Pseudokinases repurpose flexibility signatures associated with the protein kinase fold for noncatalytic roles.
Anindita PaulSeemadri SubhadarshiniNarayanaswamy SrinivasanPublished in: Proteins (2021)
The bilobal protein kinase-like fold in pseudokinases lack one or more catalytic residues, conserved in canonical protein kinases, and are considered enzymatically deficient. Tertiary structures of pseudokinases reveal that their loops topologically equivalent to activation segments of kinases adopt contracted configurations, which is typically extended in active conformation of kinases. Herein, anisotropic network model based normal mode analysis (NMA) was conducted on 51 active conformation structures of protein kinases and 26 crystal structures of pseudokinases. Our observations indicate that although backbone fluctuation profiles are similar for individual kinase-pseudokinase families, low intensity mean square fluctuations in pseudo-activation segment and other sub-structures impart rigidity to pseudokinases. Analyses of collective motions from functional modes reveal that pseudokinases, compared to active kinases, undergo distinct conformational transitions using the same structural fold. All-atom NMA of protein kinase-pseudokinase pairs from each family, sharing high amino acid sequence identities, yielded distinct community clusters, partitioned by residues exhibiting highly correlated fluctuations. It appears that atomic fluctuations from equivalent activation segments guide community membership and network topologies for respective kinase and pseudokinase. Our findings indicate that such adaptations in backbone and side-chain fluctuations render pseudokinases competent for catalysis-independent roles.
Keyphrases
- protein kinase
- amino acid
- healthcare
- molecular dynamics simulations
- high resolution
- genome wide
- mental health
- molecular dynamics
- protein protein
- binding protein
- small molecule
- social media
- dna methylation
- high intensity
- crystal structure
- gene expression
- transcription factor
- health information
- single molecule
- network analysis