DISPLAR: an accurate method for predicting DNA-binding sites on protein surfaces.
Structural and physical properties of DNA provide important constraints on the binding sites formed on surfaces of DNA-targeting proteins. Characteristics of such binding sites may form the basis for predicting DNA-binding sites from the structures of proteins alone. Such an approach has been successfully developed for predicting protein-protein interface. Here this approach is adapted for predicting DNA-binding sites. We used a representative set of 264 protein-DNA complexes from the Protein Data Bank to analyze characteristics and to train and test a neural network predictor of DNA-binding sites. The input to the predictor consisted of PSI-blast sequence profiles and solvent accessibilities of each surface residue and 14 of its closest neighboring residues. Predicted DNA-contacting residues cover 60% of actual DNA-contacting residues and have an accuracy of 76%. This method significantly outperforms previous attempts of DNA-binding site predictions. Its application to the prion protein yielded a DNA-binding site that is consistent with recent NMR chemical shift perturbation data, suggesting that it can complement experimental techniques in characterizing protein-DNA interfaces.
Tjong
Harianto
H
Department of Physics and Institute of Molecular Biophysics and School of Computational Science, Florida State University, Tallahassee, FL 32306, USA.
Zhou
Huan-Xiang
HX
D000596:Amino Acids / Q000737:chemistry; D001665:Binding Sites; D004247:DNA / Q000737:chemistry; D004268:DNA-Binding Proteins / Q000737:chemistry* / Q000145:classification; D008958:Models, Molecular; D016571:Neural Networks, Computer; D011328:Prions / Q000737:chemistry; D016601:RNA-Binding Proteins / Q000737:chemistry; D015203:Reproducibility of Results; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein
D000596:Amino Acids; D004268:DNA-Binding Proteins; D011328:Prions; D016601:RNA-Binding Proteins; D004247:DNA