A comprehensive tool for rapid and accurate prediction of kinase-specific phosphorylation sites in the human proteome

Kinase-regulated phosphorylation is a ubiquitous type of post-translational modification (PTM) in both eukaryotic and prokaryotic cells. Phosphorylation plays fundamental roles in many signalling pathways and biological processes, such as protein degradation and protein-protein interactions, and experimental studies have revealed that signalling defects caused by aberrant phosphorylation are highly associated with a variety of human diseases, especially cancers. In light of this, a number of computational methods aiming to accurately predict protein kinase-specific phosphorylation sites have been established, thereby facilitating phosphoproteomic data analysis. In this work, we present Quokka, a novel bioinformatics tool that allows users to rapidly and accurately identify human kinase-regulated phosphorylation sites. Quokka provides users with multiple prediction models, including a variety of sequence scoring functions and a logistic regression algorithm. A variety of experimental studies based on both benchmark and independent test datasets demonstrate that Quokka improves the prediction performance compared with state-of-the-art computational tools for phosphorylation prediction. We anticipate that Quokka will provide users with high-quality predicted human phosphorylation sites for hypothesis generation and further biological validation.


Please input a sequence in the FASTA format (example):[?]


The benchmark and independent test datasets for phosphorylation sites are available for download here

We have investigated the phosphorylation sites for human proteome with Quokka.

The proteome-wide prediction results for 11 kinase families can be downloaded here


AGC/AKT kinase family

AGC/PKA kinase family

AGC/PKC kinase family

Atypical/PIKK kinase family

CAMK/CAMKL kinase family

CMGC/CDK kinase family

CMGC/CK2 kinase family

CMGC/GSK kinase family

CMGC/MAPK kinase family

TK/Abl kinase family

TK/Src kinase family

If you have any questions, please do not hesitate to contact us.

Mail: fuyi.li1@monash.edu




If you are interested in our other works in the fields of bioinformatics and systems biology, please refer to the following websites for more information: