Abstract
The Eukaryotic Protein Kinases (EPKs) share a conserved hydrophobic core that conceptualizes our understanding of their regulation and catalysis. This EPK core was first described by 12 subdomains, which were later mapped to conserved elements of secondary structure in the EPK core when the first structure of PKA kinase became available. Much biochemistry, thermodynamics and biophysics has been subsequently done on many EPKs since then to explore similarities and differences in their allosteric control. The discovery of the Hydrophobic Spines in recent years has provided a novel tool for understanding both entropy driven allostery and catalysis. Both entropy driven allostery and catalysis are essentially dependent on internal protein dynamics that has been described by NMR as slow motions in the millisecond time frame. Although time and cost intensive, these NMR studies are essential and provide information for residue side chain and main chain dynamics. However, a number of sites in the EPK core evade labeling, and it becomes difficult to study them. To understand these protein dynamics further we have hence ventured into the in‐silico system of Molecular Dynamics simulations that are increasingly providing convincing information on par with NMR details. Our Graph theory methods applied to these simulations have allowed us to define dynamic clusters of residues whose correlated motions define the allosteric network of the EPK core in the PKA catalytic subunit. We call these clusters as ‘Communities’ and the cluster network is defined by a ‘Community Map’. Community maps of PKA at different steps of the catalytic cycle have allowed for dissection of internal protein dynamics that must work alongside catalysis. These community maps also allow for understanding allosteric mutations such as Y204A in PKA that are far from the active site but affect EPK function. Many such sites in EPKs, which remain unexplained, are found to be mutated in cancer genes. These Community maps hence allow for a novel, yet unexplored dynamics‐based criterion for understanding EPK modulation in molecular medicine.Support or Funding InformationNIH grant GM19301 and the Howard Hughes Medical Institute
Published Version
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