Analysis of the human kinome using methods including fold recognition reveals two novel kinases.
BACKGROUND
Protein sequence similarity is a commonly used criterion for inferring the unknown function of a protein from a protein of known function. However, proteins can diverge significantly over time such that sequence similarity is difficult, if not impossible, to find. In some cases, a structural similarity remains over long evolutionary time scales and once detected can be used to predict function.


RESULTS
Here we employed a high-throughput approach to assign structural and functional annotation to the human proteome, focusing on the collection of human protein kinases, the human kinome. We compared human protein sequences to a library of domains from known structures using WU-BLAST, PSI-BLAST, and 123D. This approach utilized both sequence comparison and fold recognition methods. The resulting set of potential protein kinases was cross-checked against previously identified human protein kinases, and analyzed for conserved kinase motifs.


CONCLUSIONS
We demonstrate that our structure-based method can be used to identify both typical and atypical human protein kinases. We also identify two potentially novel kinases that contain an interesting combination of kinase and acyl-CoA dehydrogenase domains.
Briedis
Kristine M
KM
Bioinformatics Program, University of California San Diego, La Jolla, California, USA. kbriedis@ucsd.edu
Starr
Ayelet
A
Bourne
Philip E
PE
D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D011487:Protein Conformation; D011494:Protein Kinases; D011506:Proteins / Q000737:chemistry / Q000502:physiology*; D020543:Proteome; D012984:Software
D011506:Proteins; D020543:Proteome; D011494:Protein Kinases