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. 2014 Feb 13;10(2):e1003470.
doi: 10.1371/journal.pcbi.1003470. eCollection 2014 Feb.

The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer

Affiliations

The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer

Saliha Ece Acuner Ozbabacan et al. PLoS Comput Biol. .

Abstract

Interleukin-1 (IL-1) is a large cytokine family closely related to innate immunity and inflammation. IL-1 proteins are key players in signaling pathways such as apoptosis, TLR, MAPK, NLR and NF-κB. The IL-1 pathway is also associated with cancer, and chronic inflammation increases the risk of tumor development via oncogenic mutations. Here we illustrate that the structures of interfaces between proteins in this pathway bearing the mutations may reveal how. Proteins are frequently regulated via their interactions, which can turn them ON or OFF. We show that oncogenic mutations are significantly at or adjoining interface regions, and can abolish (or enhance) the protein-protein interaction, making the protein constitutively active (or inactive, if it is a repressor). We combine known structures of protein-protein complexes and those that we have predicted for the IL-1 pathway, and integrate them with literature information. In the reconstructed pathway there are 104 interactions between proteins whose three dimensional structures are experimentally identified; only 15 have experimentally-determined structures of the interacting complexes. By predicting the protein-protein complexes throughout the pathway via the PRISM algorithm, the structural coverage increases from 15% to 71%. In silico mutagenesis and comparison of the predicted binding energies reveal the mechanisms of how oncogenic and single nucleotide polymorphism (SNP) mutations can abrogate the interactions or increase the binding affinity of the mutant to the native partner. Computational mapping of mutations on the interface of the predicted complexes may constitute a powerful strategy to explain the mechanisms of activation/inhibition. It can also help explain how an oncogenic mutation or SNP works.

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Conflict of interest statement

I have read the journal's policy and have the following conflicts: Our co-author Ruth Nussinov serves as the editor-in-chief for this journal. Additionally, our corresponding author Ozlem Keskin serves as a Guest Associate Editor for this journal. This does not alter our adherence to all the PLOS Comp Biol policies on sharing data and materials. All other authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. IL-1 signaling pathway diagram.
In this simplified diagram of the IL-1 signaling pathway, the signal initiates by the recognition of cytokines by IL-1 receptors and propagates via multiple sub-pathways involving family homologs or alternate pathways to activate transcription factors downstream.
Figure 2
Figure 2. IL-1 signaling pathway reconstructed by combining related pathways and information from the literature.
This detailed map of IL-1 signaling presents the protein-protein interactions and the resulting cellular events. The colored nodes represent proteins having experimentally identified 3D structures and the white nodes are the proteins without 3D structures. The edges represent protein-protein interactions (straight/dashed arrows relate to available/unavailable 3D structures of proteins) or associations leading to cellular events such as cell cycle or gene expression (dashed arrows beginning with circular heads).
Figure 3
Figure 3. Structures of protein-protein complexes mapped to the IL-1 signaling pathway.
A. Overall distribution of experimental and predicted complexes on the pathway. Dark blue interactions represent the experimentally determined complex structures in the PDB, red interactions represent the predicted complexes with predicted binding energies lower than −10 energy units and yellow interactions represent the interactions for which neither experimental nor computational data exists. B. Predicted structures (Template PDB code+Target PDB codes+Energy value): IL1α-IL1R1 (1itbAB 2l5x 4depB −71.92); IL1α-IL1RAP (1itbAB 2l5x 4depC −49.25); IL1R1-MYD88 (1gylAB IL1R1 (model) 2z5v −23.8); IL1R1-TOLLIP (1oh0AB IL1R1 (model) 1wgl −18.85); IL1RAP-MYD88 (1p65AB IL1RAP (model) 2z5v −31.72); MYD88-TOLLIP (1yrlAC 3mopA 1wgl −11.04); MYD88-TRAF6 (1vjlAB 2js7 1lb6 −37.01); TRAF6-IRF7 (1g8tAB 2o61 3hct −25.83). The blue color represents the proteins that precede its partners in the information flow.
Figure 4
Figure 4. SNPs/mutations mapped on the predicted complexes of MKK4 with JNK2 and JNK3.
A. MKK4 (mitogen-activated kinase kinase 4) - JNK2 (c-Jun N-terminal kinase 2) complex: Ser251 (p.Ser251Asn mutation - metastatic melanoma) on MKK4 and Gly268 (p.Gly268Ala SNP) on JNK2 are on the interface B. MKK4-JNK3 complex: Gln142 residue (p.Gln142Leu mutation - lung carcinoma) is a nearby residue of the interface and Arg154 residue (p.Arg154Trp mutation - colorectal adenocarcinoma) is on the interface as a computational hot spot residue. Orange and blue balls: interface residue atoms on MKK and JNK, respectively; yellow and cyan balls: hot spot residue atoms on MKK and JNK, respectively; red and purple balls: interface* and nearby residue atoms related to SNP and mutations on MKK and JNK, respectively.
Figure 5
Figure 5. The effects of p.Arg154Trp and p.Gln142Leu mutations on the predicted structure of the MKK4-JNK3 complex.
A. The predicted structure of the wild-type MKK4-JNK3 complex with predicted binding energy of −12.66 energy units. B. The predicted structure of the mutant MKK4-JNK3 complex (Arg154Trp) with predicted binding energy of −12.84 energy units aligned with the wild-type complex. C. The predicted structure of the mutant MKK4-JNK3 complex (Gln142Leu) with predicted binding energy of −41.14 energy units aligned with the wild-type complex. Yellow/purple/green and pink balls: residue atoms on MKK4 and JNK3, respectively; red balls: mutated residue atoms.
Figure 6
Figure 6. SNPs/mutations mapped on the predicted complex of IL-1α with IL1R1.
IL1A (Interleukin 1 alpha) – IL1R1 (Interleukin 1 type I receptor) complex: Ile 68 (p.Ile68Asn SNP) is on the interface as a computational hot spot residue* and Ile276 (p.Ile276Thr mutation - endometrioid carcinoma) is a nearby residue for the interface. Orange and blue balls: residue atoms related to the SNP and the mutation on IL1A and IL1R1, respectively.
Figure 7
Figure 7. The PRISM algorithm flow.
Two sets are given as the input: template and target. Four consecutive steps are executed to produce the output set which is composed of the structures of protein-protein complexes predicted to have the lowest binding energies. In this figure, the template set contains only one member for visualization simplicity, but it is important to note that the default template set of the algorithm is composed of 7922 interface members.

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