ArticleNucleic acids research2023
FuzPred: a web server for the sequence-based prediction of the context-dependent binding modes of proteins.
Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Phosphorylation tunes strain-specific protein condensation during rotavirus replication organelle assembly.The EMBO journal · 2026Article
- amyloid-predict and LLPS-predict: Predicting phase separation propensities in the intrinsically disordered proteome.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- FuzDrop: sequence-based prediction of the propensity of proteins for liquid-liquid phase separation and aggregation.Nature protocols · 2026Review
- Ser423-phosphorylated MECP2 (MECP2-pS423) accumulates in human brain, cerebrospinal fluid and serum in sporadic Alzheimer's disease.Acta neuropathologica · 2026Article
- Phosphorylation enables allosteric control of a viral condensate.bioRxiv : the preprint server for biology · 2025Article
- Evaluation of predictions of disordered binding regions in the CAID2 experiment.Computational and structural biotechnology journal · 2025Review
- Cellular RNA interacts with MAVS to promote antiviral signaling.Science (New York, N.Y.) · 2024Article
- Article
- Inherently disordered regions of axonemal dynein assembly factors.Cytoskeleton (Hoboken, N.J.) · 2024Review
- MEF-AlloSite: an accurate and robust Multimodel Ensemble Feature selection for the Allosteric Site identification model.Journal of cheminformatics · 2024Article
- Intrinsic disorder in the human vitreous proteome.International journal of biological macromolecules · 2024Article
- Deep mutational scanning of the RNase III-like domain inFrontiers in cellular and infection microbiology · 2024Article
- CELLULAR RNA INTERACTS WITH MAVS TO PROMOTE ANTIVIRAL SIGNALING.bioRxiv : the preprint server for biology · 2023Article
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Authors and funding
7 authors.
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Abstract
Proteins form complex interactions in the cellular environment to carry out their functions. They exhibit a wide range of binding modes depending on the cellular conditions, which result in a variety of ordered or disordered assemblies. To help rationalise the binding behavior of proteins, the FuzPred server predicts their sequence-based binding modes without specifying their binding partners. The binding mode defines whether the bound state is formed through a disorder-to-order transition resulting in a well-defined conformation, or through a disorder-to-disorder transition where the binding partners remain conformationally heterogeneous. To account for the context-dependent nature of the binding modes, the FuzPred method also estimates the multiplicity of binding modes, the likelihood of sampling multiple binding modes. Protein regions with a high multiplicity of binding modes may serve as regulatory sites or hot-spots for structural transitions in the assembly. To facilitate the interpretation of the predictions, protein regions with different interaction behaviors can be visualised on protein structures generated by AlphaFold. The FuzPred web server (https://fuzpred.bio.unipd.it) thus offers insights into the structural and dynamical changes of proteins upon interactions and contributes to development of structure-function relationships under a variety of cellular conditions.
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