Evidence map›Paper›PMID 38902252›Full record

ArticleScientific reports2024

Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics.

Vaishali P Waman, Paul Ashford, Su Datt Lam, Neeladri Sen, Mahnaz Abbasian, Laurel Woodridge, Yonathan Goldtzvik, Nicola Bordin, Jiaxin Wu, Ian Sillitoe and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

11 authors.

Vaishali P WamanInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Paul AshfordInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Su Datt LamDepartment of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia.
Neeladri SenInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Mahnaz AbbasianInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Laurel WoodridgeInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Yonathan GoldtzvikInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Nicola BordinInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Jiaxin WuInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Ian SillitoeInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK.
Christine A OrengoInstitute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK. c.orengo@ucl.ac.uk.

Funding

Resource for Biocomputing Visualization and InformaticsP41GM103311 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2012 to 2017
$8.2M
Biotechnology and Biological Sciences Research Council 60175814Biotechnology and Biological Sciences Research Council BB/M009513/1Biotechnology and Biological Sciences Research Council BB/R014892/1Biotechnology and Biological Sciences Research Council BB/S020144/1Biotechnology and Biological Sciences Research Council BB/W003368/1Ministry of Higher Education, Malaysia FRGS/1/2020/STG01/UKM/02/3NIGMS NIH HHS P41 GM103311Wellcome TrustWellcome Trust 221327/Z/20/Z
6 · The paper itself

Abstract

The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.

Indexed as

COVID-19Mutation, MissenseSARS-CoV-2COVID-19 Drug TreatmentDisease SusceptibilityDrug RepositioningGenetic Predisposition to DiseaseHumansProtein BindingViral ProteinsViral ProteinsCATH databaseCOVID-19Functional familyHuman genetic variationImmunityProtein binding affinity predictionProtein structure complexSARS-CoV-2: human protein interaction

Identifiers

PMID38902252
PMCPMC11190248

What OpenQuestion holds

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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.