Chen Qing-Yun, Tang Jijun, Du Pu-Feng
School of Computer Science and Technology, Tianjin University, Tianjin 300350, China.
Mol Biosyst. 2017 May 2;13(5):874-882. doi: 10.1039/c6mb00875e.
Post-translational modification (PTM) is essential for many biological processes. Covalent and generally enzymatic modification of proteins can impact the activity of proteins. Modified proteins would have more complex structures and functions. Knowing whether a specific residue is modified or not is significant to unravel the function and structure of this protein. As experimental approaches to discover protein PTM sites are always costly and time consuming, computational prediction methods are desirable alternative methods. Lysine phosphoglycerylation is a type of newly discovered PTM that is related to glycolytic process and glucose metabolism. Since the lysine phosphoglycerylation process requires no catalytic enzyme, its site selectivity mechanism is still not fully understood. In this study, we designed a novel computational method, namely PhoglyPred, to identify lysine phosphoglycerylation sites. By utilizing several different protein sequence descriptors, PhoglyPred achieved an overall accuracy of 90.3% in a Jackknife test, which is better than other state-of-the-art predictors. By analyzing the importance of different features using the F-score, we found several important sequence features, which may benefit future studies in understanding the site selectivity mechanism of lysine phosphoglycerylation.
翻译后修饰（PTM）对许多生物过程至关重要。蛋白质的共价修饰（通常是酶促修饰）会影响蛋白质的活性。被修饰的蛋白质会具有更复杂的结构和功能。了解特定残基是否被修饰对于阐明该蛋白质的功能和结构具有重要意义。由于发现蛋白质PTM位点的实验方法总是成本高昂且耗时，因此计算预测方法是理想的替代方法。赖氨酸磷酸甘油化是一种新发现的与糖酵解过程和葡萄糖代谢相关的PTM类型。由于赖氨酸磷酸甘油化过程不需要催化酶，其位点选择性机制仍未完全了解。在本研究中，我们设计了一种新的计算方法，即PhoglyPred，用于识别赖氨酸磷酸甘油化位点。通过使用几种不同的蛋白质序列描述符，PhoglyPred在留一法测试中总体准确率达到了90.3%，优于其他最先进的预测器。通过使用F分数分析不同特征的重要性，我们发现了几个重要的序列特征，这可能有助于未来研究了解赖氨酸磷酸甘油化的位点选择性机制。
