ArticleThe Journal of cell biology2020
Crippling life support for SARS-CoV-2 and other viruses through synthetic lethality.
Article in The Journal of cell biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets.Molecular systems biology · 2021Pooled it
- Explainable/interpretable artificial intelligence and knowledge graph neural network for synthetic lethality prediction: overview, challenges, and future directions.Briefings in bioinformatics · 2026Review
- Drug combination treatment as a strategy for inhibiting human adenovirus replication.Antiviral research · 2026Article
- Breaking barriers: Respiratory viral strategies targeting the host's nuclear pore complex and nuclear transport pathways.Molecular biology of the cell · 2026Review
- Exploiting host kinases to combat dengue virus infection and disease.Antiviral research · 2025Review
- Graphlet-based hyperbolic embeddings capture evolutionary dynamics in genetic networks.Bioinformatics (Oxford, England) · 2024Article
- Predicting host-based, synthetic lethal antiviral targets from omics data.NAR molecular medicine · 2024Article
- Predicting host-based, synthetic lethal antiviral targets from omics data.bioRxiv : the preprint server for biology · 2023Article
- Antitarget, Anti-SARS-CoV-2 Leads, Drugs, and the Drug Discovery-Genetics Alliance Perspective.Journal of medicinal chemistry · 2023Review
- Peroxisome biogenesis and inter-organelle communication: an indispensable role for Pex11 and Pex30 family proteins in yeast.Current genetics · 2022Review
- Discovery of host-directed modulators of virus infection by probing the SARS-CoV-2-host protein-protein interaction network.Briefings in bioinformatics · 2022Article
- Viral protein engagement of GBF1 induces host cell vulnerability through synthetic lethality.The Journal of cell biology · 2022Article
- Article
- Computational methods, databases and tools for synthetic lethality prediction.Briefings in bioinformatics · 2022Review
- Dengue activates mTORC2 signaling to counteract apoptosis and maximize viral replication.Frontiers in cellular and infection microbiology · 2022Article
- Research progress on the antiviral activities of natural products and their derivatives: Structure-activity relationships.Frontiers in chemistry · 2022Review
- Synthetic lethality-based prediction of anti-SARS-CoV-2 targets.bioRxiv : the preprint server for biology · 2021Article
- Host-targeted Interventions as an Exciting Opportunity to Combat Malaria.Chemical reviews · 2021Review
- Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets.bioRxiv : the preprint server for biology · 2021Article
- Metabolic Control by DNA Tumor Virus-Encoded Proteins.Pathogens (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
Abstract
With the rapid global spread of SARS-CoV-2, we have become acutely aware of the inadequacies of our ability to respond to viral epidemics. Although disrupting the viral life cycle is critical for limiting viral spread and disease, it has proven challenging to develop targeted and selective therapeutics. Synthetic lethality offers a promising but largely unexploited strategy against infectious viral disease; as viruses infect cells, they abnormally alter the cell state, unwittingly exposing new vulnerabilities in the infected cell. Therefore, we propose that effective therapies can be developed to selectively target the virally reconfigured host cell networks that accompany altered cellular states to cripple the host cell that has been converted into a virus factory, thus disrupting the viral life cycle.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.