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Browsing by Issue Date, starting with "2013-07-26"

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  • Structural basis for Z-DNA binding and stabilization by the zebrafish Z-DNA dependent protein kinase PKZ
    Publication . de Rosa, M.; Zacarias, S.; Athanasiadis, A.
    The RNA-dependent protein kinase PKR plays a central role in the antiviral defense of vertebrates by shutting down protein translation upon detection of viral dsRNA in the cytoplasm. In some teleost fish, PKZ, a homolog of PKR, performs the same function, but surprisingly, instead of dsRNA binding domains, it harbors two Z-DNA/Z-RNA-binding domains belonging to the Zalpha domain family. Zalpha domains have also been found in other proteins, which have key roles in the regulation of interferon responses such as ADAR1 and DNA-dependent activator of IFN-regulatory factors (DAI) and in viral proteins involved in immune response evasion such as the poxviral E3L and the Cyprinid Herpesvirus 3 ORF112. The underlying mechanism of nucleic acids binding and stabilization by Zalpha domains is still unclear. Here, we present two crystal structures of the zebrafish PKZ Zalpha domain (DrZalpha(PKZ)) in alternatively organized complexes with a (CG)6 DNA oligonucleotide at 2 and 1.8 Å resolution. These structures reveal novel aspects of the Zalpha interaction with DNA, and they give insights on the arrangement of multiple Zalpha domains on DNA helices longer than the minimal binding site.
    2013-07-26Journal article Open access Show more
  • Majority rules with random tie-breaking in Boolean gene regulatory networks
    Publication . Chaouiya, Claudine; Ourrad, Ouerdia; Lima, Ricardo
    We consider threshold boolean gene regulatory networks, where the update function of each gene is described as a majority rule evaluated among the regulators of that gene: it is turned ON when the sum of its regulator contributions is positive (activators contribute positively whereas repressors contribute negatively) and turned OFF when this sum is negative. In case of a tie (when contributions cancel each other out), it is often assumed that the gene keeps it current state. This framework has been successfully used to model cell cycle control in yeast. Moreover, several studies consider stochastic extensions to assess the robustness of such a model. Here, we introduce a novel, natural stochastic extension of the majority rule. It consists in randomly choosing the next value of a gene only in case of a tie. Hence, the resulting model includes deterministic and probabilistic updates. We present variants of the majority rule, including alternate treatments of the tie situation. Impact of these variants on the corresponding dynamical behaviours is discussed. After a thorough study of a class of two-node networks, we illustrate the interest of our stochastic extension using a published cell cycle model. In particular, we demonstrate that steady state analysis can be rigorously performed and can lead to effective predictions; these relate for example to the identification of interactions whose addition would ensure that a specific state is absorbing.
    2013-07-26Journal article Open access Show more