Analysis of the human kinome using methods including fold recognition reveals two novel kinases.

@article{citeulike:2805750, abstract = {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. METHODOLOGY/PRINCIPAL FINDINGS: 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/SIGNIFICANCE: 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.}, address = {Bioinformatics Program, University of California San Diego, La Jolla, California, USA. kbriedis@ucsd.edu}, author = {Briedis, K. M. and Starr, A. and Bourne, P. E. }, citeulike-article-id = {2805750}, doi = {10.1371/journal.pone.0001597}, issn = {1932-6203}, journal = {PLoS ONE}, keywords = {bioinformatics, kinome, methods}, number = {2}, posted-at = {2008-05-16 20:27:58}, priority = {2}, title = {Analysis of the human kinome using methods including fold recognition reveals two novel kinases.}, url = {http://dx.doi.org/10.1371/journal.pone.0001597}, volume = {3}, year = {2008} }

TY - JOUR ID - citeulike:2805750 L3 - citeulike-article-id:2805750 TI - Analysis of the human kinome using methods including fold recognition reveals two novel kinases. JF - PLoS ONE VL - 3 IS - 2 AD - Bioinformatics Program, University of California San Diego, La Jolla, California, USA. kbriedis@ucsd.edu SN - 1932-6203 N2 - 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. METHODOLOGY/PRINCIPAL FINDINGS: 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/SIGNIFICANCE: 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. KW - bioinformatics KW - kinome KW - methods AU - Briedis, KM AU - Starr, A AU - Bourne, PE PY - 2008/// UR - http://dx.doi.org/10.1371/journal.pone.0001597 ER -