ArticleBiophysics reports2016
Using 3dRPC for RNA-protein complex structure prediction.
Article in Biophysics reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Differentiation of RNA-protein docking structures through molecular dynamics simulation and machine learning methods.Briefings in bioinformatics · 2026Article
- RNA-protein interaction prediction using network-guided deep learning.Communications biology · 2025Article
- 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
- Evaluating native-like structures of RNA-protein complexes through the deep learning method.Nature communications · 2023Article
- A novel antiviral lncRNA, EDAL, shields a T309 O-GlcNAcylation site to promote EZH2 lysosomal degradation.Genome biology · 2020Article
- A structure-based model for the prediction of protein-RNA binding affinity.RNA (New York, N.Y.) · 2019Article
- Sampling Native-like Structures of RNA-Protein Complexes through Rosetta Folding and Docking.Structure (London, England : 1993) · 2019Article
- Review
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Authors and funding
3 authors.
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Abstract
3dRPC is a computational method designed for three-dimensional RNA-protein complex structure prediction. Starting from a protein structure and a RNA structure, 3dRPC first generates presumptive complex structures by RPDOCK and then evaluates the structures by RPRANK. RPDOCK is an FFT-based docking algorithm that takes features of RNA-protein interactions into consideration, and RPRANK is a knowledge-based potential using root mean square deviation as a measure. Here we give a detailed description of the usage of 3dRPC. The source code is available at http://biophy.hust.edu.cn/3dRPC.html.
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