Evidence map›Paper›PMID 34089757›Full record

ArticleThe Journal of infection2021

Structural dynamics of SARS-CoV-2 variants: A health monitoring strategy for anticipating Covid-19 outbreaks.

Jacques Fantini, Nouara Yahi, Fodil Azzaz, Henri Chahinian

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of infection, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
4.6field-weighted citation impact, top 4% 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

46 citing papers in PubMed, 76 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Jacques FantiniINSERM UMR_S 1072, 13015 Marseille, France; Aix-Marseille Université, 13015 Marseille, France. Electronic address: jacques.fantini@univ-amu.fr.
Nouara YahiINSERM UMR_S 1072, 13015 Marseille, France; Aix-Marseille Université, 13015 Marseille, France.
Fodil AzzazINSERM UMR_S 1072, 13015 Marseille, France; Aix-Marseille Université, 13015 Marseille, France.
Henri ChahinianINSERM UMR_S 1072, 13015 Marseille, France; Aix-Marseille Université, 13015 Marseille, France.
Aix-Marseille Université · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesthe Covid-19 pandemic has been marked by sudden outbreaks of SARS-CoV-2 variants harboring mutations in both the N-terminal (NTD) and receptor binding (RBD) domains of the spike protein. The goal of this study was to predict the transmissibility of SARS-CoV-2 variants from genomic sequence data.

methodswe used a target-based molecular modeling strategy combined with surface potential analysis of the NTD and RBD.

resultswe observed that both domains act synergistically to ensure optimal virus adhesion, which explains why most variants exhibit concomitant mutations in the RBD and in the NTD. Some mutation patterns affect the affinity of the spike protein for ACE-2. However, other patterns increase the electropositive surface of the spike, with determinant effects on the kinetics of virus adhesion to lipid raft gangliosides. Based on this new view of the structural dynamics of SARS-CoV-2 variants, we defined an index of transmissibility (T-index) calculated from kinetic and affinity parameters of coronavirus binding to host cells. The T-index is characteristic of each variant and predictive of its dissemination in animal and human populations.

conclusionsthe T-index can be used as a health monitoring strategy to anticipate future Covid-19 outbreaks due to the emergence of variants of concern.

Indexed as

COVID-19Spike Glycoprotein, CoronavirusHumansPandemicsProtein BindingSARS-CoV-2Spike Glycoprotein, CoronavirusACE-2CoronavirusElectrostatic surface potentialGangliosideLipid raftreceptorSARS-CoV-2Virus-host interactions

Identifiers

PMID34089757
PMCPMC8172274
OpenAlexW3168762998

What Socratic 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 Socratic graph.