Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database information

PTMD (Post translational modification database)

General information

Description: Here we provide a database of PTMD 1.0 (PTMs that are associated with human Diseases) that contains the manually curated associations between different PTM types and different diseases. Currently, PTMD contains 1,950 disease-associated PTM events in 749 proteins for 24 PTM types and 275 diseases. To better exhibit the relations between PTMs and diseases, we classified the PTM-disease associations into 6 classes, including U/D (Up-regulation/down-regulation of PTM levels), P/A (Presence/absence of PTMs) and C/N (Creation/disruption of PTM sites by mutations).
Year founded: 2018
Last update: 2018
Version:
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: China
Data type:
RNA
Data object:
NA
Database category:
Major organism:
Keywords:

Contact information

University/Institution: Huazhong University of Science and Technology
Address:
City: Wuhan
Province/State: Hubei
Country/Region: China
Contact name (PI/Team): Yu Xue
Contact email (PI/Helpdesk): xueyu@mail.hust.edu.cn

Related Database

Record metadata

Created on: 2018-09-21
Curated by:
Dong Zou [2019-12-05]
Dong Zou [2019-01-04]
Rabail Raza [2018-12-27]
Mengyu Pan [2018-09-21]

Ranking

All databases:
3258/4549 (28.402%)
Modification:
151/185 (18.919%)
3258
Total Rank
2
Citations
1
z-index

Community reviews

Not Rated
Data quality & quantity:
Content organization & presentation
System accessibility & reliability:

Word cloud

Publications

30244175
PTMD: A Database of Human Disease-associated Post-translational Modifications. [PMID: 30244175]
Xu H, Wang Y, Lin S, Deng W, Peng D, Cui Q, Xue Y.

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.

Genomics Proteomics Bioinformatics. 2018:16(4) | 2 Citations (from Europe PMC, 2020-02-08)