Protein-DNA binding sites play an important role in various physiological and biochemical reactions. In this paper, we establish a special method and algorithm based on Bioinformatics to forecast Protein-DNA binding sites, we call it PdDNA. According to our method we have 2 mainly algorithm: SVM-based predictor and sequence-based predictor. SVM-based predictor is trained and classified by extracting features of central residues at binding sites, and sequence-based predictor scores amino acid sequences for correlation by Position-Specific Scoring Matrix(PSSM). Normalization and integration of the two results to obtain the final forecast. According to our algorithm, it predicts DNA-binding sites with 86.87% accuracy when tested on PDNA_62 dataset. Otherwise, we established PDNA_224 data set, and PdDNA also has 83.07% accuracy at a high level. Therefore, PdDNA is an effective method for predicting "Protein-DNA binding sites ".
