ArticleNucleic acids research2018
AmyPro: a database of proteins with validated amyloidogenic regions.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
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Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it, 99 citations in OpenAlex.
- Protein Sequence Analysis landscape: A Systematic Review of Task Types, Databases, Datasets, Word Embeddings Methods, and Language Models.Database : the journal of biological databases and curation · 2025Pooled it
- VAEBAC: a representation-learning framework for proteome-scale prediction of amyloidogenic proteins and functional stratification of nucleic-acid-binding proteins.Bioinformatics (Oxford, England) · 2026Article
- Bioinformatic assessment of the potential amyloidogenicity of the human and evolutionarily more ancient proteomes.The Biochemical journal · 2026Article
- Predicting Peptide Aggregation with Protein Language Model Embeddings.Journal of chemical information and modeling · 2026Article
- FuzDrop: sequence-based prediction of the propensity of proteins for liquid-liquid phase separation and aggregation.Nature protocols · 2026Review
- Experimentally validated deep learning control of protein aggregation.Communications chemistry · 2026Article
- Synthetic deformylated α-helical PSMα3 as a selective inhibitor of human amyloid aggregation.Scientific reports · 2025Article
- Neurodegeneration Through the Lens of Bioinformatics Approaches: Computational Mechanisms of Protein Misfolding.International journal of molecular sciences · 2025Review
- Phase-separating fusion proteins drive cancer by upsetting transcription regulation.Genome biology · 2025Article
- Massive experimental quantification allows interpretable deep learning of protein aggregation.Science advances · 2025Article
- ABTrans: A Transformer-based Model for Predicting Interaction between Anti-Aβ Antibodies and Peptides.Interdisciplinary sciences, computational life sciences · 2025Article
- AggNet: Advancing protein aggregation analysis through deep learning and protein language model.Protein science : a publication of the Protein Society · 2025Article
- Prediction and Evaluation of Protein Aggregation with Computational Methods.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Aggregating amyloid resources: A comprehensive review of databases on amyloid-like aggregation.Computational and structural biotechnology journal · 2024Review
- Proteomic Evidence for Amyloidogenic Cross-Seeding in Fibrinaloid Microclots.International journal of molecular sciences · 2024Article
- Leveraging a large language model to predict protein phase transition: A physical, multiscale, and interpretable approach.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- AggreProt: a web server for predicting and engineering aggregation prone regions in proteins.Nucleic acids research · 2024Article
- Advanced computational approaches to understand protein aggregation.Biophysics reviews · 2024Review
- Lung endothelium, tau, and amyloids in health and disease.Physiological reviews · 2024Review
- A sequence-based model for identifying proteins undergoing liquid-liquid phase separation/forming fibril aggregates via machine learning.Protein science : a publication of the Protein Society · 2024Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 4 countries.
Funding
Abstract
Soluble functional proteins may transform into insoluble amyloid fibrils that deposit in a variety of tissues. Amyloid formation is a hallmark of age-related degenerative disorders. Perhaps surprisingly, amyloid fibrils can also be beneficial and are frequently exploited for diverse functional roles in organisms. Here we introduce AmyPro, an open-access database providing a comprehensive, carefully curated collection of validated amyloid fibril-forming proteins from all kingdoms of life classified into broad functional categories (http://amypro.net). In particular, AmyPro provides the boundaries of experimentally validated amyloidogenic sequence regions, short descriptions of the functional relevance of the proteins and their amyloid state, a list of the experimental techniques applied to study the amyloid state, important structural/functional/variation/mutation data transferred from UniProt, a list of relevant PDB structures categorized according to protein states, database cross-references and literature references. AmyPro greatly improves on similar currently available resources by incorporating both prions and functional amyloids in addition to pathogenic amyloids, and allows users to screen their sequences against the entire collection of validated amyloidogenic sequence fragments. By enabling further elucidation of the sequential determinants of amyloid fibril formation, we hope AmyPro will enhance the development of new methods for the precise prediction of amyloidogenic regions within proteins.
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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.