ProAcePred: prokaryote lysine acetylation sites prediction based on elastic net feature optimization

Motivation: Lysine acetylation exists extensively in prokaryotes, and plays a vital role in function adjustment. Recent progresses in the identification of prokaryote acetylation substrates and sites provide a great opportunity to explore the difference of substrate site specificity between prokaryotic and eukaryotic acetylation. Motif analysis suggests that prokaryotic and eukaryotic acetylation sites have distinct location-specific difference, and it is necessary to develop a prokaryote-specific acetylation sites prediction tool. Results: Therefore, we collected nine species of prokaryote lysine acetylation data from various databases and literature, and developed a novel online tool named ProAcePred for predicting prokaryote lysine acetylation sites. Optimization of feature vectors via elastic net could considerably improve the prediction performance. Feature analyses demonstrated that evolutionary information played significant roles in prediction model for prokaryote acetylation. Comparison between our method and other tools suggested that our species-specific prediction outperformed other existing works. We expect that the ProAcePred could provide more instructive help for further experimental investigation of prokaryotes acetylation. Availability and implementation: http://computbiol.ncu.edu.cn/ProAcePred. Supplementary information: Supplementary data are available at Bioinformatics online.