ArticleNucleic acids research2022
dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data.
Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
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Who cites it
88 citing papers in PubMed.
- Artificial intelligence catalyzes antimicrobial peptide design.Synthetic and systems biotechnology · 2027Review
- Artificial Intelligence-Driven Antimicrobial Peptide Discovery: Prediction, Generation, Mining and Optimization.Probiotics and antimicrobial proteins · 2026Review
- GANs in Peptide Drug Discovery: From De Novo Design to Multi-Property Optimization and Clinical Translation.Probiotics and antimicrobial proteins · 2026Review
- An Interpretable Multi-Objective Machine Learning Framework for In Silico Prioritization of Anti-Diagnostics (Basel, Switzerland) · 2026Article
- Complex Networks in Bioactive Peptide Research: A Methodological Review.Biomolecules · 2026Review
- Discovery of potent low-toxicity antimicrobial peptides through diffusion modeling.Nature communications · 2026Article
- Harnessing generative AI for predicting and optimizing antimicrobial peptides against drug-resistant infections.npj antimicrobials and resistance · 2026Article
- Generative models for antimicrobial peptide design: auto-encoders and beyond.BioData mining · 2026Article
- KSDiffusion: conditional diffusion for kinase-specific phosphorylation site prediction under data-limited and imbalanced regimes.Briefings in bioinformatics · 2026Article
- CLABP: a contrastive learning framework integrating protein language models and structural information for antibacterial peptide prediction.Briefings in bioinformatics · 2026Article
- De Novo Multi-Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- A generative explainable model for antimicrobial peptide prediction using bidirectional temporal convolutional neural network.Scientific reports · 2026Article
- Enhanced antibacterial activity of antimicrobial peptide-antibiotic combinations against multidrug-resistant bacteria.FEMS microbes · 2026Review
- tsAMP: a strain-level antimicrobial peptide identification framework based on large language models and pathogen genomic variation.Frontiers in microbiology · 2026Article
- Recent advances in computational antimicrobial peptide discovery through big data, modeling, and artificial intelligence and their interplay in ushering the next golden era of drug development.Frontiers in bioinformatics · 2026Review
- Article
- Integrative computational-experimental discovery and translation of antifungal peptides for multidrug-resistant fungi.Frontiers in microbiology · 2026Review
- ProjFusNet: deep neural network for peptide precursor prediction using projection-fused protein language model and structural features.Journal of cheminformatics · 2025Article
- Harnessing Machine Learning Approaches for the Identification, Characterization, and Optimization of Novel Antimicrobial Peptides.Antibiotics (Basel, Switzerland) · 2025Review
- BroadAMP-GPT: AI-Driven generation of broad-spectrum antimicrobial peptides for combating multidrug-resistant ESKAPE pathogens.Gut microbes · 2025Article
28 more citing papers are in PubMed but not listed here.
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Authors and funding
24 authors.
Funding
Abstract
The last 18 months, or more, have seen a profound shift in our global experience, with many of us navigating a once-in-100-year pandemic. To date, COVID-19 remains a life-threatening pandemic with little to no targeted therapeutic recourse. The discovery of novel antiviral agents, such as vaccines and drugs, can provide therapeutic solutions to save human beings from severe infections; however, there is no specifically effective antiviral treatment confirmed for now. Thus, great attention has been paid to the use of natural or artificial antimicrobial peptides (AMPs) as these compounds are widely regarded as promising solutions for the treatment of harmful microorganisms. Given the biological significance of AMPs, it was obvious that there was a significant need for a single platform for identifying and engaging with AMP data. This led to the creation of the dbAMP platform that provides comprehensive information about AMPs and facilitates their investigation and analysis. To date, the dbAMP has accumulated 26 447 AMPs and 2262 antimicrobial proteins from 3044 organisms using both database integration and manual curation of >4579 articles. In addition, dbAMP facilitates the evaluation of AMP structures using I-TASSER for automated protein structure prediction and structure-based functional annotation, providing predictive structure information for clinical drug development. Next-generation sequencing (NGS) and third-generation sequencing have been applied to generate large-scale sequencing reads from various environments, enabling greatly improved analysis of genome structure. In this update, we launch an efficient online tool that can effectively identify AMPs from genome/metagenome and proteome data of all species in a short period. In conclusion, these improvements promote the dbAMP as one of the most abundant and comprehensively annotated resources for AMPs. The updated dbAMP is now freely accessible at http://awi.cuhk.edu.cn/dbAMP.
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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.