Lu Yi-Chin, Tseng Liang-Wei, Huang Yu-Chieh, Yang Ching-Wei, Chen Yu-Chun, Chen Hsing-Yu
Division of Chinese Internal Medicine, Center for Traditional Chinese Medicine, Chang Gung Memorial Hospital, Taoyuan 33378, Taiwan.
Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Keelung 20401, Taiwan.
Pharmaceuticals (Basel). 2022 Jun 26;15(7):794. doi: 10.3390/ph15070794.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic in 2019-coronavirus disease (COVID-19). More and more Western medicine (WM) and Chinese herbal medicine (CHM) treatments have been used to treat COVID-19 patients, especially among Asian populations. However, the interactions between WM and CHM have not been studied. This study aims at using the network pharmacology approach to explore the potential complementary effects among commonly used CHM and WM in a clinical setting from a biomolecular perspective. Three well-published and widely used CHM formulas (National Research Institute of Chinese Medicine 101 (NRICM101), Qing-Fei-Pai-Du-Tang (QFPDT), Hua-Shi-Bai-Du-Formula (HSBDF)) and six categories of WM (Dexamethasone, Janus kinase inhibitors (JAKi), Anti-Interleukin-6 (Anti-IL6), anticoagulants, non-vitamin K antagonist oral anticoagulants (NOAC), and Aspirin) were included in the network pharmacology analysis. The target proteins on which these CHM and WM had direct effects were acquired from the STITCH database, and the potential molecular pathways were found in the REACTOME database. The COVID-19-related target proteins were obtained from the TTD database. For the three CHM formulas, QFPDT covered the most proteins (714), and 27 of them were COVID-19-related, while HSBDF and NRICM101 covered 624 (24 COVID-19-related) and 568 (25 COVID-19-related) proteins, respectively. On the other hand, WM covered COVID-19-related proteins more precisely and seemed different from CHM. The network pharmacology showed CHM formulas affected several inflammation-related proteins for COVID-19, including IL-10, TNF-α, IL-6, TLR3, and IL-8, in which Dexamethasone and Aspirin covered only IL-10 and TNF-α. JAK and IL-6 receptors were only inhibited by WM. The molecular pathways covered by CHM and WM also seemed mutually exclusive. WM had advantages in cytokine signaling, while CHM had an add-on effect on innate and adaptive immunity, including neutrophil regulation. WM and CHM could be used together to strengthen the anti-inflammation effects for COVID-19 from different pathways, and the combination of WM and CHM may achieve more promising results. These findings warrant further clinical studies about CHM and WM use for COVID-19 and other diseases.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引发了2019冠状病毒病(COVID-19)全球大流行。越来越多的西医(WM)和中药(CHM)疗法被用于治疗COVID-19患者,尤其是在亚洲人群中。然而,西医和中药之间的相互作用尚未得到研究。本研究旨在运用网络药理学方法,从生物分子角度探索临床环境中常用中药和西药之间潜在的互补作用。网络药理学分析纳入了三个已发表且广泛使用的中药方剂(国立中国医药研究所101方(NRICM101)、清肺排毒汤(QFPDT)、化湿败毒方(HSBDF))和六类西药(地塞米松、Janus激酶抑制剂(JAKi)、抗白细胞介素-6(Anti-IL6)、抗凝剂、非维生素K拮抗剂口服抗凝剂(NOAC)和阿司匹林)。这些中药和西药具有直接作用的靶蛋白从STITCH数据库中获取,潜在的分子途径在REACTOME数据库中找到。COVID-19相关的靶蛋白从TTD数据库中获取。对于这三个中药方剂,QFPDT覆盖的蛋白最多(714个),其中27个与COVID-19相关,而HSBDF和NRICM101分别覆盖624个(24个与COVID-19相关)和568个(25个与COVID-19相关)蛋白。另一方面,西药更精确地覆盖了与COVID-19相关的蛋白,且似乎与中药不同。网络药理学显示,中药方剂影响了几种与COVID-19相关的炎症蛋白,包括白细胞介素-10(IL-10)、肿瘤坏死因子-α(TNF-α)、白细胞介素-6(IL-6)、Toll样受体3(TLR3)和白细胞介素-8(IL-8),其中地塞米松和阿司匹林仅覆盖IL-10和TNF-α。JAK和白细胞介素-6受体仅被西药抑制。中药和西药覆盖的分子途径似乎也相互排斥。西药在细胞因子信号传导方面具有优势,而中药对固有免疫和适应性免疫具有附加作用,包括中性粒细胞调节。西药和中药可以联合使用,从不同途径增强对COVID-19的抗炎作用,中西医结合可能会取得更有前景的结果。这些发现值得对中西医结合治疗COVID-19及其他疾病进行进一步的临床研究。