Applying Sequence Conservation Strategy to Predict Protein Phosphorylation Sites

[[abstract]]Phosphorylation, one of the most important post-translational modifications in proteins, is involved in biological signal transduction in various processes. During signal transduction, proteins’ phosphorylation and dephosphorylation provides a control mechanism for eukaryotes to activate or inhibit a number of enzymes and receptors. Therefore, if we can predict where phosphorylation is taking place, it will benefit relevant research significantly. In this study, a new sequence conservation method is proposed to create a model. Using known phosphorylated segments as a template for prediction and matching them with non-phosphorylated segments, we attempted to find their maximum similarity. Based on this, a threshold value for prediction was then for each template. Finally, unknown sequence segments to be predicted were substituted into the prediction model. The results were then compared with the 3 websites Netphos, Disphos and GPS, and a discussion on the following 5 kinds of estimation was conducted accordingly: Sensitivity (Sn), Specificity (Sp), Accuracy (Acc), Precision, and Mattews correlation coefficient (MCC). The results show that this method had relatively good performance in MCC and Acc prediction