Evidence map›Paper›PMID 35932731›Full record

ArticleComputers in biology and medicine2022

Most frequently harboured missense variants of hACE2 across different populations exhibit varying patterns of binding interaction with spike glycoproteins of emerging SARS-CoV-2 of different lineages.

Anika Tahsin, Rubaiat Ahmed, Piyash Bhattacharjee, Maisha Adiba, Abdullah Al Saba, Tahirah Yasmin, Sajib Chakraborty, A K M Mahbub Hasan, A H M Nurun Nabi

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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 25% 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, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. 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

9 authors at 1 institution in 1 country.

Anika TahsinLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
Rubaiat AhmedLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
Piyash BhattacharjeeLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
Maisha AdibaLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
Abdullah Al SabaLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
Tahirah YasminLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
Sajib ChakrabortySystems Cell-Signalling Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
A K M Mahbub HasanLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh.
A H M Nurun NabiLaboratory of Population Genetics, Department of Biochemistry and Molecular Biology, University of Dhaka, Bangladesh. Electronic address: nabi@du.ac.bd.
University of Dhaka · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the emergence of SARS-CoV-2 at Wuhan in the Hubei province of China in 2019, the virus has accumulated various mutations, giving rise to many variants. According to the combinations of mutations acquired, these variants are classified into lineages and greatly differ in infectivity and transmissibility. In 2021 alone, a variant of interest (VoI) Mu (B.1.621), as well as, variants of concern (VoC) Delta (B.1.617.2) and Omicron (BA.1, BA.2) and later in 2022, BA.4, BA.5, and BA.2.12.1 have emerged. Since then, the world has seen prominent surges in the rate of infection during short periods of time. However, not all populations have suffered equally, which suggests a possible role of host genetic factors. Here, we investigated the strength of binding of the spike glycoprotein receptor-binding domain (RBD) of the SARS-CoV-2 variants: Mu, Delta, Delta Plus (AY.1), Omicron sub-variants BA.1, BA.2, BA.4, BA.5, and BA.2.12.1 with the human angiotensin-converting enzyme 2 (hACE2) missense variants prevalent in major populations. In this purpose, molecular docking analysis, as well as, molecular dynamics simulation was performed of the above-mentioned SARS-CoV-2 RBD variants with the hACE2 containing the single amino acid substitutions prevalent in African (E37K), Latin American (F40L), non-Finnish European (D355 N), and South Asian (P84T) populations, in order to predict the effects of the lineage-defining mutations of the viral variants on receptor binding. The effects of these mutations on protein stability were also explored. The protein-protein docking and molecular dynamics simulation analyses have revealed variable strength of attachment and exhibited altered interactions in the case of different hACE2-RBD complexes. In vitro studies are warranted to confirm these findings which may enable early prediction regarding the risk of transmissibility of newly emerging variants across different populations in the future.

Indexed as

Angiotensin-Converting Enzyme 2COVID-19GlycoproteinsHumansMolecular Docking SimulationMutationPeptidyl-Dipeptidase AProtein BindingReceptors, VirusSARS-CoV-2Spike Glycoprotein, CoronavirusAngiotensin-Converting Enzyme 2GlycoproteinsPeptidyl-Dipeptidase AReceptors, VirusSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2COVID-19hACE2Missense variantsMM/GBSAMolecular dockingMolecular dynamicsSARS-CoV-2

Identifiers

PMID35932731
PMCPMC9296255
OpenAlexW4286249778

What OpenQuestion 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 OpenQuestion graph.