ArticleProtein science : a publication of the Protein Society2023
ParSe 2.0: A web tool to identify drivers of protein phase separation at the proteome level.
Article in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Two-dimensional HRS condensates drive the assembly of flat clathrin lattices on endosomes.Nature communications · 2026Article
- Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective.Briefings in bioinformatics · 2026Review
- Comprehensive CRISPR/Cas9-based mutagenesis identifies single-amino acid substitutions that abrogate SPEN function in X inactivation.Nature communications · 2026Article
- Missense mutations in intrinsically disordered protein regions link pathogenicity and phase separation.The Journal of biological chemistry · 2025Article
- BAV-LLPS: a database of bacterial, archaea, and virus liquid-liquid phase separation proteins.Bioinformatics (Oxford, England) · 2025Article
- Empirical Assessment of Sequence-Based Predictions of Intrinsically Disordered Regions Involved in Phase Separation.Biomolecules · 2025Article
- Bioinformatics-Based Comparative Analysis of the Human Retina Proteome.Proteomics. Clinical applications · 2025Article
- The effects of retinal disease on intrinsic protein disorder and liquid-liquid‑phase separation.Journal of proteins and proteomics · 2025Article
- Hierarchy in regulator interactions with distant transcriptional activation domains empowers rheostatic regulation.Protein science : a publication of the Protein Society · 2025Article
- Artificial metalloenzyme assembly in cellular compartments for enhanced catalysis.Nature chemical biology · 2025Article
- Evolutionary analysis of ZAP and its cofactors identifies intrinsically disordered regions as central elements in host-pathogen interactions.Computational and structural biotechnology journal · 2024Article
- A two-task predictor for discovering phase separation proteins and their undergoing mechanism.Briefings in bioinformatics · 2024Article
- Positive Selection Drives the Evolution of the Structural Maintenance of Chromosomes (SMC) Complexes.Genes · 2024Article
- ParSe 2.0: A web tool to identify drivers of protein phase separation at the proteome level.Protein science : a publication of the Protein Society · 2023Article
- RNA-Protein Assemblies: A Review of Biophysical Principles and Coarse-Grained Modeling Approaches.Wiley interdisciplinary reviews. RNAReview
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Authors and funding
5 authors.
Funding
Abstract
We have developed an algorithm, ParSe, which accurately identifies from the primary sequence those protein regions likely to exhibit physiological phase separation behavior. Originally, ParSe was designed to test the hypothesis that, for flexible proteins, phase separation potential is correlated to hydrodynamic size. While our results were consistent with that idea, we also found that many different descriptors could successfully differentiate between three classes of protein regions: folded, intrinsically disordered, and phase-separating intrinsically disordered. Consequently, numerous combinations of amino acid property scales can be used to make robust predictions of protein phase separation. Built from that finding, ParSe 2.0 uses an optimal set of property scales to predict domain-level organization and compute a sequence-based prediction of phase separation potential. The algorithm is fast enough to scan the whole of the human proteome in minutes on a single computer and is equally or more accurate than other published predictors in identifying proteins and regions within proteins that drive phase separation. Here, we describe a web application for ParSe 2.0 that may be accessed through a browser by visiting https://stevewhitten.github.io/Parse_v2_FASTA to quickly identify phase-separating proteins within large sequence sets, or by visiting https://stevewhitten.github.io/Parse_v2_web to evaluate individual protein sequences.
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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.