Protein kinases (PKs), one of the largest and functionally divergent gene families, mediate most of the signal transduction pathways in eukaryotic cells by the modification of substrate activity. They function as key regulators of a number of biological functions, prominently in signal transduction and coordination of complex processes such as cell cycle and embryonic development [1]. Mutations and dysregulation of protein kinases play causal roles in the onset of multiple human diseases and thus serve as potential drug targets. KinG (Kinases encoded in Genomes) is a comprehensive collection of Ser/Thr/Tyr specific protein kinases and similar sequences encoded in the completed genomes of eukaryotes prokaryotes and viruses [2]. The full complement of protein kinases in various completely sequenced genomes hosted at (http://king.mbu.iisc.ernet.in) provides a detailed listing of the Ser/Thr/Tyr protein kinases in various organisms, accompanied by other features such as protein kinase subfamily classification and domain organization. The kinases in the database are classified based on the Hanks and Hunter group classification [3]. The database enables the retrieval of protein kinases using several search option and also kinases belonging to specified subfamily or with a specific domain combination. It also hosts an in-house program for identifying if an input sequence is likely to be a kinase or not. Protein kinases were identified using a combination of multiple profile search approaches such as RPS-BLAST and hidden Markov model (HMM) matching using Hmmscan which have been previously benchmarked and used in our earlier kinome analysis for several other genomes [2,4,5]. Conditions for identification of homologues/kinases in RPS-BLAST searches include an e-value cut off of 0.0001 and a 70% query coverage. E-value cut off used for HMM based search was 0.01. Further, curation of protein kinases has been done based on presence of the conserved catalytic aspartate residue.