Prediction of DNA-binding protein based on alpha shape modeling

Previous studies about protein-DNA interaction focused on the bound structure of DNA-binding proteins and provided good but not practical results. In our work, we apply an alpha shape model to represent the surface structure of the protein-DNA complex and use structural alignment to develop an interface-atom curvature-dependent conditional probability discriminatory function for the prediction of unbound DNA-binding protein. The proposed method provides good performance in predicting unbound structure of DNA-binding protein which is potentially useful in many fields. Computer experiment results show that the curvature-dependent formalism with the optimal parameters can achieve sensitivity ranges from 48.08% to 44.23% and specificity ranges from 73.82% to 84.29%.