ArticleNucleic acids research2012
Characterization and prediction of the binding site in DNA-binding proteins: improvement of accuracy by combining residue composition, evolutionary conservation and structural parameters.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 31 citations in OpenAlex.
- Article
- EPDRNA: A Model for Identifying DNA-RNA Binding Sites in Disease-Related Proteins.The protein journal · 2024Article
- A comprehensive review of protein-centric predictors for biomolecular interactions: from proteins to nucleic acids and beyond.Briefings in bioinformatics · 2024Review
- ProDFace: A web-tool for the dissection of protein-DNA interfaces.Frontiers in molecular biosciences · 2022Article
- DeepDISE: DNA Binding Site Prediction Using a Deep Learning Method.International journal of molecular sciences · 2021Article
- Multiple protein-DNA interfaces unravelled by evolutionary information, physico-chemical and geometrical properties.PLoS computational biology · 2020Article
- Individually double minimum-distance definition of protein-RNA binding residues and application to structure-based prediction.Journal of computer-aided molecular design · 2018Article
- Structural changes in DNA-binding proteins on complexation.Nucleic acids research · 2018Article
- Analysis and prediction of single-stranded and double-stranded DNA binding proteins based on protein sequences.BMC bioinformatics · 2017Article
- Systematic Analyses and Prediction of Human Drug Side Effect Associated Proteins from the Perspective of Protein Evolution.Genome biology and evolution · 2017Article
- A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs.PLoS computational biology · 2015Article
- PNImodeler: web server for inferring protein-binding nucleotides from sequence data.BMC genomics · 2015Article
- SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.PloS one · 2015Article
- Analysis and classification of DNA-binding sites in single-stranded and double-stranded DNA-binding proteins using protein information.IET systems biology · 2014Article
- Sequence based prediction of DNA-binding proteins based on hybrid feature selection using random forest and Gaussian naïve Bayes.PloS one · 2014Article
- Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.PloS one · 2014Article
- PiDNA: Predicting protein-DNA interactions with structural models.Nucleic acids research · 2013Article
- SVM based model generation for binding site prediction on helix turn helix motif type of transcription factors in eukaryotes.Bioinformation · 2013Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a set of four parameters that in combination can predict DNA-binding residues on protein structures to a high degree of accuracy. These are the number of evolutionary conserved residues (N(cons)) and their spatial clustering (ρ(e)), hydrogen bond donor capability (D(p)) and residue propensity (R(p)). We first used these parameters to characterize 130 interfaces in a set of 126 DNA-binding proteins (DBPs). The applicability of these parameters both individually and in combination, to distinguish the true binding region from the rest of the protein surface was then analyzed. R(p) shows the best performance identifying the true interface with the top rank in 83% cases. Importantly, we also used the unbound-bound test cases of the protein-DNA docking benchmark to test the efficacy of our method. When applied to the unbound form of the DBPs, R(p) can distinguish 86% cases. Finally, we have applied the SVM approach for recognizing the interface region using the above parameters along with the individual amino acid composition as attributes. The accuracy of prediction is 90.5% for the bound structures and 93.6% for the unbound form of the 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.