NR AWXJ
AU Tjong,H.; Zhou,H.X.
TI DISPLAR: an accurate method for predicting DNA-binding sites on protein surfaces.
QU Nucleic Acids Research 2007; 35(5): 1465-77
PT evaluation studies; journal article; research support, n.i.h., extramural
AB 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.
MH Amino Acids/chemistry; Binding Sites; DNA/chemistry; DNA-Binding Proteins/*chemistry/classification; Models, Molecular; *Neural Networks (Computer); Prions/chemistry; RNA-Binding Proteins/chemistry; Reproducibility of Results; Sequence Alignment; Sequence Analysis, Protein
AD Department of Physics and Institute of Molecular Biophysics and School of Computational Science, Florida State University, Tallahassee, FL 32306, USA.
SP englisch
PO England