Evidence map›Paper›PMID 36034710›Full record

ArticleFrontiers in cellular and infection microbiology2022

Exploring the mechanism of action of Xuanfei Baidu granule (XFBD) in the treatment of COVID-19 based on molecular docking and molecular dynamics.

Li Xiong, Junfeng Cao, Xingyu Yang, Shengyan Chen, Mei Wu, Chaochao Wang, Hengxiang Xu, Yijun Chen, Ruijiao Zhang, Xiaosong Hu and 7 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.5field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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

17 authors at 2 institutions in 1 country.

Li XiongClinical Medicine, Chengdu Medical College, Chengdu, China.
Junfeng CaoClinical Medicine, Chengdu Medical College, Chengdu, China.
Xingyu YangClinical Medicine, Chengdu Medical College, Chengdu, China.
Shengyan ChenClinical Medicine, Chengdu Medical College, Chengdu, China.
Mei WuClinical Medicine, Chengdu Medical College, Chengdu, China.
Chaochao WangClinical Medicine, Chengdu Medical College, Chengdu, China.
Hengxiang XuClinical Medicine, Chengdu Medical College, Chengdu, China.
Yijun ChenClinical Medicine, Chengdu Medical College, Chengdu, China.
Ruijiao ZhangChengdu Medical College of Basic Medical Sciences, Chengdu, China.
Xiaosong HuChengdu Medical College of Basic Medical Sciences, Chengdu, China.
Tian ChenChengdu Medical College of Basic Medical Sciences, Chengdu, China.
Jing TangDepartment of Infectious Diseases, First People's Hospital of Ziyang, Ziyang, China.
Qin DengDepartment of Infectious Diseases, First People's Hospital of Ziyang, Ziyang, China.
Dong LiClinical Medicine, Chengdu Medical College, Chengdu, China.
Zheng YangChengdu Medical College of Basic Medical Sciences, Chengdu, China.
Guibao XiaoDepartment of Infectious Diseases, First People's Hospital of Ziyang, Ziyang, China.
Xiao ZhangChengdu Medical College of Basic Medical Sciences, Chengdu, China.
Chengdu Medical College · CNThe First People's Hospital of Guiyang · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The Corona Virus Disease 2019 (COVID-19) pandemic has become a challenge of world. The latest research has proved that Methods: We screened out the key active ingredients in XFBD through TCMSP database. Besides GeneCards database was used to search disease gene targets and screen intersection gene targets. The intersection gene targets were analyzed by GO and KEGG. The disease-core gene target-drug network was analyzed and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the number of hydrogen bonds, the binding free energy, the stability of protein target at the residue level, the solvent accessible surface area, and the radius of gyration. Results: XFBD had 1308 gene targets, COVID-19 had 4600 gene targets, the intersection gene targets were 548. GO and KEGG analysis showed that XFBD played a vital role by the signaling pathways of immune response and inflammation. Molecular docking showed that I-SPD, Pachypodol and Vestitol in XFBD played a role in treating COVID-19 by acting on NLRP3, CSF2, and relieve the clinical symptoms of SARS-CoV-2 infection. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets, CSF2/I-SPD combination has the strongest binding energy. Conclusion: For the first time, it was found that the important active chemical components in XFBD, such as I-SPD, Pachypodol and Vestitol, reduce inflammatory response and apoptosis by inhibiting the activation of NLRP3, and reduce the production of inflammatory factors and chemotaxis of inflammatory cells by inhibiting the activation of CSF2. Therefore, XFBD can effectively alleviate the clinical symptoms of COVID-19 through NLRP3 and CSF2.

Indexed as

COVID-19 Drug TreatmentDrugs, Chinese HerbalSARS-CoV-2HumansMedicine, Chinese TraditionalMolecular Docking SimulationMolecular Dynamics SimulationNLR Family, Pyrin Domain-Containing 3 ProteinDrugs, Chinese HerbalNLR Family, Pyrin Domain-Containing 3 Proteinxuanfei baidubioinformatics analysisCOVID-19molecular dockingmolecular dynamicsXuanfei Baidu granule

Identifiers

PMID36034710
PMCPMC9399524
OpenAlexW4290988513

What Socratic 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 Socratic graph.