ArticleFrontiers in molecular biosciences2021
SGnn: A Web Server for the Prediction of Prion-Like Domains Recruitment to Stress Granules Upon Heat Stress.
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 20 citations in OpenAlex.
- Assessment of Aggregation- and Condensation-Prone Regions of Proteins Involved in Neurodegenerative, Neurological and Mental-State Diseases.Biomolecules · 2026Article
- Comprehensive protein datasets and benchmarking for liquid-liquid phase separation studies.Genome biology · 2025Article
- catGRANULE 2.0: accurate predictions of liquid-liquid phase separating proteins at single amino acid resolution.Genome biology · 2025Article
- Rational Tuning of the Concentration-independent Enrichment of Prion-like Domains in Stress Granules.Journal of molecular biology · 2024Article
- In silico analysis of fungal prion-like proteins for elucidating their role in plant-fungi interactions.Archives of microbiology · 2024Article
- Liquid-liquid phase separation in plants: Advances and perspectives from model species to crops.Plant communications · 2024Review
- Phase separations in oncogenesis, tumor progressions and metastasis: a glance from hallmarks of cancer.Journal of hematology & oncology · 2023Review
- In-Silico Analysis of pH-Dependent Liquid-Liquid Phase Separation in Intrinsically Disordered Proteins.Biomolecules · 2022Article
- Exploring cryptic amyloidogenic regions in prion-like proteins from plants.Frontiers in plant science · 2022Article
- Evolution of sequence traits of prion-like proteins linked to amyotrophic lateral sclerosis (ALS).PeerJ · 2022Article
- Landscape of biomolecular condensates in heat stress responses.Frontiers in plant science · 2022Review
- Microbiome Impact on Amyloidogenesis.Frontiers in molecular biosciences · 2022Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Proteins bearing prion-like domains (PrLDs) are essential players in stress granules (SG) assembly. Analysis of data on heat stress-induced recruitment of yeast PrLDs to SG suggests that this propensity might be connected with three defined protein biophysical features: aggregation propensity, net charge, and the presence of free cysteines. These three properties can be read directly in the PrLDs sequences, and their combination allows to predict protein recruitment to SG under heat stress. On this basis, we implemented SGnn, an online predictor of SG recruitment that exploits a feed-forward neural network for high accuracy classification of the assembly behavior of PrLDs. The simplicity and precision of our strategy should allow its implementation to identify heat stress-induced SG-forming proteins in complete proteomes.
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