{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T03:58:41Z","timestamp":1790308721423,"version":"4.1.0"},"reference-count":76,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Proteins"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Liquid\u2013liquid phase separation (LLPS) drives the formation of membraneless biomolecular condensates that regulate essential cellular processes including gene expression, stress response, and signal transduction. A critical challenge in this field is distinguishing RNA\u2010dependent from RNA\u2010independent condensates, a distinction central to the pathology of neurodegenerative disorders. Current computational approaches typically overlook this separation. Here, we introduce an interpretable two\u2010stage deep learning framework that first predicts the likelihood of a protein sequence undergoing phase separation, and subsequently determines whether condensate formation is RNA\u2010dependent. Our framework integrates deep contextual embeddings obtained from ProtBERT, a pretrained protein language transformer with 66 handcrafted sequence\u2010derived features. These representations are processed using an ensemble of machine learning classifiers, and their outputs are combined using a stacked artificial neural network, capturing both local sequence traits and global contextual information. Interpretability analyses like SHAP and feature correlation demonstrate that the most predictive ProtBERT embedding dimensions are associated with sequence\u2010derived hallmarks of LLPS, including descriptors related to intrinsic disorder and multivalent interaction motifs. Benchmarking shows that our framework achieves superior performance compared to the existing predictors on the external test set with 96.5% accuracy, F1\u2010score of 0.965, and MCC of 0.931. It also shows superior performance over the sole existing RNA\u2010dependent LLPS predictor. Structural analysis of representative misclassifications further reveals how spatial constraints and topology modulate phase separation beyond sequence features. This study offers a unified approach for modeling RNA\u2010mediated phase separation from protein sequence and establishes a foundation for bridging sequence\u2010based prediction with structural understanding of biomolecular condensates.<\/jats:p>","DOI":"10.1002\/prot.70180","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T03:06:31Z","timestamp":1790305591000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoding\n                    <scp>RNA<\/scp>\n                    \u2010Dependent Protein Phase Separation Using an Ensemble\u2010Based Deep Learning Framework Integrating\n                    <scp>ProtBERT<\/scp>\n                    Embeddings With Physicochemical Features"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1319-6941","authenticated-orcid":false,"given":"Sonali","family":"Chatterjee","sequence":"first","affiliation":[{"name":"Computational Structural Biology Laboratory, Department of Bioscience and Biotechnology Indian Institute of Technology Kharagpur  Kharagpur India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0187-9884","authenticated-orcid":false,"given":"Tanujay","family":"Saha","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Princeton University  Princeton New Jersey USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6705-1713","authenticated-orcid":false,"given":"Ranjit Prasad","family":"Bahadur","sequence":"additional","affiliation":[{"name":"Computational Structural Biology Laboratory, Department of Bioscience and Biotechnology Indian Institute of Technology Kharagpur  Kharagpur India"},{"name":"Bioinformatics Center, Department of Bioscience and Biotechnology Indian Institute of Technology Kharagpur  Kharagpur India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,24]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"crossref","first-page":"19474","DOI":"10.1073\/pnas.1907849116","article-title":"Three Archetypical Classes of Macromolecular Regulators of Protein Liquid\u2013Liquid Phase Separation","volume":"116","author":"Ghosh A.","year":"2019","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"key":"e_1_2_12_3_1","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1038\/nrm.2017.7","article-title":"Biomolecular Condensates: Organizers of Cellular Biochemistry","volume":"18","author":"Banani S. 