OPEN Mechanisms of breast cancer treatment using Gentiana robusta: evidence from comprehensive bioinformatics investigation
OPEN 使用罗布斯塔龙胆治疗乳腺癌的机制：来自综合生物信息学调查的证据

This study investigates the potential treatment of breast cancer utilizing Gentiana robusta King ex Hook. f. (QJ) through an integrated approach involving network pharmacology, molecular docking, and molecular dynamics simulation. Building upon prior research on $Q$$Q$QQ ‘s chemical constituents, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using the DAVID database. Network interactions and core genes were identified using Cytoscape 3.9.1. Key target genes, including Interleukin-6 (IL-6), tumour suppressor gene P53 (TP53), and epidermal growth factor receptor (EGFR), were selected for molecular docking with Q’s active components, 2’-O- $\beta$$\beta$beta\beta-D-glucopyranosyl-gentiopicroside and macrophylloside $D$$D$DD, employing Schrodinger Maestro 13.5. Molecular dynamics (MD) simulations were performed using the Desmond program. A total of 270 intersection targets of active ingredients and diseases were identified, with three core targets determined through network topology screening. Enrichment analysis highlighted the involvement of $QJ$$QJ$QJQ J in breast cancer treatment, primarily through the hsa05200 cancer signaling pathway and the hsa04066 HIF-1 signaling pathway. Molecular docking and dynamics simulations demonstrated the close interaction of 2’-O- $\beta$$\beta$beta\beta-D-glucopyranosyl-gentiopicroside (OJ17) and macrophylloside D (OJ25) with IL6, TP53, and EGFR, and other target genes, showcasing a stabilizing effect. In conclusion, this study unveils the effective components and potential mechanisms of $2^{\prime }$$2^{\prime }$2^(')2^{\prime}-O- $\beta$$\beta$beta\beta-D-glucopyranosyl-gentiopicroside and macrophylloside $D$$D$DD in breast cancer prevention and treatment. The identified components act on target genes such as IL6, TP53, and EGFR, regulating crucial pathways including the cancer signaling and Hypoxia-inducible factor 1 (HIF-1) signaling pathways. These findings provide valuable insights into the therapeutic potential of QJ in breast cancer management. However, further experimental research are needed to validate the computational findings of QJ .
本研究调查了利用 Gentiana robusta King ex Hook 治疗乳腺癌的潜在方法。f. （QJ） 通过涉及网络药理学、分子对接和分子动力学模拟的综合方法。在先前对 $Q$$Q$QQ 化学成分的研究基础上，我们使用 DAVID 数据库进行了基因本体论 （GO） 和京都基因与基因组百科全书 （KEGG） 通路分析。使用 Cytoscape 3.9.1 鉴定网络相互作用和核心基因。选择关键靶基因，包括白细胞介素-6 （IL-6）、肿瘤抑制基因 P53 （TP53） 和表皮生长因子受体 （EGFR），与 Q 的活性成分 2'-O- $\beta$$\beta$beta\beta --D-吡喃葡萄糖基-龙胆苦子苷和大叶糖苷 $D$$D$DD 进行分子对接，采用 Schrodinger Maestro 13.5。使用 Desmond 程序进行分子动力学 （MD） 模拟。共确定了 270 个有效成分与病害的交叉靶点，其中 3 个核心靶点通过网络拓扑筛选确定。富集分析突出了 参与 $QJ$$QJ$QJQ J 乳腺癌治疗，主要通过 hsa05200 癌症信号通路和 hsa04066 HIF-1 信号通路。分子对接和动力学模拟表明，2'-O- $\beta$$\beta$beta\beta 吡喃葡萄糖基-龙胆苦苷 （OJ17） 和大叶糖苷 D （OJ25） 与 IL6 、 TP53 和 EGFR 等靶基因密切相互作用，显示出稳定作用。总之，本研究揭示了 $2^{\prime }$$2^{\prime }$2^(')2^{\prime} -O- $\beta$$\beta$beta\beta -D-吡喃葡萄糖基龙胆苷和大叶糖苷 $D$$D$DD 在乳腺癌预防和治疗中的有效成分和潜在机制。 已鉴定的成分作用于 IL6、TP53 和 EGFR 等靶基因，调节关键通路，包括癌症信号传导和缺氧诱导因子 1 （HIF-1） 信号通路。这些发现为 QJ 在乳腺癌管理中的治疗潜力提供了有价值的见解。然而，需要进一步的实验研究来验证 QJ 的计算结果。

Keywords Gentiana robusta, Breast cancer, Network pharmacology, Molecular docking, Molecular dynamics simulation
关键词 罗布斯塔龙胆， 乳腺癌， 网络药理学， 分子对接， 分子动力学模拟

