title: Correlated mutation analysis on the catalytic domains of serine/threonine protein kinases.
abstract: BACKGROUND
  Protein kinases (PKs) have emerged as the largest family of signaling proteins in eukaryotic cells and are involved in every aspect of cellular regulation. Great progresses have been made in understanding the mechanisms of PKs phosphorylating their substrates, but the detailed mechanisms, by which PKs ensure their substrate specificity with their structurally conserved catalytic domains, still have not been adequately understood. Correlated mutation analysis based on large sets of diverse sequence data may provide new insights into this question.
  
  
  RESULTS
  Statistical coupling, residue correlation and mutual information analyses along with clustering were applied to analyze the structure-based multiple sequence alignment of the catalytic domains of the Ser/Thr PK family. Two clusters of highly coupled sites were identified. Mapping these positions onto the 3D structure of PK catalytic domain showed that these two groups of positions form two physically close networks. We named these two networks as theta-shaped and gamma-shaped networks, respectively.
  
  
  CONCLUSIONS
  The theta-shaped network links the active site cleft and the substrate binding regions, and might participate in PKs recognizing and interacting with their substrates. The gamma-shaped network is mainly situated in one side of substrate binding regions, linking the activation loop and the substrate binding regions. It might play a role in supporting the activation loop and substrate binding regions before catalysis, and participate in product releasing after phosphoryl transfer. Our results exhibit significant correlations with experimental observations, and can be used as a guide to further experimental and theoretical studies on the mechanisms of PKs interacting with their substrates.
authors.affiliation: State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China. xu_feng@fudan.edu.cn
authors.forename: Feng
authors.initials: F
authors.lastname: Xu
authors.forename: Pan
authors.initials: P
authors.lastname: Du
authors.forename: Hongbo
authors.initials: H
authors.lastname: Shen
authors.forename: Hairong
authors.initials: H
authors.lastname: Hu
authors.forename: Qi
authors.initials: Q
authors.lastname: Wu
authors.forename: Jun
authors.initials: J
authors.lastname: Xie
authors.forename: Long
authors.initials: L
authors.lastname: Yu
mesh_terms: D000818:Animals; D020134:Catalytic Domain; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D004252:DNA Mutational Analysis; D030562:Databases, Protein; D006801:Humans; D008958:Models, Molecular; D010766:Phosphorylation; D011487:Protein Conformation; D017346:Protein Serine-Threonine Kinases / Q000737:chemistry* / Q000378:metabolism; D040901:Proteomics / Q000379:methods; D015398:Signal Transduction
chemical_list: D017346:Protein Serine-Threonine Kinases