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1.  hUbiquitome: a database of experimentally verified ubiquitination cascades in humans 
Protein ubiquitination is an evolutionarily conserved and functionally diverse post-translational modification achieved through the sequential action of E1-activating enzymes, E2-conjugating enzymes and E3 ligases. A summary of validated ubiquitination substrates have been presented and a prediction of new substrates have been conducted in yeast. However, a systematic summary of human ubiquitination substrates containing experimental evidence and the enzymatic cascade of each substrate is not available. In the present study, hUbiquitome web resource is introduced, a public resource for the retrieval of experimentally verified human ubiquitination enzymes and substrates. hUbiquitome is the first comprehensive database of human ubiquitination cascades. Currently, hUbiquitome has in its repertoire curated data comprising 1 E1 enzyme, 12 E2 enzymes, 138 E3 ligases or complexes, 279 different substrate proteins and 17 deubiquitination enzyme terms. The biological functions of substrates from different kinds of E3s were analyzed using the collected data. The findings show that substrates ubiquitinated by RING (Really Interesting New Gene) E3s are enriched most in apoptosis-related processes, whereas substrates ubiquitinated by other E3s are enriched in gene expression-associated processes. An analysis of the data demonstrates the biological process preferences of the different kinds of E3s. hUbiquitome is the first database to systematically collect experimentally validated ubiquitinated proteins and related ubiquitination cascade enzymes which might be helpful in the field of ubiquitination-modification research.
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PMCID: PMC3228279  PMID: 22134927
2.  Identifying Human Kinase-Specific Protein Phosphorylation Sites by Integrating Heterogeneous Information from Various Sources 
PLoS ONE  2010;5(11):e15411.
Phosphorylation is an important type of protein post-translational modification. Identification of possible phosphorylation sites of a protein is important for understanding its functions. Unbiased screening for phosphorylation sites by in vitro or in vivo experiments is time consuming and expensive; in silico prediction can provide functional candidates and help narrow down the experimental efforts. Most of the existing prediction algorithms take only the polypeptide sequence around the phosphorylation sites into consideration. However, protein phosphorylation is a very complex biological process in vivo. The polypeptide sequences around the potential sites are not sufficient to determine the phosphorylation status of those residues. In the current work, we integrated various data sources such as protein functional domains, protein subcellular location and protein-protein interactions, along with the polypeptide sequences to predict protein phosphorylation sites. The heterogeneous information significantly boosted the prediction accuracy for some kinase families. To demonstrate potential application of our method, we scanned a set of human proteins and predicted putative phosphorylation sites for Cyclin-dependent kinases, Casein kinase 2, Glycogen synthase kinase 3, Mitogen-activated protein kinases, protein kinase A, and protein kinase C families (avaiable at The predicted phosphorylation sites can serve as candidates for further experimental validation. Our strategy may also be applicable for the in silico identification of other post-translational modification substrates.
PMCID: PMC2981550  PMID: 21085571

Results 1-2 (2)