ArticleiScience2021
A multi-pronged approach targeting SARS-CoV-2 proteins using ultra-large virtual screening.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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
50 citing papers in PubMed.
- Article
- The impact of library size and scale of testing on virtual screening.Nature chemical biology · 2025Article
- A Database for Large-Scale Docking and Experimental Results.Journal of chemical information and modeling · 2025Article
- Unveiling the mechanism of action of a novel natural dual inhibitor of SARS-CoV-2 Mpro and PLpro with molecular dynamics simulations.Natural products and bioprospecting · 2025Article
- Structure and dynamics in drug discovery.npj drug discovery · 2024Review
- Identifying Artifacts from Large Library Docking.Journal of medicinal chemistry · 2024Article
- Identifying Artifacts from Large Library Docking.bioRxiv : the preprint server for biology · 2024Article
- The impact of Library Size and Scale of Testing on Virtual Screening.bioRxiv : the preprint server for biology · 2024Article
- Virtual Screening of a Chemically Diverse "Superscaffold" Library Enables Ligand Discovery for a Key GPCR Target.ACS chemical biology · 2024Article
- AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor.Molecular systems biology · 2024Article
- DockOpt: A Tool for Automatic Optimization of Docking Models.Journal of chemical information and modeling · 2024Article
- Review
- SARS-CoV-2-induced phosphorylation and its pharmacotherapy backed by artificial intelligence and machine learning.Future science OA · 2024Article
- AI-assisted structural consensus-proteome prediction of human monkeypox viruses isolated within a year after the 2022 multi-country outbreak.Microbiology spectrum · 2023Article
- Unsupervised deep learning for molecular dynamics simulations: a novel analysis of protein-ligand interactions in SARS-CoV-2 MRSC advances · 2023Article
- A practical guide to machine-learning scoring for structure-based virtual screening.Nature protocols · 2023Review
- Identification of motif-based interactions between SARS-CoV-2 protein domains and human peptide ligands pinpoint antiviral targets.Nature communications · 2023Article
- Large-Scale Docking in the Cloud.Journal of chemical information and modeling · 2023Article
- Review
- SARS-CoV2 billion-compound docking.Scientific data · 2023Article
Corrections and comments
- Update of
Authors and funding
37 authors.
Funding
Abstract
The unparalleled global effort to combat the continuing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic over the last year has resulted in promising prophylactic measures. However, a need still exists for cheap, effective therapeutics, and targeting multiple points in the viral life cycle could help tackle the current, as well as future, coronaviruses. Here, we leverage our recently developed, ultra-large-scale
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.