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J.","year":"2021","journal-title":"Nature Structural & Molecular Biology"},{"key":"e_1_2_12_5_1","doi-asserted-by":"crossref","first-page":"eaaf4382","DOI":"10.1126\/science.aaf4382","article-title":"Liquid Phase Condensation in Cell Physiology and Disease","volume":"357","author":"Shin Y.","year":"2017","journal-title":"Science"},{"key":"e_1_2_12_6_1","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1146\/annurev-genet-112618-043527","article-title":"Liquid\u2013Liquid Phase Separation in Disease","volume":"53","author":"Alberti S.","year":"2019","journal-title":"Annual Review of Genetics"},{"key":"e_1_2_12_7_1","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/s41392-021-00678-1","article-title":"Liquid\u2013Liquid Phase Separation in Human Health and Diseases","volume":"6","author":"Wang B.","year":"2021","journal-title":"Signal Transduction and Targeted Therapy"},{"key":"e_1_2_12_8_1","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1038\/s41580-020-0264-6","article-title":"RNA Contributions to the Form and Function of Biomolecular Condensates","volume":"22","author":"Roden C.","year":"2021","journal-title":"Nature Reviews. Molecular Cell Biology"},{"key":"e_1_2_12_9_1","doi-asserted-by":"crossref","first-page":"4636","DOI":"10.1016\/j.jmb.2018.08.005","article-title":"Multiple Modes of Protein\u2013Protein Interactions Promote RNP Granule Assembly","volume":"430","author":"Mittag T.","year":"2018","journal-title":"Journal of Molecular Biology"},{"key":"e_1_2_12_10_1","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1126\/science.aar7366","article-title":"RNA Buffers the Phase Separation Behavior of Prion\u2010Like RNA\u2010Binding Proteins","volume":"360","author":"Maharana S.","year":"2018","journal-title":"Science"},{"key":"e_1_2_12_11_1","doi-asserted-by":"crossref","first-page":"826719","DOI":"10.3389\/fmolb.2022.826719","article-title":"Liquid\u2013Liquid Phase Separation of TDP\u201043 and FUS in Physiology and Pathology of Neurodegenerative Diseases","volume":"9","author":"Carey J. 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S.","year":"2017","journal-title":"Biophysical Journal"},{"key":"e_1_2_12_42_1","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/0022-2836(82)90515-0","article-title":"A Simple Method for Displaying the Hydropathic Character of a Protein","volume":"157","author":"Kyte J.","year":"1982","journal-title":"Journal of Molecular Biology"},{"key":"e_1_2_12_43_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman L.","year":"2001","journal-title":"Machine Learning"},{"key":"e_1_2_12_44_1","first-page":"2825","article-title":"Scikit\u2010Learn: Machine Learning in Python","volume":"12","author":"Pedregosa F.","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_12_45_1","volume-title":"Dynamic Programming","author":"Bellman R.","year":"1957"},{"key":"e_1_2_12_46_1","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1023\/A:1022627411411","article-title":"Support\u2010Vector Networks","volume":"20","author":"Cortes C.","year":"1995","journal-title":"Machine Learning"},{"key":"e_1_2_12_47_1","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1142\/S0218001405003983","article-title":"Exploring Conditions for the Optimality of Na\u00efve Bayes","volume":"19","author":"Zhang H.","year":"2005","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"},{"key":"e_1_2_12_48_1","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203451","article-title":"Greedy Function Approximation: A Gradient Boosting Machine","volume":"29","author":"Friedman J. H.","year":"2001","journal-title":"Annals of Statistics"},{"key":"e_1_2_12_49_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","article-title":"Extremely Randomized Trees","volume":"63","author":"Geurts P.","year":"2006","journal-title":"Machine Learning"},{"key":"e_1_2_12_50_1","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.sbi.2016.10.015","article-title":"Intrinsically Disordered Proteins in Overcrowded Milieu: Membrane\u2010Less Organelles, Phase Separation, and Intrinsic Disorder","volume":"44","author":"Uversky V. N.","year":"2017","journal-title":"Current Opinion in Structural Biology"},{"key":"e_1_2_12_51_1","doi-asserted-by":"crossref","first-page":"e30294","DOI":"10.7554\/eLife.30294","article-title":"Intrinsically Disordered Linkers Determine the Interplay Between Phase Separation and Gelation in Multivalent Proteins","volume":"6","author":"Harmon T. 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