Evidence map›Paper›PMID 34251748›Full record

ArticleTransboundary and emerging diseases2022

A computational study of the interface interaction between SARS-CoV-2 RBD and ACE2 from human, cat, dog, and ferret.

William O Soté, Eduardo F Franca, Aline S Hora, Moacyr Comar

Open access · greenAbstract read
In one paragraph

Article in Transboundary and emerging diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

4 citing papers in PubMed, 5 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

4 authors at 1 institution in 1 country.

William O SotéChemistry Institute, Federal University of Uberlandia, Minas Gerais, Brazil.
Eduardo F FrancaChemistry Institute, Federal University of Uberlandia, Minas Gerais, Brazil.
Aline S HoraSchool of Veterinary Medicine, Federal University of Uberlandia, Minas Gerais, Brazil.
Moacyr ComarChemistry Institute, Federal University of Uberlandia, Minas Gerais, Brazil.
Universidade Federal de Uberlândia · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The total impact of the worldwide COVID-19 pandemic is still emerging, changing all relationships as a result, including those with pet animals. In the infection process, the use of angiotensin-converting enzyme 2 (ACE2) as a cellular receptor to the spike protein of the new coronavirus is a fundamental step. In this sense, understanding which residue plays what role in the interaction between SARS-CoV-2 spike glycoprotein and ACE2 from cats, dogs, and ferrets is an important guide for helping to choose which animal model can be used to study the pathology of COVID-19, and if there are differences between these interactions and those occurring in the human system. To help answer these questions, we performed classical molecular dynamics simulations to evaluate, from an atomistic point of view, the interactions in these systems. Our results show that there are significant differences in the interacting residues between the systems from different animal species, and the role of ACE2 key residues are different in each system, and can assist in the search for different inhibitors for each animal.

Indexed as

Angiotensin-Converting Enzyme 2COVID-19Spike Glycoprotein, CoronavirusAnimalsCatsDogsFerretsHumansPandemicsSARS-CoV-2Angiotensin-Converting Enzyme 2Spike Glycoprotein, Coronavirusspike protein, SARS-CoV-2angiotensin-converting enzyme 2molecular dynamicsreceptor binding domainSevere acute respiratory syndrome coronavirus 2

Identifiers

PMID34251748
PMCPMC8447414
OpenAlexW3137083483

What OpenQuestion 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 OpenQuestion graph.