Breast cancer has emerged as the predominant female malignancy, surpassing lung cancer to claim the title of the most common cancer globally ${}^1$${}^1$^(1){ }^{1}. The escalating incidence, attributed to heightened exposure to risk factors, underscores the urgent need for effective treatments. In the realm of clinical intervention, individualized approaches such as surgery, radiotherapy, chemotherapy, endocrine therapy, and molecular targeted therapy are the primary means of treatment.
乳腺癌已成为主要的女性恶性肿瘤，超过肺癌成为全球 ${}^1$${}^1$^(1){ }^{1} 最常见的癌症。由于暴露于风险因素的增加，发病率不断上升，凸显了对有效治疗的迫切需求。在临床干预领域，手术、放疗、化疗、内分泌治疗和分子靶向治疗等个体化方法是主要的治疗手段。

Despite the prevalent use of various drug therapies, Western medicines employed in breast cancer treatment often come with severe adverse reactions, including liver and kidney toxicity, gastrointestinal issues, allergic reactions, and bone marrow suppression. Recognizing these challenges, the medical community is turning its attention towards alternative approaches, particularly Traditional Chinese medicine (TCM) and other natural
尽管广泛使用各种药物治疗，但用于乳腺癌治疗的西药往往伴随着严重的不良反应，包括肝肾毒性、胃肠道问题、过敏反应和骨髓抑制。认识到这些挑战，医学界正在将注意力转向替代方法，特别是中医 （TCM） 和其他天然方法

drugs. These modalities offer notable advantages, including high efficacy, fewer side effects, and the ability to target multiple pathways.
药物。这些方式具有显着优势，包括疗效高、副作用少以及靶向多种途径的能力。

The promising prospects of TCM and natural drugs in anti-tumor treatments have positioned them as focal points in the ongoing research and development of anticancer drugs ${}^{2,3}$${}^{2,3}$^(2,3){ }^{2,3}. This shift towards exploring diverse treatment modalities reflects the growing recognition of the need for holistic and personalized approaches to tackle the complex challenges posed by breast cancer.
中医和天然药物在抗肿瘤治疗中的光明前景使其成为抗癌药物 ${}^{2,3}$${}^{2,3}$^(2,3){ }^{2,3} 持续研发的重点。这种探索不同治疗方式的转变反映了人们越来越认识到需要整体和个性化的方法来应对乳腺癌带来的复杂挑战。

China’s abundance in natural medicinal resources is complemented by the diversity of its traditional ethnic medicines, with Tibetan medicine standing as a significant component of Chinese traditional medicine. Our research group has undertaken multiple expeditions to the Qinghai-Tibet Plateau throughout the year, aiming to collect scientific research samples and explore the rich tapestry of Tibetan medicinal resources.
中国丰富的天然药用资源与传统民族医学的多样性相辅相成，藏医是中国传统医学的重要组成部分。我们的研究小组全年多次前往青藏高原进行考察，旨在收集科研样本，探索藏族丰富的药材资源。

Amidst the myriad of medicinal plants, QJ emerged as a focal point of our attention. This perennial herb, belonging to Sect. Cruciata Gaudin of Gentiana genus, thrives in the southern Tibetan region. Revered as one of the original plant sources in “Jieji” Tibetan medicine, QJ boasts a storied history of medicinal usage. Known for its therapeutic effects in dispelling wind and dampness, clearing heat and the gallbladder, soothing tendons, and relieving pain, it has found extensive clinical application in treating conditions such as rheumatoid arthritis, low-fever night sweats, jaundice hepatitis, various forms of bleeding, swelling, and other “Chi-ba” diseases ${}^{4-6}$${}^{4-6}$^(4-6){ }^{4-6}.
在无数的药用植物中，QJ 成为我们关注的焦点。这种多年生草本植物，属于 Sect.龙胆属的 Cruciata Gaudin 在藏族南部地区茁壮成长。QJ 被尊为藏医“解记”的原始植物来源之一，拥有悠久的药用历史。以其祛风祛湿、清热、清胆、舒缓筋腱和止痛的治疗作用而闻名，在治疗类风湿性关节炎、低烧盗汗、黄疸肝炎、各种形式的出血、肿胀和其他“赤巴”疾病 ${}^{4-6}$${}^{4-6}$^(4-6){ }^{4-6} 等方面得到了广泛的临床应用。

