期刊
NUCLEIC ACIDS RESEARCH
卷 35, 期 5, 页码 1465-1477出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkm008
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资金
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM058187] Funding Source: NIH RePORTER
- NIGMS NIH HHS [R01 GM058187, GM58187] Funding Source: Medline
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 DNAbinding 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.
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