PreDNA: Accurate prediction of DNA-binding sites in proteins by integrating sequence and geometric structure information

Abstract

Motivation: Protein-DNA interactions often take part in various crucial processes, which are essential for cellular function. The identification of DNA-binding sites in proteins is important for understanding the molecular mechanisms of protein-DNA interaction. Thus, we have developed an improved method to predict DNA-binding sites by integrating structural alignment algorithm and support vector machine-based methods.Results: Evaluated on a new non-redundant protein set with 224 chains, the method has 80.7 sensitivity and 82.9 specificity in the 5-fold cross-validation test. In addition, it predicts DNA-binding sites with 85.1 sensitivity and 85.3 specificity when tested on a dataset with 62 protein-DNA complexes. Compared with a recently published method, BindN+, our method predicts DNA-binding sites with a 7 better area under the receiver operating characteristic curve value when tested on the same dataset. Many important problems in cell biology require the dense non-linear interactions between functional modules be considered. Thus, our prediction method will be useful in detecting such complex interactions. © The Author 2013.