Evidence map›Paper›PMID 35312321›Full record

ArticleJournal of chemical information and modeling2022

Interaction Analysis of the Spike Protein of Delta and Omicron Variants of SARS-CoV-2 with hACE2 and Eight Monoclonal Antibodies Using the Fragment Molecular Orbital Method.

Sungbo Hwang, Seung-Hwa Baek, Daeui Park

Open access · hybridAbstract read
In one paragraph

Article in Journal of chemical information and modeling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 26 citations in OpenAlex.

  1. D614G reshapes allosteric networks and opening mechanisms of SARS-CoV-2 spikes.Proceedings of the National Academy of Sciences of the United States of America · 2026
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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.

Sungbo HwangDepartment of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 34114, Republic of Korea.ORCID 0000-0002-1610-5259
Seung-Hwa BaekDepartment of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 34114, Republic of Korea.
Daeui ParkDepartment of Predictive Toxicology, Korea Institute of Toxicology, Daejeon 34114, Republic of Korea.ORCID 0000-0002-9452-5849
Korea Institute of Toxicology · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past 2 years, since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), multiple SARS-CoV-2 variants have emerged. Whenever a new variant emerges, considerable time is required to analyze the binding affinity of the viral surface proteins to human angiotensin-converting enzyme 2 (hACE2) and monoclonal antibodies. To efficiently predict the binding affinities associated with hACE2 and monoclonal antibodies in a short time, herein, we propose a method applying statistical analysis to simulations performed using molecular and quantum mechanics. This method efficiently predicted the trend of binding affinity for the binding of the spike protein of each variant of SARS-CoV-2 to hACE2 and individually to eight commercial monoclonal antibodies. Additionally, this method accurately predicted interaction energy changes in the crystal structure for 10 of 13 mutated residues in the Omicron variant, showing a significant change in the interaction energy of hACE2. S375F was found to be a mutation that majorly changed the binding affinity of the spike protein to hACE2 and the eight monoclonal antibodies. Our proposed analysis method enables the prediction of the binding affinity of new variants to hACE2 or to monoclonal antibodies in a shorter time compared to that utilized by the experimental method.

Indexed as

COVID-19Spike Glycoprotein, CoronavirusAngiotensin-Converting Enzyme 2Antibodies, MonoclonalHumansProtein BindingSARS-CoV-2Angiotensin-Converting Enzyme 2Antibodies, MonoclonalSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2

Identifiers

PMID35312321
PMCPMC8982492
OpenAlexW4220740715

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.