ArticleBMC bioinformatics2015
RNA-binding residues prediction using structural features.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 27 citations in OpenAlex.
- A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond.Briefings in bioinformatics · 2024Review
- HybridRNAbind: prediction of RNA interacting residues across structure-annotated and disorder-annotated proteins.Nucleic acids research · 2023Article
- PRIME-3D2D is a 3D2D model to predict binding sites of protein-RNA interaction.Communications biology · 2020Article
- iProDNA-CapsNet: identifying protein-DNA binding residues using capsule neural networks.BMC bioinformatics · 2019Article
- A deep learning framework to predict binding preference of RNA constituents on protein surface.Nature communications · 2019Article
- Computational approaches for the analysis of RNA-protein interactions: A primer for biologists.The Journal of biological chemistry · 2019Review
- Systematic Analysis of the Binding Surfaces between tRNAs and Their Respective Aminoacyl tRNA Synthetase Based on Structural and Evolutionary Data.Frontiers in genetics · 2017Article
- Protein-RNA interactions: structural biology and computational modeling techniques.Biophysical reviews · 2016Review
- The parameter sensitivity of random forests.BMC bioinformatics · 2016Article
- Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors.BMC bioinformatics · 2016Article
- Computational Prediction of RNA-Binding Proteins and Binding Sites.International journal of molecular sciences · 2015Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRNA-protein complexes play an essential role in many biological processes. To explore potential functions of RNA-protein complexes, it's important to identify RNA-binding residues in proteins.
resultsIn this work, we propose a set of new structural features for RNA-binding residue prediction. A set of template patches are first extracted from RNA-binding interfaces. To construct structural features for a residue, we compare its surrounding patches with each template patch and use the accumulated distances as its structural features. These new features provide sufficient structural information of surrounding surface of a residue and they can be used to measure the structural similarity between the surface surrounding two residues. The new structural features, together with other sequence features, are used to predict RNA-binding residues using ensemble learning technique.
conclusionsThe experimental results reveal the effectiveness of the proposed structural features. In addition, the clustering results on template patches exhibit distinct structural patterns of RNA-binding sites, although the sequences of template patches in the same cluster are not conserved. We speculate that RNAs may have structure preferences when binding with proteins.
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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.