title: The structural network of inflammation and cancer: merits and challenges.
abstract: Inflammation, the first line of defense against pathogens can contribute to all phases of tumorigenesis, including tumor initiation, promotion and metastasis. Within this framework, the Toll-like receptor (TLR) pathway plays a central role in inflammation and cancer. Although extremely useful, the classical representation of this, and other pathways in the cellular network in terms of nodes (proteins) and edges (interactions) is incomplete. Structural pathways can help complete missing parts of such diagrams: they demonstrate in detail how signals coming from different upstream pathways merge and propagate downstream, how parallel pathways compensate each other in drug resistant mutants, how multi-subunit signaling complexes form and in particular why they are needed and how they work, how allosteric events can control these proteins and their pathways, and intricate details of feedback loops and how kick in. They can also explain the mechanisms of some oncogenic SNP mutations. Constructing structural pathways is a challenging task. Here, our goal is to provide an overview of inflammation and cancer from the structural standpoint, focusing on the TLR pathway. We use the powerful PRISM (PRotein Interactions by Structural Matching) tool to reveal important structural information of interactions in and within key orchestrators of the TLR pathway, such as MyD88.
authors.affiliation: Center for Computational Biology and Bioinformatics, College of Engineering, Koc University, Rumelifeneri Yolu, Sariyer, Istanbul, Turkey. eguven@ku.edu.tr
authors.forename: Emine
authors.initials: E
authors.lastname: Guven Maiorov
authors.forename: Ozlem
authors.initials: O
authors.lastname: Keskin
authors.forename: Attila
authors.initials: A
authors.lastname: Gursoy
authors.forename: Ruth
authors.initials: R
authors.lastname: Nussinov
mesh_terms: D007249:Inflammation / Q000235:genetics / Q000378:metabolism*; D008958:Models, Molecular; D009154:Mutation; D053594:Myeloid Differentiation Factor 88 / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D009369:Neoplasms / Q000235:genetics / Q000378:metabolism*; D025941:Protein Interaction Mapping / Q000379:methods; D060066:Protein Interaction Maps; D017434:Protein Structure, Tertiary; D015398:Signal Transduction; D051193:Toll-Like Receptors / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*
chemical_list: C507779:MYD88 protein, human; D053594:Myeloid Differentiation Factor 88; D051193:Toll-Like Receptors
keywords: Cancer; DAMPs; ECM; EGF; HMGB1; IAP; IBD; IFN-α; IFN-β; IKK; IL-6; IRAK; IRFs; Inflammation; Inflammation and cancer link; IκB-kinase; LRR; MDSCs; Mal; MyD88; MyD88 adaptor-like; NF-κB; NSAIDs; PAMPs; PRISM; PRRs; PRotein Interactions by Structural Matching; PTEN; PTMs; RANK; ROS; SARM; Structural data; Structural pathway; T(reg)s; TAMs; TGF-β; TIR; TIR domain containing adaptor inducing interferon-β; TLR; TNF-α; TRAM; TRIF; TRIF-related adaptor molecule; Toll-like receptor; Toll/IL-1R; Ubc13; VEGF; VHL; damage-associated molecular patterns; epidermal growth factor; extracellular matrix; high mobility group box-1; inflammatory bowel disease; inhibitors of apoptosis; interferon alpha; interferon beta; interferon regulatory factors; interleukin-1 receptor-associated kinases; interleukin-6; leucine-rich repeats; myeloid differentiation factor 88; myeloid-derived suppressor cells; non-steroidal anti-inflammatory drugs; pathogen-associated molecular patterns; pattern recognition receptors; phosphatase and tensin homologue; post-translational modifications; reactive oxygen species; receptor activator of NF-κB; regulatory T cells; sterile α and heat-armadillo motifs; transforming growth factor-1 beta; tumor necrosis factor-alpha; tumor-associated macrophages; ubiquitin-conjugating enzyme E2N; vascular endothelial growth factor; von Hippel Lindau