ArticlePeerJ2021
Multi-schema computational prediction of the comprehensive SARS-CoV-2 vs. human interactome.
Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Host-Directed Antiviral Strategies Against Influenza Viruses: Host Targets, Multi-Omics Approaches and AI-Assisted Discovery.Veterinary sciences · 2026Review
- Sequence-Based Protein-Protein Interaction Prediction and Its Applications in Drug Discovery.Cells · 2025Review
- A graph neural network-based approach for predicting SARS-CoV-2-human protein interactions from multiview data.PloS one · 2025Article
- Graph embedding on mass spectrometry- and sequencing-based biomedical data.BMC bioinformatics · 2024Review
- Assessment of GO-Based Protein Interaction Affinities in the Large-Scale Human-Coronavirus Family Interactome.Vaccines · 2023Article
- Large-scale data mining pipeline for identifying novel soybean genes involved in resistance against the soybean cyst nematode.Frontiers in bioinformatics · 2023Article
- Reciprocal perspective as a super learner improves drug-target interaction prediction (MUSDTI).Scientific reports · 2022Article
- Using informative features in machine learning based method for COVID-19 drug repurposing.Journal of cheminformatics · 2021Article
- A review on the interaction of nucleoside analogues with SARS-CoV-2 RNA dependent RNA polymerase.International journal of biological macromolecules · 2021Review
- Bioinformatics resources facilitate understanding and harnessing clinical research of SARS-CoV-2.Briefings in bioinformatics · 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
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding the disease pathogenesis of the novel coronavirus, denoted SARS-CoV-2, is critical to the development of anti-SARS-CoV-2 therapeutics. The global propagation of the viral disease, denoted COVID-19 ("coronavirus disease 2019"), has unified the scientific community in searching for possible inhibitory small molecules or polypeptides. A holistic understanding of the SARS-CoV-2 vs. human inter-species interactome promises to identify putative protein-protein interactions (PPI) that may be considered targets for the development of inhibitory therapeutics.
methodsWe leverage two state-of-the-art, sequence-based PPI predictors (PIPE4 & SPRINT) capable of generating the comprehensive SARS-CoV-2 vs. human interactome, comprising approximately 285,000 pairwise predictions. Three prediction schemas (
resultsThe
conclusionWe publicly released the comprehensive sets of PPI predictions and their corresponding PIPE-Sites landscapes in the following DataVerse repository: https://www.doi.org/10.5683/SP2/JZ77XA. The information provided represents theoretical modeling only and caution should be exercised in its use. It is intended as a resource for the scientific community at large in furthering our understanding of SARS-CoV-2.
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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.