Evidence map›Paper›PMID 32811894›Full record

ArticleCommunications biology2020

Network pharmacology suggests biochemical rationale for treating COVID-19 symptoms with a Traditional Chinese Medicine.

Deng-Hai Zhang, Xue Zhang, Bin Peng, Sheng-Qiong Deng, Yu-Fang Wang, Lin Yang, Kai-Zheng Zhang, Chang-Quan Ling, Kun-Lun Wu

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.7field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Traditional Chinese medicine in COVID-19.Acta pharmaceutica Sinica. B · 2021
    Review
  9. Insights into forsythia honeysuckle (Lianhuaqingwen) capsules: A Chinese herbal medicine repurposed for COVID-19 pandemic.Phytomedicine plus : international journal of phytotherapy and phytopharmacology · 2021
    Review
  10. Review
  11. The mechanism and active compounds of semenFood & nutrition research · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Deng-Hai ZhangShanghai Health Commission Key Lab of Artificial Intelligence (AI)-Based Management of Inflammation and Chronic Diseases, Sino-French Cooperative Central Lab, Shanghai Pudong Gongli Hospital, Secondary Military Medical University, 200135, Shanghai, China. shanghai_zhang@hotmail.com.ORCID http://orcid.org/0000-0002-1154-1078
Xue ZhangShanghai Health Commission Key Lab of Artificial Intelligence (AI)-Based Management of Inflammation and Chronic Diseases, Sino-French Cooperative Central Lab, Shanghai Pudong Gongli Hospital, Secondary Military Medical University, 200135, Shanghai, China.
Bin PengShanghai Health Commission Key Lab of Artificial Intelligence (AI)-Based Management of Inflammation and Chronic Diseases, Sino-French Cooperative Central Lab, Shanghai Pudong Gongli Hospital, Secondary Military Medical University, 200135, Shanghai, China.
Sheng-Qiong DengDepartment of Research Affair Management, Shanghai Pudong Gongli Hospital, Secondary Military Medical University, 200135, Shanghai, China.
Yu-Fang WangPost-graduate Training Base in Shanghai Gongli, Post-Graduate College, Ningxia Medical University, 750004, Yinchuan, Ningxia Province, China.
Lin YangPost-graduate Training Base in Shanghai Gongli, Post-Graduate College, Ningxia Medical University, 750004, Yinchuan, Ningxia Province, China.
Kai-Zheng ZhangThe State Key Laboratory of Bioreactor Engineering, New World Institute of Biotechnology, East China University of Science and Technology, 200237, Shanghai, China.
Chang-Quan LingThe Traditional Chinese Medicines of Changhai Hospital, Secondary Military Medical University, 200433, Shanghai, China.
Kun-Lun WuDepartment of Traditional Chinese Medicine, Shanghai Pudong Gongli Hospital, China, Secondary Military Medical University, 200135, Shanghai, China.
Second Military Medical University · CNNingxia Medical University · CNEast China University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chinese herbal formulas including the lung-cleaning and toxicity-excluding (LCTE) soup have played an important role in treating the ongoing COVID-19 pandemic (caused by SARS-CoV-2) in China. Applying LCTE outside of China may prove challenging due to the unfamiliar rationale behind its application in terms of Traditional Chinese Medicine. To overcome this barrier, a biochemical understanding of the clinical effects of LCTE is needed. Here, we explore the chemical compounds present in the reported LCTE ingredients and the proteins targeted by these compounds via a network pharmacology analysis. Our results indicate that LCTE contains compounds with the potential to directly inhibit SARS-CoV-2 and inflammation, and that the compound targets proteins highly related to COVID-19's main symptoms. We predict the general effect of LCTE is to affect the pathways involved in viral and other microbial infections, inflammation/cytokine response, and lung diseases. Our work provides a biochemical basis for using LCTE to treat COVID-19 and its main symptoms.

Indexed as

Medicine, Chinese TraditionalPandemicsAnti-Inflammatory AgentsAntiviral AgentsBetacoronavirusCalcium SulfateChinaCoronavirus InfectionsCOVID-19COVID-19 Drug TreatmentDrug Delivery SystemsDrugs, Chinese HerbalGastrointestinal TractHumansMetabolic Networks and PathwaysPhytotherapyAnti-Inflammatory AgentsAntiviral AgentsCalcium SulfateDrugs, Chinese Herbalqing fei pai du tangViral Proteins

Identifiers

PMID32811894
PMCPMC7434773
OpenAlexW3077953480

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.