Discriminate RNA binding residues from DNA binding residues

Together with the problem of binding site prediction, it is very interesting to know whether there is a program that can discriminate RNA binding residues from DNA binding residues. This discrimination would first include three assumptions: i) residues from different proteins could be compared; ii) RNA binding and DNA binding adopt different driving forces; iii) such driving forces have been explored by current programs. We assessed this discrimination by mixing DNA binding residues of a data set with RNA binding residues of another data set.

According to the Figure, we find several machine learning based approaches display a discriminative ability for RNA binding residues, including PRNA, Predict_RBP, RNABindRPlus and RBscore_SVM. However, this cannot guarantee predictive ability, since all of the programs have AUC <0.5 on some data sets, which means the program favor the wrong type of residue. Further, we can find the programs PRNA, Predict_RBP, RNABindRPlus and RBscore_SVM have similar distribution for this test while their wAUC distributions are also similar. This result implies that these methods have similar prediction accuracies and similar preferences on data sets but cannot distinguish different residue types.