title: Quantitative network mapping of the human kinome interactome reveals new clues for rational kinase inhibitor discovery and individualized cancer therapy.
abstract: The human kinome is gaining importance through its promising cancer therapeutic targets, yet no general model to address the kinase inhibitor resistance has emerged. Here, we constructed a systems biology-based framework to catalogue the human kinome, including 538 kinase genes, in the broader context of the human interactome. Specifically, we constructed three networks: a kinase-substrate interaction network containing 7,346 pairs connecting 379 kinases to 36,576 phosphorylation sites in 1,961 substrates, a protein-protein interaction network (PPIN) containing 92,699 pairs, and an atomic resolution PPIN containing 4,278 pairs. We identified the conserved regulatory phosphorylation motifs (e.g., Ser/Thr-Pro) using a sequence logo analysis. We found the typical anticancer target selection strategy that uses network hubs as drug targets, might lead to a high adverse drug reaction risk. Furthermore, we found the distinct network centrality of kinases creates a high anticancer drug resistance risk by feedback or crosstalk mechanisms within cellular networks. This notion is supported by the systematic network and pathway analyses that anticancer drug resistance genes are significantly enriched as hubs and heavily participate in multiple signaling pathways. Collectively, this comprehensive human kinome interactome map sheds light on anticancer drug resistance mechanisms and provides an innovative resource for rational kinase inhibitor design.
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
authors.forename: Feixiong
authors.initials: F
authors.lastname: Cheng
authors.forename: Peilin
authors.initials: P
authors.lastname: Jia
authors.forename: Quan
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA; Center for Quantitative Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA; Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA; Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.
authors.forename: Zhongming
authors.initials: Z
authors.lastname: Zhao
mesh_terms: D002874:Chromosome Mapping / Q000379:methods*; D055808:Drug Discovery; D006801:Humans; D053858:Metabolic Networks and Pathways; D009369:Neoplasms / Q000201:enzymology* / Q000235:genetics / Q000628:therapy*; D010766:Phosphorylation; D057285:Precision Medicine / Q000379:methods*; D047428:Protein Kinase Inhibitors / Q000494:pharmacology*; D011494:Protein Kinases / Q000235:genetics* / Q000378:metabolism*; D015398:Signal Transduction
chemical_list: D047428:Protein Kinase Inhibitors; D011494:Protein Kinases