PTMD: A Database of Human Disease-associated Post-translational Modifications

查看全文 作　　者：Haodong [1]Xu;Yongbo [1]Wang;Shaofeng [1]Lin;Wankun [1]Deng;Di [1]Peng;Qinghua [2]Cui;Yu [1]Xue

机构地区：[1]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;[2]Department of Biomedical Informatics, School of Basic Medical Sciences, MOE Key Laboratory of Molecular Cardiovascular Sciences, Center for Non-coding RNA Medicine, Peking University

出　　处：《Genomics, Proteomics & Bioinformatics》索引2018年第16卷第4期,共8页

基　　金：supported by grants from the Special Project on Precision Medicine under the National Key R&D Program of China (Grant Nos. 2017YFC0906600 and 2016YFC0903003);the Natural Science Foundation of China (Grant Nos. 31671360 and 81670462);the Fundamental Research Funds for the Central Universities (Grant No. 2017KFXKJC001);the National Program for Support of Top-Notch Young Professionals;the program for HUST Academic Frontier Youth Team, China 摘　　要：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 diseaseassociated PTM events. By reconstructing a disease–gene network, we observed that breast cancershave 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://gffzz7d3e84778ac14081huf5owbp966qn66k9.ffgz.tsg.suse.edu.cn. 关键词：神经疾病数据库 PTM 异常状态学术研究基因网络 http 蛋白质

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PTMD: A Database of Human Disease-associated Post-translational Modifications

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