Evidence map›Paper›PMID 34003827›Full record

ArticlePloS one2021

Computational designing of a peptide that potentially blocks the entry of SARS-CoV, SARS-CoV-2 and MERS-CoV.

Priya V K, Satish Prasad Rath, Parvin Abraham

Abstract read
In one paragraph

Article in PloS one, 2021. 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
–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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. RSC advances · 2022
    Article
  6. Article
  7. 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.

Priya V KNational Institute of Technology, Calicut, Kerala, India.
Satish Prasad RathMIMS Research Foundation, Calicut, Kerala, India.
Parvin AbrahamMIMS Research Foundation, Calicut, Kerala, India.ORCID 0000-0001-5091-9419

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Last decade has witnessed three major pandemics caused by SARS-CoV, SARS-CoV-2 and MERS-CoV that belong to Coronavirus family. Currently, there are no effective therapies available for corona virus infections. Since the three viruses belong to the same family and share many common features, we can theoretically design a drug that can be effective on all the three of them. In this study, using computational approach, we designed a peptide (Peptide 7) that can bind to the Receptor Binding Domain (RBD) of SARS-CoV, SARS-CoV-2 and MERS-CoV thereby preventing the entry of the viruses into the host cell. The peptide inhibitor was designed as a consensus peptide from three different peptides that might individually bind to the RBD of the three viruses. Docking studies and molecular dynamic simulations using Peptide 7 has shown that it binds with higher affinity than the native receptors of the RBD and forms a stable complex thereby preventing further viral-receptor interaction and inhibiting their cellular entry. This effective binding is observed for the three RBDs, despite the Peptide 7 interactions being slightly different. Hence; this peptide inhibitor can be used as a potential candidate for the development of peptide based anti-viral therapy against Corona viruses.

Indexed as

Amino Acid SequenceBinding SitesHumansHydrogen BondingMiddle East Respiratory Syndrome CoronavirusMolecular Docking SimulationMolecular Dynamics SimulationPeptidesProtein BindingReceptors, VirusSARS-CoV-2Severe acute respiratory syndrome-related coronavirusSpike Glycoprotein, CoronavirusVirus InternalizationPeptidesReceptors, VirusSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2

Identifiers

PMID34003827
PMCPMC8130920

What OpenQuestion holds

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LicenceCC BY
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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.