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The Structural Pathway of Interleukin 1 (IL-1) Initiated Signaling Reveals Mechanisms of Oncogenic Mutations and SNPs in Inflammation and Cancer

Overview of attention for article published in PLoS Computational Biology, February 2014
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Title
The Structural Pathway of Interleukin 1 (IL-1) Initiated Signaling Reveals Mechanisms of Oncogenic Mutations and SNPs in Inflammation and Cancer
Published in
PLoS Computational Biology, February 2014
DOI 10.1371/journal.pcbi.1003470
Pubmed ID
Authors

Saliha Ece Acuner Ozbabacan, Attila Gursoy, Ruth Nussinov, Ozlem Keskin

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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Geographical breakdown

Country Count As %
Japan 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 155 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 19%
Student > Master 28 18%
Student > Bachelor 26 16%
Researcher 14 9%
Student > Doctoral Student 9 6%
Other 16 10%
Unknown 35 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 23%
Biochemistry, Genetics and Molecular Biology 32 20%
Medicine and Dentistry 16 10%
Immunology and Microbiology 8 5%
Neuroscience 6 4%
Other 22 14%
Unknown 38 24%