Notably, QJ serves as a primary raw material for several proprietary Chinese medicines, including Shisanwei Bang-Ga powder, Ershiwuwei Datang pills, and more ${}^7$${}^7$^(7){ }^{7}. This underscores its significance not only in traditional Tibetan medicine but also in the broader landscape of Chinese herbal formulations.
值得注意的是，QJ 是多种中成药的主要原料，包括石三味 Bang-Ga 粉、二食味大唐丸等 ${}^7$${}^7$^(7){ }^{7} 。这不仅强调了它在传统藏医中的重要性，而且在更广泛的中草药配方中也强调了它的重要性。

In essence, the exploration of QJ and Tibetan medicine not only contributes to our understanding of traditional healing practices but also holds promise for the development of novel therapeutic interventions. The unique ecological context of the Qinghai-Tibet Plateau adds an extra layer of richness to the potential discoveries in the realm of medicinal plants and their applications.
从本质上讲，对 QJ 和藏医的探索不仅有助于我们对传统治疗实践的理解，而且为开发新的治疗干预措施带来了希望。青藏高原独特的生态背景为药用植物及其应用领域的潜在发现增添了额外的丰富性。

To date, research on QJ has primarily centered on the identification of raw materials, with limited attention given to specific components such as gentiopicroside, loganic acid, swertiamarin, other iridoid terpenoids, roburic acid, and stigmasterol ${}^8$${}^8$^(8){ }^{8}. In order to delve deeper into the contemporary pharmacological actions and clinical applications of QJ, we employed ultra-high-performance liquid chromatography-electrospray ionization with quadrupole time-of-flight tandem mass spectrometry (UHPLC-ESI-Q-TOF-MS/MS) technology for a comprehensive analysis of its chemical composition ${}^9$${}^9$^(9){ }^{9}.
迄今为止，对 QJ 的研究主要集中在原材料的鉴定上，对特定成分的关注有限，例如龙胆苦苷、洛甘酸、獐牙菌素、其他环烯醚萜类化合物、roburic acid 和 stigastrool ${}^8$${}^8$^(8){ }^{8} 。为了更深入地研究QJ的当代药理作用和临床应用，我们采用了超高效液相色谱-电喷雾电离-四极杆飞行时间串联质谱（UHPLC-ESI-Q-TOF-MS/MS）技术对其化学成分 ${}^9$${}^9$^(9){ }^{9} 进行了综合分析。

The association between inflammation and tumors is well-established, with inflammation recognized as the eighth biological feature in malignant tumors, influencing their occurrence, development, invasion, and metastasis ${}^{10,11}$${}^{10,11}$^(10,11){ }^{10,11}. In this context, QJ’s role in managing inflammatory conditions becomes particularly relevant in the broader framework of cancer research.
炎症与肿瘤之间的关联是公认的，炎症被认为是恶性肿瘤的第八个生物学特征，影响其发生、发展、侵袭和转移 ${}^{10,11}$${}^{10,11}$^(10,11){ }^{10,11} 。在这种情况下，QJ 在管理炎症状况方面的作用在更广泛的癌症研究框架中变得尤为重要。

Natural medicine is inherently complex, featuring numerous components, targets, and action pathways. Network pharmacology has proven instrumental in understanding the relationship between TCM and modern pharmacology, providing insights into the overall mechanisms of action for TCM compounds and facilitating the analysis of drug compatibility laws and formulations. This innovative approach sparks new ideas for studying intricate TCM systems ${}^{12,13}$${}^{12,13}$^(12,13){ }^{12,13}.
天然医学本质上是复杂的，具有许多成分、靶标和作用途径。事实证明，网络药理学有助于理解中医与现代药理学之间的关系，为中药化合物的整体作用机制提供见解，并促进药物相容性规律和配方的分析。这种创新方法激发了研究复杂中医系统 ${}^{12,13}$${}^{12,13}$^(12,13){ }^{12,13} 的新思路。

Molecular docking technology, a simulation method predicting the interaction between small molecule ligands and receptors, along with MD simulation, addressing dynamic molecular behavior, are integral tools in drug design. The combination of these approaches enhances the precision and efficiency of drug design, contributing to the discovery of novel drugs and elucidating the mechanisms underlying drug treatments ${}^{14,15}$${}^{14,15}$^(14,15){ }^{14,15}.
分子对接技术是一种预测小分子配体和受体之间相互作用的模拟方法，以及解决动态分子行为的 MD 模拟，是药物设计中不可或缺的工具。这些方法的结合提高了药物设计的精度和效率，有助于发现新药并阐明药物治疗的潜在机制 ${}^{14,15}$${}^{14,15}$^(14,15){ }^{14,15} 。

