ArticlePloS one2011
Exploiting a reduced set of weighted average features to improve prediction of DNA-binding residues from 3D structures.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Article
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- gRINN: a tool for calculation of residue interaction energies and protein energy network analysis of molecular dynamics simulations.Nucleic acids research · 2018Article
- Prediction of Effective Drug Combinations by an Improved Naïve Bayesian Algorithm.International journal of molecular sciences · 2018Article
- PredT4SE-Stack: Prediction of Bacterial Type IV Secreted Effectors From Protein Sequences Using a Stacked Ensemble Method.Frontiers in microbiology · 2018Article
- Analysis and prediction of single-stranded and double-stranded DNA binding proteins based on protein sequences.BMC bioinformatics · 2017Article
- An overview of the prediction of protein DNA-binding sites.International journal of molecular sciences · 2015Review
- Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features.Journal of cheminformatics · 2015Article
- Analysis and classification of DNA-binding sites in single-stranded and double-stranded DNA-binding proteins using protein information.IET systems biology · 2014Article
- A hadoop-based method to predict potential effective drug combination.BioMed research international · 2014Article
- Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.PloS one · 2014Article
- DBSI: DNA-binding site identifier.Nucleic acids research · 2013Article
- Small world network strategies for studying protein structures and binding.Computational and structural biotechnology journal · 2013Review
- Characterization and prediction of the binding site in DNA-binding proteins: improvement of accuracy by combining residue composition, evolutionary conservation and structural parameters.Nucleic acids research · 2012Article
- Prediction of heme binding residues from protein sequences with integrative sequence profiles.Proteome science · 2012Article
- Computational prediction of conformational B-cell epitopes from antigen primary structures by ensemble learning.PloS one · 2012Article
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4 authors.
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Abstract
Predicting DNA-binding residues from a protein three-dimensional structure is a key task of computational structural proteomics. In the present study, based on machine learning technology, we aim to explore a reduced set of weighted average features for improving prediction of DNA-binding residues on protein surfaces. Via constructing the spatial environment around a DNA-binding residue, a novel weighting factor is first proposed to quantify the distance-dependent contribution of each neighboring residue in determining the location of a binding residue. Then, a weighted average scheme is introduced to represent the surface patch of the considering residue. Finally, the classifier is trained on the reduced set of these weighted average features, consisting of evolutionary profile, interface propensity, betweenness centrality and solvent surface area of side chain. Experimental results on 5-fold cross validation and independent tests indicate that the new feature set are effective to describe DNA-binding residues and our approach has significantly better performance than two previous methods. Furthermore, a brief case study suggests that the weighted average features are powerful for identifying DNA-binding residues and are promising for further study of protein structure-function relationship. The source code and datasets are available upon request.
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