Evidence map›Paper›PMID 34505138›Full record

ArticleBriefings in bioinformatics2022

Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients.

Hong Wang, Jingqing Zhang, Zhigang Lu, Weina Dai, Chuanjiang Ma, Yun Xiang, Yonghong Zhang

Open access · greenAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 23 citations in OpenAlex.

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  9. (Revista brasileira de farmacognosia : orgao oficial da Sociedade Brasileira de Farmacognosia · 2023
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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

7 authors at 3 institutions in 1 country.

Hong WangChongqing Key Research Laboratory for Drug Metabolism, College of Pharmacy, Chongqing Medical University, Chongqing, 400016, China.
Jingqing ZhangChongqing Key Research Laboratory for Drug Metabolism, College of Pharmacy, Chongqing Medical University, Chongqing, 400016, China.
Zhigang LuDepartment of Neurology, The First People's Hospital of Jingmen affiliated to Hubei Minzu University, Jingmen, 448000, China.
Weina DaiChongqing Key Research Laboratory for Drug Metabolism, College of Pharmacy, Chongqing Medical University, Chongqing, 400016, China.
Chuanjiang MaChongqing Key Research Laboratory for Drug Metabolism, College of Pharmacy, Chongqing Medical University, Chongqing, 400016, China.
Yun XiangGynaecology and Obstetrics, Guangzhou Women and Children's Medical Center, Guangzhou, 510623, China.
Yonghong ZhangChongqing Key Research Laboratory for Drug Metabolism, College of Pharmacy, Chongqing Medical University, Chongqing, 400016, China.ORCID 0000-0001-8574-9288
Chongqing Medical University · CNFirst People’s Hospital of Jingmen · CNGuangzhou Women and Children Medical Center · CN

Funding

Chongqing Natural Science Foundation cstc2020jcyj-msxmX0150Health Commission of Hubei Province of China WJ2021M075Intelligent Medicine Research Project of Chongqing Medical University ZHYX202020National Natural Science Foundation of China 22176020Natural Science Foundation of Hubei Province of China 2020CFB722Science and Technology Planning Project of Jingmen City of China 2020YFZD025Science and Technology Research Program of Chongqing Municipal Education Commission of China KJQN201900440
6 · The paper itself

Abstract

After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein-protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

Indexed as

COVID-19 Drug TreatmentDrug RepositioningMolecular Docking SimulationPandemicsSARS-CoV-2Antiviral AgentsCOVID-19Drugs, Chinese HerbalHumansAntiviral AgentsDrugs, Chinese HerbalCOVID-19disease moduledrug repurposingherbal ingredientsnetwork proximity

Identifiers

PMID34505138
PMCPMC8499921
OpenAlexW3198742822

What Socratic holds

Textmetadata
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.