In this study, we aimed to unravel the potential breast cancer-resistant mechanism of QJ. Employing state-of-the-art UHPLC-ESI-Q-TOF-MS/MS detection, we meticulously determined the chemical composition of QJ. Additionally, we harnessed the power of network pharmacology, molecular docking, and MD simulation, utilizing diverse biological information analysis methods ${}^{16}$${}^{16}$^(16){ }^{16}.
在这项研究中，我们旨在揭示 QJ 的潜在乳腺癌耐药机制。采用最先进的 UHPLC-ESI-Q-TOF-MS/MS 检测，我们仔细测定了 QJ 的化学成分。此外，我们利用网络药理学、分子对接和 MD 模拟的力量，利用了多种生物信息分析方法 ${}^{16}$${}^{16}$^(16){ }^{16} 。

To identify the active components linked to breast cancer target genes, an exhaustive screening process was conducted on QJ. Subsequently, molecular docking and MD simulation were employed to predict the binding sites of small molecule active components with target genes.
为了确定与乳腺癌靶基因相关的活性成分，对 QJ 进行了详尽的筛选过程。随后，采用分子对接和 MD 模拟预测小分子活性成分与靶基因的结合位点。

The flowchart showing the outline of this study is presented in Fig. 1. Based on our previous studies on the chemical composition analysis of QJ, all 39 compounds in QJ(Table S1) were selected for the prediction of biological targets. Using the PubChem database, (https://pubchem.ncbi.nlm.nih.gov/) information regarding the 39 active ingredients was retrieved. The 2D SDF file was input to the Swiss Target Prediction platform ${}^{17}$${}^{17}$^(17){ }^{17}, with an aim-listed probability threshold of 0.1 or higher. Additionally, the active ingredient target was screened. The MalaCards (https://www.malacards.org/), OMIM (https://omim.org/), and DisGeNET (https://www.disgenet.org/) databases were utilized ${}^{18}$${}^{18}$^(18){ }^{18}. Furthermore, to obtain the disease target genes, “breast cancer” was applied as the search term and the species was set to human.
显示本研究大纲的流程图如图 1 所示。根据我们前人对 QJ 化学成分分析的研究，选择了 QJ 中的 39 种化合物（表 S1）用于生物靶点的预测。使用 PubChem 数据库，检索了有关 39 种活性成分的 （https://pubchem.ncbi.nlm.nih.gov/） 信息。2D SDF 文件被输入到 Swiss Target Prediction 平台 ${}^{17}$${}^{17}$^(17){ }^{17} ，目标列表概率阈值为 0.1 或更高。此外，还筛选了活性成分靶标。使用了 ${}^{18}$${}^{18}$^(18){ }^{18} MalaCards （https://www.malacards.org/）、OMIM （https://omim.org/） 和 DisGeNET （https://www.disgenet.org/） 数据库。此外，为了获得疾病靶基因，将 “breast cancer” 作为搜索词，并将物种设置为 human。

The targets of the screened active ingredients were intersected with the targets of breast cancer and imported into Venny 2.1 software. They were then displayed on a Venn diagram and used as potential targets of drug action for subsequent analysis. To better understand the complex relationship between the active ingredients of TCM and the corresponding disease targets, a composition-target-disease network map was constructed using Cytoscape 3.9.1 software. This network map was based on the QJ active ingredients, active ingredient targets, and breast cancer disease targets.
将筛选的活性成分的靶点与乳腺癌的靶点相交，并导入 Venny 2.1 软件。然后将它们显示在维恩图上，并用作药物作用的潜在靶标进行后续分析。为了更好地了解中药活性成分与相应疾病靶点之间的复杂关系，使用 Cytoscape 3.9.1 软件构建了成分-靶点-疾病网络图谱。该网络图基于 QJ 活性成分、活性成分靶点和乳腺癌疾病靶点。

Fig. 1. Flowchart of this study.
图 1.本研究的流程图。

The QJ active ingredients and common breast cancer disease targets were imported into DAVID Bioinformatics Resources 6.8 (https://david.ncifcrf.gov/home.jsp) for KEGG and GO pathway enrichment analysis. With $\mathrm{P}<0.05$$\mathrm{P}<0.05$P < 0.05\mathrm{P}<0.05 as the threshold, the top ten enrichment items were displayed in both a column chart and a bubble chart. The KEGG database was used to map the proteins associated with the relevant signaling pathways to the KEGG pathway.
将 QJ 活性成分和常见的乳腺癌疾病靶点导入 DAVID Bioinformatics Resources 6.8 （https://david.ncifcrf.gov/home.jsp） 进行 KEGG 和 GO 通路富集分析。作为 $\mathrm{P}<0.05$$\mathrm{P}<0.05$P < 0.05\mathrm{P}<0.05 阈值，前 10 个扩充项同时显示在柱形图和气泡图中。使用 KEGG 数据库将与相关信号通路相关的蛋白质映射到 KEGG 通路。