Network pharmacology-based screening of active constituents of Avicennia marina and their clinical biochemistry related mechanism against breast cancer

Breast cancer is the second major cause of cancer death in women globally. Avicennia marina is a medicinal plant that belongs to the family Acanthaceae and is known as grey or white mangrove. It has antioxidant, antiviral, anticancer, anti-inflammatory, and antibacterial activity in the treatment of various diseases including cancer. The goal of the study is to use a network pharmacology method to identify the potential phenomena of bioactive compounds of A. marina in the treatment of breast cancer and explore clinical biochemistry related aspects. A total of 74 active compounds of A. marina were retrieved from various databases as well as a literature review and collectively 429 targets of these compounds were identified by STITCH and Swiss Target Prediction databases. Breast cancer related 15606 potential targets were retrieved from the GeneCards database. A Venn diagram was drawn to find common key targets. To check the biological functions, the GO enrichment and KEGG pathways analysis of 171 key targets were performed through the DAVID database. To understand the interactions among key targets, Protein-protein interaction (PPI) studies were completed using the STRING database, and the Protein-Protein Interaction (PPI) network, as well as the compound-target-pathway network, was constructed using Cytoscape 3.9.0. Finally, molecular docking analysis of 5 hub genes named tumor protein 53 (TP53), catenin beta 1 (CTNNB1), interleukin 6 (IL6), tumor necrosis factor (TNF), and RAC-alpha serine/threonine protein kinases 1 (AKT1) with the active constituent of A. marina against breast cancer were performed. Additionally, a molecular docking study demonstrates that active drugs have a higher affinity for the target that may be used to decrease breast cancer. The molecular dynamic simulation analysis predicted the very stable behavior of docked complexes with no global structure deviations seen. The MMGBSA further supported strong intermolecular interactions with net energy values as; AKT1_Betulinic_acid (−20.97 kcal/mol), AKT1_Stigmasterol (−44.56 kcal/mol), TNF_Betulinic_acid (−28.68 kcal/mol) and TNF_Stigmastero (−29.47 kcal/mol). Communicated by Ramaswamy H. Sarma乳腺癌是全球范围内女性癌症相关死亡的第二大诱因。海榄雌（Avicennia marina）是隶属于爵床科（Acanthaceae）的药用植物，俗称灰红树林或白红树林。其具备抗氧化、抗病毒、抗肿瘤、抗炎及抗菌活性，可用于包括癌症在内的多种疾病的治疗。本研究旨在通过网络药理学（network pharmacology）方法，明确海榄雌生物活性成分在乳腺癌治疗中的潜在作用机制与靶点，并探索相关临床生物化学研究方向。本研究从多个数据库及文献综述中共筛选得到74种海榄雌活性成分，并通过STITCH与Swiss Target Prediction数据库，共鉴定得到对应这74种成分的429个靶点。从GeneCards数据库中获取得到15606个乳腺癌相关潜在靶点。绘制韦恩图以筛选两类靶点的共同关键靶点，最终得到171个关键靶点。通过DAVID数据库对该171个关键靶点开展基因本体（Gene Ontology, GO）功能富集分析与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路富集分析，以解析其生物学功能。为解析关键靶点间的相互作用，本研究通过STRING数据库完成蛋白质-蛋白质相互作用（Protein-Protein Interaction, PPI）分析，并使用Cytoscape 3.9.0构建PPI网络及成分-靶点-通路网络。最终，针对5个核心靶点基因——肿瘤蛋白p53（tumor protein 53, TP53）、β-连环蛋白1（catenin beta 1, CTNNB1）、白细胞介素6（interleukin 6, IL6）、肿瘤坏死因子（tumor necrosis factor, TNF）及RAC-α丝氨酸/苏氨酸蛋白激酶1（RAC-alpha serine/threonine protein kinases 1, AKT1），本研究开展了其与海榄雌抗乳腺癌活性成分的分子对接（molecular docking）分析。此外，分子对接实验结果显示，海榄雌活性成分与对应靶点具有较高结合亲和力，有望用于乳腺癌的干预治疗。分子动力学模拟（molecular dynamic simulation）分析结果表明，对接得到的复合物具备极高稳定性，未观察到整体结构偏移。分子力学/广义玻恩表面积法（Molecular Mechanics/Generalized Born Surface Area, MMGBSA）分析进一步验证了靶点与配体间存在强分子间相互作用，其净结合能如下：AKT1-白桦脂酸（AKT1_Betulinic_acid，−20.97 kcal/mol）、AKT1-豆甾醇（AKT1_Stigmasterol，−44.56 kcal/mol）、TNF-白桦脂酸（TNF_Betulinic_acid，−28.68 kcal/mol）及TNF-豆甾醇（TNF_Stigmasterol，−29.47 kcal/mol）。本文由Ramaswamy H. Sarma转交刊发。