ArticleJournal of computational chemistry2013
A nonredundant structure dataset for benchmarking protein-RNA computational docking.
Article in Journal of computational chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Differentiation of RNA-protein docking structures through molecular dynamics simulation and machine learning methods.Briefings in bioinformatics · 2026Article
- Dockground: The Resource Expands to Protein-RNA Interactome.Journal of molecular biology · 2025Article
- Assessing interface accuracy in macromolecular complexes.PloS one · 2025Article
- 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
- RPpocket: An RNA-Protein Intuitive Database with RNA Pocket Topology Resources.International journal of molecular sciences · 2022Article
- Conformational variability in proteins bound to single-stranded DNA: A new benchmark for new docking perspectives.Proteins · 2022Article
- pyDockDNA: A new web server for energy-based protein-DNA docking and scoring.Frontiers in molecular biosciences · 2022Article
- The HDOCK server for integrated protein-protein docking.Nature protocols · 2020Article
- PepPro: A Nonredundant Structure Data Set for Benchmarking Peptide-Protein Computational Docking.Journal of computational chemistry · 2020Article
- Scoring Functions for Protein-RNA Complex Structure Prediction: Advances, Applications, and Future Directions.Communications in information and systems · 2020Article
- A structure-based model for the prediction of protein-RNA binding affinity.RNA (New York, N.Y.) · 2019Article
- Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes.RNA (New York, N.Y.) · 2018Article
- Molecular Modeling Applied to Nucleic Acid-Based Molecule Development.Biomolecules · 2018Review
- Review
- Determination of an effective scoring function for RNA-RNA interactions with a physics-based double-iterative method.Nucleic acids research · 2018Article
- HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.Nucleic acids research · 2017Article
- A Graph Approach to Mining Biological Patterns in the Binding Interfaces.Journal of computational biology : a journal of computational molecular cell biology · 2017Article
- A pair-conformation-dependent scoring function for evaluating 3D RNA-protein complex structures.PloS one · 2017Article
- Using 3dRPC for RNA-protein complex structure prediction.Biophysics reports · 2016Article
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2 authors.
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Abstract
Protein-RNA interactions play an important role in many biological processes. The ability to predict the molecular structures of protein-RNA complexes from docking would be valuable for understanding the underlying chemical mechanisms. We have developed a novel nonredundant benchmark dataset for protein-RNA docking and scoring. The diverse dataset of 72 targets consists of 52 unbound-unbound test complexes, and 20 unbound-bound test complexes. Here, unbound-unbound complexes refer to cases in which both binding partners of the cocrystallized complex are either in apo form or in a conformation taken from a different protein-RNA complex, whereas unbound-bound complexes are cases in which only one of the two binding partners has another experimentally determined conformation. The dataset is classified into three categories according to the interface root mean square deviation and the percentage of native contacts in the unbound structures: 49 easy, 16 medium, and 7 difficult targets. The bound and unbound cases of the benchmark dataset are expected to benefit the development and improvement of docking and scoring algorithms for the docking community. All the easy-to-view structures are freely available to the public at http://zoulab.dalton.missouri.edu/RNAbenchmark/.
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