Evidence map›Paper›PMID 34105049›Full record

ArticleMolecular diversity2022

Investigating the active compounds and mechanism of HuaShi XuanFei formula for prevention and treatment of COVID-19 based on network pharmacology and molecular docking analysis.

Juan Wang, Wen Ge, Xin Peng, Lixia Yuan, Shuaibing He, Xuyan Fu

Abstract read
In one paragraph

Article in Molecular diversity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Observational
  2. Article
  3. In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review.Advances in pharmacological and pharmaceutical sciences · 2023
    Review
  4. Influence of Harvest Time on the Chemical Profile ofMolecules (Basel, Switzerland) · 2022
    Article
  5. Review
  6. 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

6 authors.

Juan Wang *Zhejiang Pharmaceutical College, Zhejiang Province, Ningbo, 315100, People's Republic of China.
Wen Ge *Zhejiang Pharmaceutical College, Zhejiang Province, Ningbo, 315100, People's Republic of China.
Xin PengNingbo Research Institute of Zhejiang University, Zhejiang Province, Ningbo, 315100, People's Republic of China. pengx@nit.zju.edu.cn.ORCID http://orcid.org/0000-0002-6168-9505
Lixia YuanZhejiang Pharmaceutical College, Zhejiang Province, Ningbo, 315100, People's Republic of China.
Shuaibing HeKey Laboratory of Vector Biology and Pathogen Control of Zhejiang Province, School of Medicine, Huzhou University, Huzhou Central Hospital, Huzhou, People's Republic of China.
Xuyan FuKey Laboratory of Vector Biology and Pathogen Control of Zhejiang Province, School of Medicine, Huzhou University, Huzhou Central Hospital, Huzhou, People's Republic of China.

Funding

Natural Science Foundation of Zhejiang Province LQ19C020003Ningbo City Science and Technology Innovation 2025 Major Research Project 2019B10008Ningbo Natural Science Foundation Project 2019A610370,2017A610263Ningbo Public Welfare Science and Technology Project 2019C50064The Science and Technology Program of Fuzhou 2018-N-9The scientific research projects of Zhejiang Pharmaceutical College XY2020003,2019010Zhejiang Province Public Welfare Technology Application Research Project (CN) LGN18B020001,LGF20H280009
6 · The paper itself

Abstract

Traditional Chinese medicine (TCM) has exerted positive effects in controlling the COVID-19 pandemic. HuaShi XuanFei Formula (HSXFF) was developed to treat patients with mild and general COVID-19 in Zhejiang Province, China. The present study seeks to explore its potentially active compounds and pharmacological mechanisms against COVID-19 based on network pharmacology, molecular docking, and molecular dynamics (MD) simulation. All components of HSXFF were harvested from the pharmacology database of the TCMSP system. COVID-19-related targets were retrieved from using OMIM and GeneCards databases. The herb-compound-targets network was constructed by Cytoscape. The target protein-protein interaction (PPI) network, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to discover the potential key target genes and mechanism. The main active compounds of HSXFF were docked with 3C-like (3CL) protease hydrolase and angiotensin-converting enzyme 2 (ACE2). The MD simulation confirmed the binding stability of docking results. The herbs-targets network mainly contained 52 compounds and 70 corresponding targets, including key targets such as RELA, TNF, TP53, IL6, MAPK1, CXCL8, IL-1β, and MAPK14. The GO and KEGG indicated that HSXFF may be mainly acting on the IL-17 signaling pathway, TNF signaling pathway, NF-κB signaling pathway, etc. The molecular docking results indicated that isovitexin and procyanidin B1 showed the highest affinity with 3CL and ACE2, respectively, which were confirmed by MD simulation. These findings suggested HSXFF exerted therapeutic effects involving "multi-compounds and multi-targets." It might be working through directly inhibiting the virus, improving immune function, and reducing the inflammatory in response to anti-COVID-19. In summary, the present study would provide a valuable direction for further research of HSXFF.

Indexed as

COVID-19 Drug TreatmentDrugs, Chinese HerbalAngiotensin-Converting Enzyme 2HumansMolecular Docking SimulationNetwork PharmacologyPandemicsSARS-CoV-2Angiotensin-Converting Enzyme 2Drugs, Chinese HerbalCOVID-19HuaShi XuanFei formulaMolecular dockingNetwork pharmacologySARS-CoV-2

Identifiers

PMID34105049
PMCPMC8187140

What OpenQuestion holds

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Registered trials

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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.