Evidence map›Paper›PMID 35910782›Full record

ArticleStructural chemistry2022

Identification of SARS-CoV-2 inhibitors through phylogenetics and drug repurposing.

Anamika Mishra, Viswajit Mulpuru, Nidhi Mishra

Open access · bronzeAbstract read
In one paragraph

Article in Structural chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Anamika MishraDepartment of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj, India.
Viswajit MulpuruDepartment of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj, India.
Nidhi MishraDepartment of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj, India.ORCID 0000-0002-6028-7723
Indian Institute of Information Technology Allahabad · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus that has affected the whole world is declared a pandemic by the World Health Organization. Since the emergence of this virus, researchers worldwide have searched for potential antivirals against it. Being an RNA virus, it shows a high rate of mutability and variability in its genome. In the present study, all the reported SARS-CoV-2 genomes isolated from diverse regions of the world available in the GISAID database have been considered for phylogenetic analysis. The strain identified at the root is subjected to phylogenetic analysis with genomes of other known human viruses obtained from NCBI for identifying the nearest viral neighbor. Furthermore, the phylogenetic relationship between various human viruses was used to repurpose the known antiviral drugs towards coronavirus using in silico docking approach. The phylogeny reveals the link of the COVID virus with adenovirus. The known drugs against adenovirus are considered in the present study for drug repurposing through molecular docking analysis. The reference inhibitors of the respective targets were also considered in the docking study. The protein targets, namely protease, endoribonuclease, methyltransferase, phosphatase, and spike protein, are considered for screening with the known drug of adenovirus. Ribavirin, known to treat adenoviral infection, shows the best docking score, suggesting its use as a repurposed drug to treat SARS-CoV-2. Furthermore, the potency of the ribavirin drug is analyzed using molecular dynamics studies. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02019-6.

Indexed as

COVID-19DockingDrug repurposingMolecular dynamicsPhylogeneticsSARS-CoV-2Virtual screening

Identifiers

PMID35910782
PMCPMC9315090
OpenAlexW4287958493

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.