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Literature DB >> 20300450

Struct-NB: predicting protein-RNA binding sites using structural features.

Fadi Towfic¹, Cornelia Caragea, David C Gemperline, Drena Dobbs, Vasant Honavar.

Abstract

We analyse sequence and structural features of protein-RNA interfaces using RB-147, a non-redundant dataset of protein-RNA complexes extracted from the PDB. We train classifiers using machine learning algorithms to predict protein-RNA interfaces from sequence and structure-derived features of proteins. Our experiments show that Struct-NB, a Naive Bayes classifier that exploits structural features, outperforms its counterparts that use only sequence features to predict protein-RNA binding residues.

Entities: Chemical Disease Gene Species

Keywords: propensity; protein-RNA interactions; structural features

Mesh：

Substances：
RNA-Binding Proteins
RNA

Year: 2010 PMID： 20300450 PMCID： PMC2840657 DOI： 10.1504/ijdmb.2010.030965

Source DB: PubMed Journal: Int J Data Min Bioinform ISSN： 1748-5673 Impact factor: 0.667

21 in total

1. The Protein Data Bank.

Authors: H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal: Nucleic Acids Res Date: 2000-01-01 Impact factor: 16.971

2. CX, an algorithm that identifies protruding atoms in proteins.

Authors: Alessandro Pintar; Oliviero Carugo; Sándor Pongor
Journal: Bioinformatics Date: 2002-07 Impact factor: 6.937

Review 3. Pre-mRNA splicing: awash in a sea of proteins.

Authors: Melissa S Jurica; Melissa J Moore
Journal: Mol Cell Date: 2003-07 Impact factor: 17.970

4. Protein-RNA interactions: a structural analysis.

Authors: S Jones; D T Daley; N M Luscombe; H M Berman; J M Thornton
Journal: Nucleic Acids Res Date: 2001-02-15 Impact factor: 16.971

5. A neural network method for identification of RNA-interacting residues in protein.

Authors: Euna Jeong; I-Fang Chung; Satoru Miyano
Journal: Genome Inform Date: 2004

6. The interpretation of protein structures: estimation of static accessibility.

Authors: B Lee; F M Richards
Journal: J Mol Biol Date: 1971-02-14 Impact factor: 5.469

7. The molecular surface package.

Authors: M L Connolly
Journal: J Mol Graph Date: 1993-06

8. Fractal surfaces of proteins.

Authors: M Lewis; D C Rees
Journal: Science Date: 1985-12-06 Impact factor: 47.728

9. Statistical analysis of atomic contacts at RNA-protein interfaces.

Authors: M Treger; E Westhof
Journal: J Mol Recognit Date: 2001 Jul-Aug Impact factor: 2.137

10. Glycosylation site prediction using ensembles of Support Vector Machine classifiers.

Authors: Cornelia Caragea; Jivko Sinapov; Adrian Silvescu; Drena Dobbs; Vasant Honavar
Journal: BMC Bioinformatics Date: 2007-11-09 Impact factor: 3.169

19 in total

1. Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction.

Authors: Wen Hu; Liu Qin; Menglong Li; Xuemei Pu; Yanzhi Guo
Journal: J Comput Aided Mol Des Date: 2018-11-26 Impact factor: 3.686

Struct-NB: predicting protein-RNA binding sites using structural features.

1. The Protein Data Bank.

2. CX, an algorithm that identifies protruding atoms in proteins.

Review 3. Pre-mRNA splicing: awash in a sea of proteins.

4. Protein-RNA interactions: a structural analysis.

5. A neural network method for identification of RNA-interacting residues in protein.

6. The interpretation of protein structures: estimation of static accessibility.

7. The molecular surface package.

8. Fractal surfaces of proteins.

9. Statistical analysis of atomic contacts at RNA-protein interfaces.

10. Glycosylation site prediction using ensembles of Support Vector Machine classifiers.

1. Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction.

Review 2. Computational approaches for the analysis of RNA-protein interactions: A primer for biologists.

Review 3. Prediction of RNA binding proteins comes of age from low resolution to high resolution.

4. PRIDB: a Protein-RNA interface database.

5. Predicting RNA-binding residues from evolutionary information and sequence conservation.

6. From face to interface recognition: a differential geometric approach to distinguish DNA from RNA binding surfaces.

7. SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

8. Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

9. RNA-binding residues prediction using structural features.

Review 10. Computational Prediction of RNA-Binding Proteins and Binding Sites.