ArticleNature communications2023
Evaluating native-like structures of RNA-protein complexes through the deep learning method.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Computational Methods in Drug Development: From Molecular Modeling to Artificial Intelligence Technologies.Pharmaceuticals (Basel, Switzerland) · 2026Article
- xBind: an integrated webserver for large language model-enabled cross-molecular protein binding site prediction.Nucleic acids research · 2026Article
- Bridging technical innovation and computational advances in studies of RNA-protein assemblies.Nature reviews. Genetics · 2026Review
- Inferring the qualities of protein-RNA models with graph transformers.Bioinformatics (Oxford, England) · 2026Article
- Differentiation of RNA-protein docking structures through molecular dynamics simulation and machine learning methods.Briefings in bioinformatics · 2026Article
- gCoSRNA: Generalizable Coaxial Stacking Prediction for RNA Junctions Using Secondary Structure.Biomolecules · 2026Article
- Quality assessment of RNA 3D structure models using deep learning and intermediate 2D maps.Communications biology · 2026Article
- Single-sequence protein-RNA complex structure prediction by geometric attention-enabled pairing of biological language models.Cell systems · 2025Article
- Advances in Protein-RNA aptamer recognition and modeling: Current trends and future perspectives.Current opinion in structural biology · 2025Review
- GluK2 kainate receptor subunit-selective, potentiating RNA aptamer.Scientific reports · 2025Article
- LncRNA-Protein Interactions: A Key to Deciphering LncRNA Mechanisms.Biomolecules · 2025Review
- Targeting Glioblastoma Stem Cells via EphA2: Structural Insights into the RNA Aptamer A40s for Precision Therapy.Journal of chemical information and modeling · 2025Article
- Current perspectives in drug targeting intrinsically disordered proteins and biomolecular condensates.BMC biology · 2025Review
- Decoding the effects of mutation on protein interactions using machine learning.Biophysics reviews · 2025Review
- Advances and Mechanisms of RNA-Ligand Interaction Predictions.Life (Basel, Switzerland) · 2025Review
- AI-integrated network for RNA complex structure and dynamic prediction.Biophysics reviews · 2024Review
- Advances and Challenges in Scoring Functions for RNA-Protein Complex Structure Prediction.Biomolecules · 2024Review
- Generative language models on nucleotide sequences of human genes.Scientific reports · 2024Article
- Review and Comparative Analysis of Methods and Advancements in Predicting Protein Complex Structure.Interdisciplinary sciences, computational life sciences · 2024Review
- Mitochondrial RNA Helicases: Key Players in the Regulation of Plant Organellar RNA Splicing and Gene Expression.International journal of molecular sciences · 2024Review
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5 authors.
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Abstract
RNA-protein complexes underlie numerous cellular processes, including basic translation and gene regulation. The high-resolution structure determination of the RNA-protein complexes is essential for elucidating their functions. Therefore, computational methods capable of identifying the native-like RNA-protein structures are needed. To address this challenge, we thus develop DRPScore, a deep-learning-based approach for identifying native-like RNA-protein structures. DRPScore is tested on representative sets of RNA-protein complexes with various degrees of binding-induced conformation change ranging from fully rigid docking (bound-bound) to fully flexible docking (unbound-unbound). Out of the top 20 predictions, DRPScore selects native-like structures with a success rate of 91.67% on the testing set of bound RNA-protein complexes and 56.14% on the unbound complexes. DRPScore consistently outperforms existing methods with a roughly 10.53-15.79% improvement, even for the most difficult unbound cases. Furthermore, DRPScore significantly improves the accuracy of the native interface interaction predictions. DRPScore should be broadly useful for modeling and designing RNA-protein complexes.
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