ArticleNucleic acids research2024
AggreProt: a web server for predicting and engineering aggregation prone regions in proteins.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Systematic optimization ofEngineering microbiology · 2026Review
- EnzymeMiner 2.0: advancing automated enzyme discovery with expansive sequence mining and smart property analysis.Nucleic acids research · 2026Article
- Predicting Peptide Aggregation with Protein Language Model Embeddings.Journal of chemical information and modeling · 2026Article
- Experimentally validated deep learning control of protein aggregation.Communications chemistry · 2026Article
- The Interaction between the Tyrosine Kinase Receptor EphA2 and RNF5: Structural Insights from anComputational and structural biotechnology journal · 2026Article
- Emerging Technologies and Integrated Interdisciplinary Strategies for Mitigating Protein Aggregation in Therapeutic Formulations.Pharmaceutical research · 2026Review
- In vivo modeling of lethal congenital contracture syndrome 1 suggests pathomechanisms in cellular stress responses.The FEBS journal · 2025Article
- Analyses of exon 4a structure reveal unique properties of Big tau.bioRxiv : the preprint server for biology · 2025Article
- AlphaFold modeling uncovers global structural features of class I and class II fungal hydrophobins.Protein science : a publication of the Protein Society · 2025Article
- Decoding Protein Stabilization: Impact on Aggregation, Solubility, and Unfolding Mechanisms.Journal of chemical information and modeling · 2025Article
- A Convenient Strategy for Studying Antibody Aggregation and Inhibition of Aggregation: Characterization and Simulation.Pharmaceutics · 2025Article
- Effect of Lipidation on the Structure, Oligomerization, and Aggregation of Glucagon-like Peptide 1.Bioconjugate chemistry · 2025Article
- AggNet: Advancing protein aggregation analysis through deep learning and protein language model.Protein science : a publication of the Protein Society · 2025Article
- A comprehensive strategy for the development of a multi-epitope vaccine targetingFrontiers in microbiology · 2025Article
- Analyses of exon 4a structure reveal the properties of Big tau related to distribution, function and aggregation.Frontiers in molecular neuroscience · 2025Article
- Proteomic Evidence for Amyloidogenic Cross-Seeding in Fibrinaloid Microclots.International journal of molecular sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Recombinant proteins play pivotal roles in numerous applications including industrial biocatalysts or therapeutics. Despite the recent progress in computational protein structure prediction, protein solubility and reduced aggregation propensity remain challenging attributes to design. Identification of aggregation-prone regions is essential for understanding misfolding diseases or designing efficient protein-based technologies, and as such has a great socio-economic impact. Here, we introduce AggreProt, a user-friendly webserver that automatically exploits an ensemble of deep neural networks to predict aggregation-prone regions (APRs) in protein sequences. Trained on experimentally evaluated hexapeptides, AggreProt compares to or outperforms state-of-the-art algorithms on two independent benchmark datasets. The server provides per-residue aggregation profiles along with information on solvent accessibility and transmembrane propensity within an intuitive interface with interactive sequence and structure viewers for comprehensive analysis. We demonstrate AggreProt efficacy in predicting differential aggregation behaviours in proteins on several use cases, which emphasize its potential for guiding protein engineering strategies towards decreased aggregation propensity and improved solubility. The webserver is freely available and accessible at https://loschmidt.chemi.muni.cz/aggreprot/.
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.