Lysine succinylation is a type of protein post-translational modification which is widely involved in cell differentiation, cell metabolism and other important physiological activities. To study the molecular mechanism of succinylation in depth, succinylation sites need to be accurately identified, and because experimental approaches are costly and time-consuming, there is a great demand for reliable computational methods. Feature extraction is a key step in building succinylation site prediction models, and the development of effective new features improves predictive accuracy. Because the number of false succinylation sites far exceeds that of true sites, traditional classifiers perform poorly, and designing a classifier to effectively handle highly imbalanced datasets has always been a challenge.
We propose a new computational method, iSuc-ChiDT, to identify succinylation sites in proteins. In iSuc-ChiDT, chi-square statistical difference table encoding is developed to extract positional features, and has the highest predictive accuracy and fewest features compared to binary encoding and physicochemical property encoding. The chi-square decision table (ChiDT) classifier is designed to implement imbalanced pattern classification. With a training set of 4748:50,551(true: false sites), independent tests showed that ChiDT significantly outperformed traditional classifiers (including random forest, artificial neural network and relaxed variable kernel density estimator) in predictive accuracy and only taking 17s. Using an independent testing set of experimentally identified succinylation sites, iSuc-ChiDT achieved sensitivity of 70.47%, specificity of 66.27%, Matthews correlation coefficient of 0.205, and a global accuracy index Q9 of 0.683, showing a significant improvement in sensitivity and overall accuracy compared to PSuccE, Success, SuccinSite and other existing succinylation site predictors.
iSuc-ChiDT shows great promise in predicting succinylation sites and is expected to facilitate further experimental investigation of protein succinylation.