Evidence map›Paper›PMID 36055162›Full record

ArticleComputers in biology and medicine2022

Molecular dynamics simulations highlight the altered binding landscape at the spike-ACE2 interface between the Delta and Omicron variants compared to the SARS-CoV-2 original strain.

Eleni Pitsillou, Julia J Liang, Raymond C Beh, Andrew Hung, Tom C Karagiannis

Open access · greenAbstract read
In one paragraph

Article in Computers in biology and medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.2field-weighted citation impact, top 10% 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

13 citing papers in PubMed, 23 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

5 authors at 2 institutions in 1 country.

Eleni PitsillouEpigenomic Medicine, Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia; School of Science, STEM College, RMIT University, VIC, 3001, Australia.
Julia J LiangEpigenomic Medicine, Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia; School of Science, STEM College, RMIT University, VIC, 3001, Australia.
Raymond C BehEpigenomic Medicine, Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia; Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, 3052, Australia.
Andrew HungSchool of Science, STEM College, RMIT University, VIC, 3001, Australia.
Tom C KaragiannisEpigenomic Medicine, Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia; Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, 3052, Australia. Electronic address: karat@unimelb.edu.au.
Monash University · AURMIT University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) B.1.1.529 variant (Omicron), represents a significant deviation in genetic makeup and function compared to previous variants. Following the BA.1 sublineage, the BA.2 and BA.3 Omicron subvariants became dominant, and currently the BA.4 and BA.5, which are quite distinct variants, have emerged. Using molecular dynamics simulations, we investigated the binding characteristics of the Delta and Omicron (BA.1) variants in comparison to wild-type (WT) at the interface of the spike protein receptor binding domain (RBD) and human angiotensin converting enzyme-2 (ACE2) ectodomain. The primary aim was to compare our molecular modelling systems with previously published observations, to determine the robustness of our approach for rapid prediction of emerging future variants. Delta and Omicron were found to bind to ACE2 with similar affinities (-39.4 and -43.3 kcal/mol, respectively) and stronger than WT (-33.5 kcal/mol). In line with previously published observations, the energy contributions of the non-mutated residues at the interface were largely retained between WT and the variants, with F456, F486, and Y489 having the strongest energy contributions to ACE2 binding. Further, residues N440K, Q498R, and N501Y were predicted to be energetically favourable in Omicron. In contrast to Omicron, which had the E484A and K417N mutations, intermolecular bonds were detected for the residue pairs E484:K31 and K417:D30 in WT and Delta, in accordance with previously published findings. Overall, our simplified molecular modelling approach represents a step towards predictive model systems for rapidly analysing arising variants of concern.

Indexed as

Angiotensin-Converting Enzyme 2COVID-19HumansMolecular Dynamics SimulationMutationPeptidyl-Dipeptidase AProtein BindingSARS-CoV-2Spike Glycoprotein, CoronavirusACE2 protein, humanAngiotensin-Converting Enzyme 2Peptidyl-Dipeptidase ASpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2ACE2 receptorsDelta variantOmicron variantSARS-CoV-2Spike protein

Identifiers

PMID36055162
PMCPMC9420038
OpenAlexW4293564861

What OpenQuestion holds

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Registered trials

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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.