ArticleScientific data2022
A database of anti-coronavirus peptides.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Mucosal immune response in biology, disease prevention and treatment.Signal transduction and targeted therapy · 2025Pooled it
- MFE-ACVP: anti-coronavirus peptide prediction based on multimodal feature extraction and ensemble learning.Briefings in bioinformatics · 2025Article
- Deep learning in the discovery of antiviral peptides and peptidomimetics: databases and prediction tools.Molecular diversity · 2025Review
- Human coronaviruses: activation and antagonism of innate immune responses.Microbiology and molecular biology reviews : MMBR · 2025Review
- ACVPICPred: Inhibitory activity prediction of anti-coronavirus peptides based on artificial neural network.Computational and structural biotechnology journal · 2024Article
- Review and perspective on bioinformatics tools using machine learning and deep learning for predicting antiviral peptides.Molecular diversity · 2024Review
- FEOpti-ACVP: identification of novel anti-coronavirus peptide sequences based on feature engineering and optimization.Briefings in bioinformatics · 2024Article
- Current Development of Data Resources and Bioinformatics Tools for Anticoronavirus Peptide.Current medicinal chemistry · 2024Review
- Peptides as Therapeutic Agents: Challenges and Opportunities in the Green Transition Era.Molecules (Basel, Switzerland) · 2023Review
- Article
- Can Probiotics, ParticularlyBiology · 2023Review
- MFPPDB: a comprehensive multi-functional plant peptide database.Frontiers in plant science · 2023Article
- Computer-Aided Screening for Potential Coronavirus 3-Chymotrypsin-like Protease (3CLpro) Inhibitory Peptides from Putative Hemp Seed Trypsinized Peptidome.Molecules (Basel, Switzerland) · 2022Article
- In Silico Discovery of Anticancer Peptides from Sanghuang.International journal of molecular sciences · 2022Article
- Peptide-based inhibitors hold great promise as the broad-spectrum agents against coronavirus.Frontiers in microbiology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
Since 2019, the novel coronavirus (SARS-COV-2) disease (COVID-19) has caused a worldwide epidemic. Anti-coronavirus peptides (ACovPs), a type of antimicrobial peptides (AMPs), have demonstrated excellent inhibitory effects on coronaviruses. However, state-of-the-art AMP databases contain only a small number of ACovPs. Additionally, the fields of these databases are not uniform, and the units or evaluation standards of the same field are inconsistent. Most of these databases have not included the target domains of ACovPs and description of in vitro and in vivo assays to measure the inhibitory effects of ACovPs. Here, we present a database focused on ACovPs (ACovPepDB), which contains comprehensive and precise ACovPs information of 518 entries with 214 unique ACovPs manually collected from public databases and published peer-reviewed articles. We believe that ACovPepDB is of great significance for facilitating the development of new peptides and improving treatment for coronavirus infection. The database will become a portal for ACovPs and guide and help researchers perform further studies. The ACovPepDB is available at http://i.uestc.edu.cn/ACovPepDB/ .
Indexed as
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What Socratic 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 Socratic graph.