A two-component protease in Methylorubrum extorquens with high activity toward the peptide precursor of the redox cofactor pyrroloquinoline quinone

Pyrroloquinoline quinone is a prominent redox cofactor in many prokaryotes, produced from a ribosomally synthesized and post-translationally modified peptide PqqA via a pathway comprising four conserved proteins PqqB?E. These four proteins are now fairly well-characterized and span radical SAM activity (PqqE), aided by a peptide chaperone (PqqD), a dual hydroxylase (PqqB), and an eight-electron, eight-proton oxidase (PqqC). A full description of this pathway has been hampered by a lack of information regarding a protease/peptidase required for the excision of an early, cross-linked di-amino acid precursor to pyrroloquinoline quinone. Herein, we isolated and characterized a two-component heterodimer protein from the ?-proteobacterium Methylobacterium (Methylorubrum) extorquens that can rapidly catalyze cleavage of PqqA into smaller peptides. Using pulldown assays, surface plasmon resonance, and isothermal calorimetry, we demonstrated the formation of a complex PqqF/PqqG, with a K-D of 300 nm. We created a molecular model of the heterodimer by comparison with the Sphingomonas sp. A1 M16B Sph2681/Sph2682 protease. Analysis of time-dependent patterns for the appearance of proteolysis products indicates high specificity of PqqF/PqqG for serine side chains. We hypothesize that PqqF/PqqG initially cleaves between the PqqE/PqqD-generated cross-linked form of PqqA, with nonspecific cellular proteases completing the release of a suitable substrate for the downstream enzyme PqqB. The finding of a protease that specifically targets serine side chains is rare, and we propose that this activity may be useful in proteomic analyses of the large family of proteins that have undergone post-translational phosphorylation at serine.National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [GM118117, GM124002, 1S10OD020062-01

Structural Pathways of Cytokines May Illuminate Their Roles in Regulation of Cancer Development and Immunotherapy

Cytokines are messengers between tissues and the immune system. They play essential roles in cancer initiation, promotion, metastasis, and immunotherapy. Structural pathways of cytokine signaling which contain their interactions can help understand their action in the tumor microenvironment. Here, our aim is to provide an overview of the role of cytokines in tumor development from a structural perspective. Atomic details of protein-protein interactions can help in understanding how an upstream signal is transduced; how higher-order oligomerization modes of proteins can influence their function; how mutations, inhibitors or antagonists can change cellular consequences; why the same protein can lead to distinct outcomes, and which alternative parallel pathways can take over. They also help to design drugs/inhibitors against proteins de novo or by mimicking natural antagonists as in the case of interferon-γ. Since the structural database (PDB) is limited, structural pathways are largely built from a series of predicted binary protein-protein interactions. Below, to illustrate how protein-protein interactions can help illuminate roles played by cytokines, we model some cytokine interaction complexes exploiting a powerful algorithm (PRotein Interactions by Structural Matching—PRISM)

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

<div><p>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%. <i>In silico</i> 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.</p></div

t-test for COSMIC mutations mapped onto the interface region including the nearby residues.

<p>t-test for COSMIC mutations mapped onto the interface region including the nearby residues.</p

The PRISM algorithm flow.

<p>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.</p

The distribution of oncogenic mutations and SNPs on structures of interacting protein-protein complexes in IL-1 pathway.

<p>The distribution of oncogenic mutations and SNPs on structures of interacting protein-protein complexes in IL-1 pathway.</p

Structures of protein-protein complexes mapped to the IL-1 signaling pathway.

<p><b>A.</b> 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>B.</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 (1g8<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003470#pcbi-1003470-t002" target="_blank">tAB 2o</a>61 3hct −25.83). The blue color represents the proteins that precede its partners in the information flow.</p