期刊
JOURNAL OF PROTEOME RESEARCH
卷 15, 期 12, 页码 4234-4244出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.6b00240
关键词
acylation; acetylation; malonylation; succinylation; glutarylation; prediction; proteomics; posttranslational modification; PTM
资金
- National Natural Science Foundation of China [31400666, 31371337, 31671175]
- National Basic Research Program of China [2012CB934003]
- National High-Tech Research and Development Program of China [2012AA020401]
- Major Equipment Program of China [2011YQ030134]
- National Laboratory of Biomacromolecules
Liquid chromatography tandem mass spectrometry (LC-MS/MS)based proteomic methods have been widely used to identify lysine acylation proteins. However, these experimental approaches often fail to detect proteins that are in low abundance or absent in specific biological samples. To circumvent these problems, we developed a computational method to predict lysine acylation, including acetylation, malonylation, succinylation, and glutarylation. The prediction algorithm integrated flanking primary sequence determinants and evolutionary conservation of acylated lysine as well as multiple protein functional annotation features including gene ontology, conserved domains, and protein protein interactions. The inclusion of functional annotation features increases predictive power oversimple sequence considerations for four of the acylation species evaluated. For example, the Matthews correlation coefficient (MCC) for the prediction of malonylation increased from 0.26 to 0.73. The performance of prediction was validated against an independent data set for malonylation. Likewise, when tested with independent data sets, the algorithm displayed improved sensitivity and specificity over existing methods. Experimental validation by Western blot experiments and LC-MS/ MS detection further attested to the performance of prediction. We then applied our algorithm on to the mouse proteome and reported the global-scale prediction of lysine acetylation, malonylation, succinylation, and glutarylation, which should serve as a valuable resource for future functional studies.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据