title: Molecular Dynamics Simulations and Structural Network Analysis of c-Abl and c-Src Kinase Core Proteins: Capturing Allosteric Mechanisms and Communication Pathways from Residue Centrality.
abstract: The Abl and Src tyrosine kinases play a fundamental regulatory role in orchestrating functional processes in cellular networks and represent an important class of therapeutic targets. Crystallographic studies of these kinases have revealed a similar structural organization of multidomain complexes that confers salient features of their regulatory mechanisms. Molecular characterization of the interaction networks and regulatory residues by which the SH3 and SH2 domains act cooperatively with the catalytic domain to suppress or promote kinase activation presents an active area of structural, biochemical, and computational investigations. In this work, we combine biophysical simulations with computational modeling of the residue interaction networks to characterize allosteric mechanisms of kinase regulation and gain insight into differential sensitivity of c-Abl and c-Src kinases to specific drug binding. Using these approaches, we examine dynamics of cooperative rearrangements in the residue interaction networks and elucidate the structural role of regulatory residues responsible for modulation of kinase activity. We have found that global network parameters such as residue centrality can unambiguously distinguish functional sites that are responsible for mediating allosteric interactions in the regulatory assemblies. This study has revealed mechanistic aspects of allosteric mechanisms and communication pathways by which the SH3 and SH2 domains may exert their regulatory influence on the catalytic domain and kinase activity. We have also found that high centrality residues can be linked to each other to form efficient and robust routes that transmit allosteric signals between spatially separated regulatory regions. The presented results have demonstrated that global features of the residue interaction networks may serve as transparent and robust indicators of kinase regulatory mechanisms and accurately pinpoint key functional residues.
authors.affiliation: Graduate Program in Computational and Data Sciences, Department of Computational Sciences, Schmid College of Science and Technology, Chapman University , One University Drive, Orange, California 92866, United States.
authors.forename: Amanda
authors.initials: A
authors.lastname: Tse
authors.affiliation: Graduate Program in Computational and Data Sciences, Department of Computational Sciences, Schmid College of Science and Technology, Chapman University , One University Drive, Orange, California 92866, United States.|Chapman University School of Pharmacy , Irvine, California 92618, United States.
authors.forename: Gennady M
authors.initials: GM
authors.lastname: Verkhivker
mesh_terms: D000494:Allosteric Regulation; D000081247:CSK Tyrosine-Protein Kinase; D006801:Humans; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D060066:Protein Interaction Maps; D016315:Proto-Oncogene Proteins c-abl / Q000737:chemistry / Q000378:metabolism*; D015398:Signal Transduction; D018909:src Homology Domains; D019061:src-Family Kinases / Q000737:chemistry / Q000378:metabolism*
chemical_list: D000081247:CSK Tyrosine-Protein Kinase; D016315:Proto-Oncogene Proteins c-abl; D019061:src-Family Kinases; C000631346:CSK protein, human