口腔疾病防治 ›› 2022, Vol. 30 ›› Issue (7): 464-474.DOI: 10.12016/j.issn.2096-1456.2022.07.002

• 基础研究 • 上一篇    下一篇

基于数据挖掘、网络药理学和分子对接的中药治疗牙周疾病的用药规律与作用机制

李新尚(), 牛巧丽, 赵今()   

  1. 新疆医科大学第一附属医院(附属口腔医院)牙体牙髓科,新疆维吾尔自治区 乌鲁木齐(830054)
  • 收稿日期:2021-10-26 修回日期:2021-12-26 出版日期:2022-07-20 发布日期:2022-04-25
  • 通讯作者: 赵今
  • 作者简介:李新尚,主治医师,硕士,Email: 330630787@qq.com
  • 基金资助:
    新疆维吾尔自治区自然科学基金项目(2016D01C315);中华口腔医学会西部口腔医学临床科研基金项目(CSA-W2021-02)

Exploration of medication rules and mechanisms of traditional Chinese medicine in the treatment of periodontal disease based on data mining, network pharmacology, and molecular docking

LI Xinshang(), NIU Qiaoli, ZHAO Jin()   

  1. Department of Endodontics, the First Affiliated Hospital of Xinjiang Medical University (Affiliated Stomatology Hospital), Urumqi 830054, China
  • Received:2021-10-26 Revised:2021-12-26 Online:2022-07-20 Published:2022-04-25
  • Contact: ZHAO Jin
  • Supported by:
    Natural Science Foundation of Xinjiang Uygur Autonomous Region(2016D01C315);Western Stomatology Clinical Research Fund Project of Chinese Stomatological Association(CSA-W2021-02)

摘要:

目的 通过数据挖掘、网络药理学和分子对接探讨中药复方治疗牙周疾病的用药规律及其作用机制。方法 首先,数据挖掘搜索治疗牙周疾病的单味药材,并筛选活性成分及其作用靶点。然后,利用疾病靶点数据库下载牙周疾病发病机制相关的靶点,与中药复方的作用靶点去映射,获取被认为中药复方治疗牙周疾病的潜在靶点,并对潜在靶点进行基因本体功能和信号通路分析。潜在靶点再通过筛选获取治疗牙周疾病的关键靶点。最后,将活性成分与关键靶点进行分子对接。 结果 治疗牙周疾病的中药复方中熟地黄、牡丹皮、当归、茯苓、金银花、山药、知母等药材的出现频率最高,筛选得到43个活性成分及其118个作用靶点,并与856个疾病靶点进行交集得到52个潜在靶点。潜在靶点可能参与的分子功能和生物学过程主要集中在维生素D生物合成过程和对RNA聚合酶Ⅱ调控,并涉及96条信号通路。52个潜在靶点通过网络拓扑参数分析,得到11个关键靶点。分子对接结果表明,活性成分与α-丝氨酸/苏氨酸蛋白激酶(RAC-alpha serine/threonine-protein kinase,AKT1)、细胞肿瘤抗原p53(cellular tumor antigen p53,TP53)和丝裂原活化蛋白激酶-1(mitogen-activated protein kinase-1,MAPK-1)等关键靶点具有较好的结合活性。 结论 中药复方可能通过抑制牙槽骨吸收、抗菌、抗炎和促进组织修复功能,从而发挥治疗牙周疾病的作用,为中药复方的有效治疗牙周疾病提供更加科学性的参考。

关键词: 中药复方, 熟地黄, 牡丹皮, 当归, 茯苓, 牙周疾病, 牙周炎, 分子对接, 细胞肿瘤抗原p53, 丝裂原活化蛋白激酶-1, 网络药理学, 数据挖掘, 活性成分, 潜在靶点, 维生素D合成, “Lipinski”规则

Abstract:

Objective To explore the medication law and mechanism of traditional Chinese medicine compounds in the treatment of periodontal disease through data mining, network pharmacology, and molecular docking. Methods First, data mining was used to search single medicinal materials for the treatment of periodontal disease, and the active components and their action targets were screened. Second, the disease target database was employed to download the targets related to the pathogenesis of periodontal disease, map them with the action targets of traditional Chinese medicine, and obtain the targets that are considered potential targets of traditional Chinese medicine in the treatment of periodontal disease. Potential targets were analyzed for gene ontology function and signaling pathway. They were then screened to obtain the key targets for the treatment of periodontal disease. Finally, the active components were docked with key targets. Results Among the traditional Chinese medicine prescriptions for the treatment of periodontal disease, Shudihuang, Mudanpi, Danggui, Fuling, Jinyinhua, Shanyao and Zhimu had the highest frequencies. Forty-three active components and 118 action targets were screened, and 52 potential targets were obtained by intersection with 856 disease targets. The molecular functions and biological processes in which potential targets may participate mainly focus on vitamin D biosynthesis and RNA polymerase Ⅱ regulation and involve 96 signaling pathways. Through the analysis of network topology parameters, 11 key targets were obtained. The results of molecular docking showed that the active components and RAC-alpha serine/threonine-protein kinase (AKT1), cellular tumor antigen p53 (TP53), and mitogen-activated protein kinase-1 (MAPK-1) have good binding activity. Conclusion Traditional Chinese medicine compounds may play a role in the treatment of periodontal disease by inhibiting alveolar bone absorption, have antibacterial and anti-inflammatory properties, and promote tissue repair. The effective treatment of periodontal disease by traditional Chinese medicine compounds provides a more scientific reference to the sustainable development of traditional Chinese medicine.

Key words: traditional Chinese medicine, Shudihuang, Mudanpi, Danggui, Fuling, periodontal disease, periodontitis, molecular docking, cellular tumor antigen p53, mitogen-activated protein kinase-1, network pharmacology, data mining, active ingredient, potential targets, vitamin D synthesis, "Lipinski" rule

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