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Latest news:

Jan. 20, 2008:
The structural information, protein disorder regions, will be annotated on dbPTM in Feb. 2008!

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How to Link:

Users can directly link to dbPTM by Swiss-Prot ID.
For example:

http://dbPTM.mbc.
nctu.edu.tw/search
_result.php?swiss_id
=H31_HUMAN

 

PTM Resource:

- Swiss-Prot
- Phospho.ELM
- PhosphoSite
- Phosphorylation Site Database
- OGlycBase
- UbiProt

Version: 2.0
(Dec. 1, 2007)

Welcome to dbPTM!

dbPTM was proposed to integrate experimentally verified PTMs from several databases, and to annotate the predicted PTMs on Swiss-Prot proteins. This update extends dbPTM to a knowledgebase comprisingthe modified sites, solvent accessibility of substrate, protein secondary and tertiary structures, protein domains and protein variations.

Literature related to PTM, protein conservations and substrate site specificity are also analyzed. Moreover, various computational tools have been developed for more than ten PTM types, such as phosphorylation, glycosylation, acetylation, methylation, sulfation and sumoylation. This study compiles a PTM benchmark consisting of all available experimental PTM sites for performance evaluation of these computational tools. The interface is also redesigned and enhanced to facilitate access to the resource.


Citing dbPTM
T.Y. Lee, H.D. Huang*, J.H. Hung, H.Y. Huang, Y.S. Yang and T.H. Wang. (2006) "dbPTM: An information repository of protein post-translational modification" Nucleic Acids Research, Vol. 34, D622-D627. [PubMed]

Highlight of dbPTM
Computational Annotation of PTM

In the computational identification of PTMs, KinasePhos-like method was applied to 20 types of PTM with over 30 experimentally verified PTM sites, which were learned the computational models and then adopted to identify potential PTM sites against all Swiss-Prot proteins. The learned models were evaluated using k-fold cross validation. Table 2 lists the parameters of the predictive models that achieved the best predictive accuracy. To reduce the number of false positive predictions when the potential PTM sites were fully detected against the Swiss-Prot protein sequences, the predictive parameters were set to ensure a predictive specificity of 100%.


System Architecture


Improvements of dbPTM Update

To enhance the knowledge of protein post-translational modification, dbPTM was extended to a knowledgebase of PTM referable literatures, orthologous conserved regions, substrate specificity, relationship between PTMs and subcellular localization, and PTM benchmarks. The proposed knowledgebase provides effective information relating to each type of PTM, including orthologous conserved regions, relationship between PTMs and subcellular localization, and the substrate specificity such as the frequency of amino acids, the average solvent accessibility and the frequency of secondary structure surrounding the modified site. Moreover, the proposed PTM benchmark can be adopted to compare the predictive performance of various tools involved in the same type of PTM prediction, based on the same testing set.