Next Article in Journal
Molecular Characterization and Functional Analysis of Three Pathogenesis-Related Cytochrome P450 Genes from Bursaphelenchus xylophilus (Tylenchida: Aphelenchoidoidea)
Next Article in Special Issue
Molecular Dynamics Simulations of Acylpeptide Hydrolase Bound to Chlorpyrifosmethyl Oxon and Dichlorvos
Previous Article in Journal
Spectrofluorometric and Molecular Docking Studies on the Binding of Curcumenol and Curcumenone to Human Serum Albumin
Previous Article in Special Issue
Efficient Prediction of Progesterone Receptor Interactome Using a Support Vector Machine Model

An Overview of the Prediction of Protein DNA-Binding Sites

Center for Computational Biology, National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
Author to whom correspondence should be addressed.
Academic Editor: Christo Christov
Int. J. Mol. Sci. 2015, 16(3), 5194-5215;
Received: 31 December 2014 / Revised: 21 February 2015 / Accepted: 27 February 2015 / Published: 6 March 2015
(This article belongs to the Collection Proteins and Protein-Ligand Interactions)
Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications. View Full-Text
Keywords: DNA-binding site; prediction; machine learning method; bioinformatics DNA-binding site; prediction; machine learning method; bioinformatics
Show Figures

Figure 1

MDPI and ACS Style

Si, J.; Zhao, R.; Wu, R. An Overview of the Prediction of Protein DNA-Binding Sites. Int. J. Mol. Sci. 2015, 16, 5194-5215.

AMA Style

Si J, Zhao R, Wu R. An Overview of the Prediction of Protein DNA-Binding Sites. International Journal of Molecular Sciences. 2015; 16(3):5194-5215.

Chicago/Turabian Style

Si, Jingna, Rui Zhao, and Rongling Wu. 2015. "An Overview of the Prediction of Protein DNA-Binding Sites" International Journal of Molecular Sciences 16, no. 3: 5194-5215.

Find Other Styles

Article Access Map by Country/Region

Only visits after 24 November 2015 are recorded.
Back to TopTop