Evidence map›Paper›PMID 33519272›Full record

ArticleSaudi journal of biological sciences2021

Zarlish Attique, Ashaq Ali, Muhammad Hamza, Khalid A Al-Ghanim, Azhar Mehmood, Sajid Khan, Zubair Ahmed, Norah Al-Mulhm, Muhammad Rizwan, Anum Munir and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Saudi journal of biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

14 authors at 4 institutions in 3 countries.

Zarlish AttiqueUniversity of Chinese Academy of Sciences, Beijing, 100049, China.
Ashaq AliUniversity of Chinese Academy of Sciences, Beijing, 100049, China.
Muhammad HamzaUniversity of Chinese Academy of Sciences, Beijing, 100049, China.
Khalid A Al-GhanimDepartment of Zoology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Azhar MehmoodUniversity of Chinese Academy of Sciences, Beijing, 100049, China.
Sajid KhanUniversity of Chinese Academy of Sciences, Beijing, 100049, China.
Zubair AhmedDepartment of Zoology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Norah Al-MulhmDepartment of Zoology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Muhammad RizwanUniversity of Chinese Academy of Sciences, Beijing, 100049, China.
Anum MunirUniversity of Chinese Academy of Sciences, Beijing, 100049, China.
Emin Al-SulimanDepartment of Zoology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Muhammad FarooqDepartment of Zoology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Al-Misned FDepartment of Zoology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
Shahid MahboobDepartment of Zoology, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia.
King Saud University · SAUniversity of Chinese Academy of Sciences · CNAbbottabad University of Science and Technology · PKWuhan Institute of Virology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionResearchers worldwide with great endeavor searching and repurpose drugs might be potentially useful in fighting newly emerged coronavirus. These drugs show inhibition but also show side effects and complications too. On December 27, 2020, 80,926,235 cases have been reported worldwide. Specifically, in Pakistan, 471,335 has been reported with inconsiderable deaths. PROBLEM STATEMENT: Identification of COVID-19 drugs pathway through drug-gene and gene-gene interaction to find out the most important genes involved in the pathway to deal with the actual cause of side effects beyond the beneficent effects of the drugs. METHODOLOGY: The medicines used to treat COVID-19 are retrieved from the Drug Bank. The drug-gene interaction was performed using the Drug Gene Interaction Database to check the relation between the genes and the drugs. The networks of genes are developed by Gene MANIA, while Cytoscape is used to check the active functional association of the targeted gene. The developed systems cross-validated using the EnrichNet tool and identify drug genes' concerned pathways using Reactome and STRING.

resultsFive drugs Azithromycin, Bevacizumab, CQ, HCQ, and Lopinavir, are retrieved. The drug-gene interaction shows several genes that are targeted by the drug. Gene MANIA interaction network shows the functional association of the genes like co-expression, physical interaction, predicted, genetic interaction, co-localization, and shared protein domains.

conclusionOur study suggests the pathways for each drug in which targeted genes and medicines play a crucial role, which will help experts

Indexed as

COVID-19Drug-interactionsGene-analysisInteraction networksPathways

Identifiers

PMID33519272
PMCPMC7825994
OpenAlexW3124799094

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.