ArticleScience (New York, N.Y.)2025
Sequence-based prediction of intermolecular interactions driven by disordered regions.
Article in Science (New York, N.Y.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed.
- How do low-complexity domain interactions control transcription?Biochemical Society transactions · 2026Review
- Article
- Designed IDPs phase separate and mix or demix according to sequence designed parameters.bioRxiv : the preprint server for biology · 2026Article
- Integrative proteomics defines FANCA as a multifunctional hub linking DNA repair to translation.iScience · 2026Article
- Interpretable biophysical neural networks of transcriptional activation domains separate roles of protein abundance and coactivator binding.Cell systems · 2026Article
- Condensates in fusion oncoprotein-driven leukemia: new biology and therapeutic opportunities.Trends in cancer · 2026Review
- RBM15 in leukemogenesis: an emerging regulator at the interface of RNA biology and hematopoiesis.Trends in cancer · 2026Review
- A natural solution from caterpillar cuticles for flexible impact-resistant materials.Nature communications · 2026Article
- Structural Features of a Tiny Viral Protein, ORF7b of SARS-CoV-2.International journal of molecular sciences · 2026Article
- Hierarchical Nuclear Architecture in Pre-mRNA Splicing: From IDRs to Speckles and Meshworks.International journal of molecular sciences · 2026Review
- Article
- Centenarian SIRT6 variants elevate SIRT6 protein and enhance cellular senescence resistance.Research square · 2026Article
- Mapping interactions between disordered regions reveals promiscuity in biomolecular condensate formation.Nature communications · 2026Article
- Physics-guided design of intrinsically disordered proteins.bioRxiv : the preprint server for biology · 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
- In Search of Shape in the Unshaped: Constructing Ensembles of Intrinsically Disordered Proteins.Biophysics reviews · 2026Article
- Short autoinhibitory sequences control phase separation of an essential bacterial transcription termination factor.The EMBO journal · 2026Article
- Sketching microprotein portraits.Protein science : a publication of the Protein Society · 2026Review
- The Polymers of Life: Exploring Cellular Function Through Polymer Concepts.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- A coherent structural picture of the interaction of Tau with tubulin provides a link to its aggregation.The Journal of biological chemistry · 2026Review
2 more citing papers are in PubMed but not listed here.
Corrections and comments
- Update of
Authors and funding
9 authors.
Funding
Abstract
Intrinsically disordered regions (IDRs) in proteins play essential roles in cellular function. A growing body of work has shown that IDRs often interact with partners in a manner that does not depend on the precise order of amino acids but is instead driven by complementary chemical interactions, leading to disordered bound-state complexes. However, these chemically specific dynamic interactions are difficult to predict. In this study, we repurposed the chemical physics developed originally for molecular simulations to predict this chemical specificity between IDRs and partner proteins using protein sequence as the only input. Our approach-FINCHES-enables the direct prediction of phase diagrams, the identification of chemically specific interaction hotspots on IDRs, the decomposition of chemically distinct domains in IDRs, and a route to develop and test mechanistic hypotheses regarding IDR function in molecular recognition.
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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.