Evidence map›Paper›PMID 34741079›Full record

ArticleScientific reports2021

Molecular strategies for antibody binding and escape of SARS-CoV-2 and its mutations.

Mohamed Hendy, Samuel Kaufman, Mauricio Ponga

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 22% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
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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

3 authors at 1 institution in 1 country.

Mohamed HendyDepartment of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, V6T 1Z4, BC, Canada.
Samuel KaufmanDepartment of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, V6T 1Z4, BC, Canada.
Mauricio PongaDepartment of Mechanical Engineering, University of British Columbia, 2054-6250 Applied Science Lane, Vancouver, V6T 1Z4, BC, Canada. mponga@mech.ubc.ca.
University of British Columbia · CA

Funding

Natural Sciences and Engineering Research Council of Canada 2016-06114New Frontier in Research Fund Exploration NFRFE-2019-01095
6 · The paper itself

Abstract

The COVID19 pandemic, caused by SARS-CoV-2, has infected more than 200 million people worldwide. Due to the rapid spreading of SARS-CoV-2 and its impact, it is paramount to find effective treatments against it. Human neutralizing antibodies are an effective method to fight viral infection. However, the recent discovery of new strains that substantially change the S-protein sequence has raised concern about vaccines and antibodies' effectiveness. Here, using molecular simulations, we investigated the binding mechanisms between the S-protein and several antibodies. Multiple mutations were included to understand the strategies for antibody escape in new variants. We found that the combination of mutations K417N, E484K, L452R, and T478K produced higher binding energy to ACE2 than the wild type, suggesting higher efficiency to enter host cells. The mutations' effect depends on the antibody class. While Class I enhances the binding avidity in the presence of N501Y mutation, class II antibodies showed a sharp decline in the binding affinity. Our simulations suggest that Class I antibodies will remain effective against the new strains. In contrast, Class II antibodies will have less affinity to the S-protein, potentially affecting these antibodies' efficiency.

Indexed as

MutationAngiotensin-Converting Enzyme 2Antibodies, NeutralizingAntibodies, ViralCluster AnalysisComputational BiologyComputer SimulationCOVID-19HumansHydrogen BondingMolecular ConformationMolecular Dynamics SimulationProtein BindingSARS-CoV-2Signal TransductionSpike Glycoprotein, CoronavirusACE2 protein, humanAngiotensin-Converting Enzyme 2Antibodies, NeutralizingAntibodies, ViralSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2

Identifiers

PMID34741079
PMCPMC8571385
OpenAlexW3209221247

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.