Department of Bioinformatics & Systems Biology, MOE Key Laboratory of Molecular Biophysics, College of Life Science and Technology and the Collaborative Innovation Center for Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Department of Biomedical Informatics, School of Basic Medical Sciences, MOE Key Laboratory of Molecular Cardiovascular Sciences, Center for Non-coding RNA Medicine, Peking University, Beijing 100191, China.
Genomics Proteomics Bioinformatics. 2018 Aug;16(4):244-251. doi: 10.1016/j.gpb.2018.06.004. Epub 2018 Sep 21.
Various posttranslational modifications (PTMs) participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently implicated in human diseases. Therefore, an integral resource of PTM-disease associations (PDAs) would be a great help for both academic research and clinical use. In this work, we reported PTMD, a well-curated database containing PTMs that are associated with human diseases. We manually collected 1950 known PDAs in 749 proteins for 23 types of PTMs and 275 types of diseases from the literature. Database analyses show that phosphorylation has the largest number of disease associations, whereas neurologic diseases have the largest number of PTM associations. We classified all known PDAs into six classes according to the PTM status in diseases and demonstrated that the upregulation and presence of PTM events account for a predominant proportion of disease-associated PTM events. By reconstructing a disease-gene network, we observed that breast cancers have the largest number of associated PTMs and AKT1 has the largest number of PTMs connected to diseases. Finally, the PTMD database was developed with detailed annotations and can be a useful resource for further analyzing the relations between PTMs and human diseases. PTMD is freely accessible at http://ptmd.biocuckoo.org.
各种翻译后修饰（PTMs）通过调节蛋白质功能参与几乎所有的生物过程，并且 PTM 的异常状态经常与人类疾病有关。因此，一个完整的 PTM-疾病关联（PDA）资源将对学术研究和临床应用都有很大的帮助。在这项工作中，我们报告了 PTMD，这是一个精心整理的数据库，包含与人类疾病相关的 PTMs。我们从文献中手动收集了 749 种蛋白质中的 23 种 PTM 和 275 种疾病的 1950 种已知的 PDA。数据库分析表明，磷酸化具有最多的疾病关联，而神经疾病具有最多的 PTM 关联。我们根据疾病中的 PTM 状态将所有已知的 PDA 分为六类，并表明 PTM 事件的上调和存在占疾病相关 PTM 事件的主要比例。通过重建疾病-基因网络，我们观察到乳腺癌具有最多的相关 PTM，并且 AKT1 具有与疾病相关的最多 PTM。最后，PTMD 数据库具有详细的注释，可以成为进一步分析 PTM 与人类疾病之间关系的有用资源。PTMD 可在 http://ptmd.biocuckoo.org 免费获取。
