Evidence map›Paper›PMID 33456724›Full record

ArticleComputational and structural biotechnology journal2021

Unraveling the molecular basis of host cell receptor usage in SARS-CoV-2 and other human pathogenic β-CoVs.

Camila Pontes, Victoria Ruiz-Serra, Rosalba Lepore, Alfonso Valencia

Open access · goldAbstract read
In one paragraph

Article in Computational and structural biotechnology journal, 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
0.3field-weighted citation impact, top 41% 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, 5 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

4 authors at 3 institutions in 2 countries.

Camila PontesBarcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
Victoria Ruiz-SerraBarcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
Rosalba LeporeBarcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
Alfonso ValenciaBarcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
Barcelona Supercomputing Center · ESInstitució Catalana de Recerca i Estudis Avançats · ESUniversidade de Brasília · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent emergence of the novel SARS-CoV-2 in China and its rapid spread in the human population has led to a public health crisis worldwide. Like in SARS-CoV, horseshoe bats currently represent the most likely candidate animal source for SARS-CoV-2. Yet, the specific mechanisms of cross-species transmission and adaptation to the human host remain unknown. Here we show that the unsupervised analysis of conservation patterns across the β-CoV spike protein family, using sequence information alone, can provide valuable insights on the molecular basis of the specificity of β-CoVs to different host cell receptors. More precisely, our results indicate that host cell receptor usage is encoded in the amino acid sequences of different CoV spike proteins in the form of a set of specificity determining positions (SDPs). Furthermore, by integrating structural data,

Indexed as

APC, average product correctionCoVs, CoronavirusesEV, evolutionary rateFunctional specificityhACE2, human angiotensin converting enzyme 2MCA, multiple correspondence analysisMI, mutual informationMSA, multiple sequence alignmentNTD, N-terminal domainPhylogenetic analysisProtein subfamiliesRBD, receptor binding domainRBM, receptor binding motifSARS-CoV-2SDPs, specificity determining positionsSpecificity Determining PositionsSpike protein evolution

Identifiers

PMID33456724
PMCPMC7802526
OpenAlexW3119580877

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.