title: Identification and classification of small molecule kinases: insights into substrate recognition and specificity.
abstract: BACKGROUND
  Many prokaryotic kinases that phosphorylate small molecule substrates, such as antibiotics, lipids and sugars, are evolutionarily related to Eukaryotic Protein Kinases (EPKs). These Eukaryotic-Like Kinases (ELKs) share the same overall structural fold as EPKs, but differ in their modes of regulation, substrate recognition and specificity-the sequence and structural determinants of which are poorly understood.
  
  
  RESULTS
  To better understand the basis for ELK specificity, we applied a Bayesian classification procedure designed to identify sequence determinants responsible for functional divergence. This reveals that a large and diverse family of aminoglycoside kinases, characterized members of which are involved in antibiotic resistance, fall into major sub-groups based on differences in putative substrate recognition motifs. Aminoglycoside kinase substrate specificity follows simple rules of alternating hydroxyl and amino groups that is strongly correlated with variations at the DFG + 1 position.
  
  
  CONCLUSIONS
  Substrate specificity determining features in small molecule kinases are mostly confined to the catalytic core and can be identified based on quantitative sequence and crystal structure comparisons.
authors.affiliation: Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA, 30602, USA. okrishnadev@gmail.com.
authors.forename: Krishnadev
authors.initials: K
authors.lastname: Oruganty
authors.affiliation: Department of Pathology and Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, 94158, USA. eric.talevich@gmail.com.
authors.forename: Eric E
authors.initials: EE
authors.lastname: Talevich
authors.affiliation: Institute for Genome Sciences and Department of Biochemistry & Molecular Biology, School of Medicine, University of Maryland, Baltimore, MD, 21201, USA. aneuwald@som.umaryland.edu.
authors.forename: Andrew F
authors.initials: AF
authors.lastname: Neuwald
authors.affiliation: Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA, 30602, USA. kannan@bmb.uga.edu.|Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA. kannan@bmb.uga.edu.
authors.forename: Natarajan
authors.initials: N
authors.lastname: Kannan
mesh_terms: D000595:Amino Acid Sequence; D001499:Bayes Theorem; D011494:Protein Kinases / Q000737:chemistry / Q000145:classification* / Q000378:metabolism; D017434:Protein Structure, Tertiary; D013379:Substrate Specificity
chemical_list: D011494:Protein Kinases