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ARTICLE
Year : 2011  |  Volume : 2  |  Issue : 3  |  Page : 10-11  

Multi-domain protein kinases: Evolution of domain architectures, classification, hybrid protein kinases


Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India

Date of Web Publication26-May-2012

Correspondence Address:
N Srinivasan
Molecular Biophysics Unit, Indian Institute of Science, Bangalore
India
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Source of Support: None, Conflict of Interest: None


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How to cite this article:
Srinivasan N. Multi-domain protein kinases: Evolution of domain architectures, classification, hybrid protein kinases. J Nat Sc Biol Med 2011;2, Suppl S1:10-1

How to cite this URL:
Srinivasan N. Multi-domain protein kinases: Evolution of domain architectures, classification, hybrid protein kinases. J Nat Sc Biol Med [serial online] 2011 [cited 2020 Feb 24];2, Suppl S1:10-1. Available from: http://www.jnsbm.org/text.asp?2011/2/3/10/95726

Protein phosphorylation is a generic way to regulate signal transduction pathways in all kingdoms of life. In many organisms, it is achieved by the large family of Ser/Thr/Tyr protein kinases which are traditionally classified into groups and subfamilies on the basis of the amino acid sequence of their catalytic domains. Many protein kinases are multi-domain in nature but the diversity of the accessory domains and their organization are usually not taken into account while classifying kinases into groups or subfamilies.

Here, we present an approach which considers amino acid sequences of complete gene products, in order to suggest refinements in sets of pre-classified sequences. The strategy is based on alignment-free similarity scores and iterative Area Under the Curve (AUC) computation. Similarity scores are computed by detecting common patterns between two sequences and scoring them using a substitution matrix, with a consistent normalization scheme. This allows us to handle full-length sequences, and implicitly takes into account domain diversity and domain shuffling. We quantitatively validate our approach on a subset of 212 human protein kinases. We then employ it on the complete repertoire of human protein kinases and suggest few qualitative refinements in the subfamily assignment stored in the KinG database, which is based on catalytic domains only. Based on our new measure, we delineate 37 cases of potential hybrid kinases: sequences for which classical classification based entirely on catalytic domains is inconsistent with the full-length similarity scores computed here, which implicitly consider multi-domain nature and regions outside the catalytic kinase domain. We also provide some examples of hybrid kinases of the protozoan parasite Entamoeba histolytica. The implicit consideration of multi-domain architectures is a valuable inclusion to complement other classification schemes. The proposed algorithm may also be employed to classify other families of enzymes with multi-domain architecture.




 

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