地黄丸和POF共同靶点, 筛选出163个潜在基因; 这些共同靶点涉及对化学物质反应、分子功能调节、信号受体结合等生物学过程; 生物学通路包括MAPK信号通路、IL-17信号通路、HIF-1信号通路等。分子对接结果显示六味地黄丸的核心基因与成分有较好的结合能。

关键词: 网络药理学, 六味地黄丸, 卵巢早衰, 分子对接

Abstract:

Premature ovarian failure (POF) is a prevalent gynecological disorder with significant implications for the physical and mental well-being of affected individuals. Liu Wei Di Huang Wan (LWDHW), a Chinese herbal compound, has demonstrated efficacy in alleviating the effects of POF. However, the underlying mechanism of action of LWDHW remains unclear. This study aimed to elucidate the potential molecular mechanism of LWDHW in treating POF using network pharmacology and molecular docking techniques. The active ingredients of LWDHW were initially screened through the TCMSP platform. At the same time, the relevant target genes associated with POF were identified using databases such as Disgenet, TTD, Drugbank, GeneCards, OMIM, and PharmGKB. Data analysis was conducted using the R language, Cytoscape, and STRING to construct and analyze the traditional Chinese medicine (TCM) regulatory network and protein-protein interaction (PPI) network maps. Subsequently, GO and KEGG enrichment analyses were performed using the R language. Finally, molecular docking was carried out between the protein receptors of the core genes and the corresponding small-molecule ligands. The study revealed 49 components and 189 predicted targets (after de-duplication) of LWDHW, along with 4524 targets (after de-duplication) associated with POF. Through comparative analysis, 163 potential genes were identified as common targets of LWDHW and POF, participating in biological processes such as response to chemical substances, molecular function regulation, and signaling receptor binding. Key biological pathways implicated included the MAPK signaling pathway, IL-17 signaling pathway, and HIF-1 signaling pathway, among others. Molecular docking results demonstrated a robust binding ability between the core genes of LWDHW and their corresponding ingredients. In conclusion, this comprehensive analysis provided insights into the potential molecular mechanisms of LWDHW in treating POF. The identified common targets and associated pathways contributed to our understanding of how LWDHW exerted its therapeutic effects, paving the way for further research and clinical applications. It is worth noting that future studies with experimental validation and clinical trials are essential to confirm these findings and establish the safety and efficacy of LWDHW in the treatment of POF.

Key words: Network pharmacology, Liu Wei Di Huang Wan, Premature ovarian failure, Molecular docking

Supporting:

尚平, 刘琳, 方毅. 基于网络药理学和分子对接探讨六味地黄丸治疗卵巢早衰的作用机制[J]. 中国药学(英文版), 2024, 33(9): 805-818.

Ping Shang, Lin Liu, Yi Fang. Deciphering the mechanism of Liu Wei Di Huang Wan in treating premature ovarian failure: a comprehensive exploration through network pharmacology and molecular docking analysis[J]. Journal of Chinese Pharmaceutical Sciences, 2024, 33(9): 805-818.

图/表 11

Table 1. The main active components of LWDHW.

Figure 1. Disease target Venn diagram.

Figure 2. Drug target-disease target Venn diagram.

Figure 3. Drug-molecular-target network diagram. The circle shape indicates the name of the Chinese medicine (SY: Chinese Yam, SZY: cornel, FL: Poria, ZX: Alisma orientale, MDP: Peony bark, SDH: Prepared Radix Rehmanniae), the hexagon of each color indicates the compound molecule, and the diamond indicates the drug target.

Table 2. The specific meaning of the abbreviated compound-target interaction network diagram of LWDHW.

Figure 4. PPI network.

Figure 5. 147 intersection targets → 8 key targets.

Figure 6. The KEGG enrichment analysis.

Figure 7. The GO enrichment analysis.

Table 3. The binding energies of eight key targets and their interacting compounds.

Figure 8. The five target protein-active molecule docking patterns with smaller binding energies active. (A) The mode of action of diosgenin with the target ATK1 (PDB ID: 4GV1); (B) The mode of action of quercetin with the target CASP3 (PDB ID: 3DEK); (C) The mode of action of quercetin with the target EGFR (PDB ID: 4RJ3); (D) The mode of action of quercetin with the target JUN (PDB ID: 3OY1); (E) The mode of action of quercetin with the target MYC (PDB ID: 3BBF).

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