• 2018-07
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • Hymenialdisine the most potent inhibitor of parasite TgCK en


    Hymenialdisine, the most potent inhibitor of parasite TgCK1 enzymes in vitro has no whole cell anti-parasitic activity (Table 2). Like purvalanol B however, this Cy5 NHS ester (non-sulfonated) also displays poor activity against target enzymes in cultured cells. For example, in vitro IC50 values for inhibition of CDK5/cyclin and GSk3-β are in the 10–30nM range, but 50μM levels were required to detect the effects on CDK5/p35 and GSK-3 kinase inhibition in rat cortical neurons [39]. Validation of parasite CK1 as a therapeutic target remains an important but as yet unfulfilled goal. The activity of compounds described in this study suggest parasite CK1 as a potential chemotherapeutic target, but more medicinal chemistry is needed to establish a firmer correlation between anti-parasitic efficacy and CK1α activity within a collection of structurally related inhibitors such as the purvalanols. Future target validation efforts aimed at parasite CK1 will require the identification of new inhibitors with improved potency and safety properties. Genetic validation will also be necessary to show that the CK1α gene is essential. As demonstrated with the coccidian parasite PKG [9], this can be accomplished in T. gondii through gene knock-out experiments and by the construction of allelic variants of the protein kinase target that are refractory to selective compounds. Minimally, the inhibitor studies presented here provide evidence for the existence of structural differences in the CK1 enzymes of the parasite compared with orthologues in the vertebrate host. Using target-based screening approaches, it should be possible to identify selective CK1 inhibitors that lack host CDK-related anti-mitotic properties associated with host cell toxicity. With the availability of crystallographic data for CDK and CK enzymes [62], [63], [64], [65], [66], [67], the construction of similarity models based on available parasite sequence information should serve as additional tools for optimizing the selectivity of potential lead compounds.
    Protein kinase CK1 represents a unique and well-conserved group of protein kinases within the superfamily of serine/threonine kinases that is ubiquitously expressed in eukaryotic organisms. Recently, seven mammalian CK1 isoforms have been identified (α, β, γ1, γ2, γ3, δ, ε) with a molecular weight between 37 and 51kDa. Even if all CK1 isoforms are highly conserved within their kinase domains, they show important differences in length and primary structure of the N-terminal and C-terminal domains. CK1 isoforms are showed to be constitutive active with a consensus motif pS-X-X-S; this means that a prephosphorylation by other kinases (e.g., GSK3β) is required before they reach their basal activity. Despite its constitutive activation, several mechanisms of CK1 activity control are known, such as the inhibitory autophosphorylation, the proteolytic cleavage of the C-terminal domain, and its subcellular localization and compartimentalization. Members of CK1 family are involved in regulating a variety of cellular events including transduction of the Wnt signaling pathway, regulation of circadian rhythms,, the DNA damage response,, and late cell cycle progression., Consequently, the alteration of CK1 homeostasis has been possibly related to several diseases like neurodegenerative diseases, including Alzheimer’s and Parkinson’s disorders (CK1δ isoform), the familial advanced sleep phase syndrome (CK1δ and ε isoforms), hepatitis C (CK1α isoform), leishmaniasis, and cancer (CK1α, δ and ε isoforms). Very few potent and selective CK1 inhibitors have been described. Among these it is worthy to mention: the 4-[4-(2,3-dihydro-benzo[1,4]dioxin-6-yl)-5-pyridin-2-yl-1-imidazol-2-yl]benzamide (D4476), the 3-[(2,4,6-trimethoxyphenyl)methylidenyl]-indolin-2-one (IC261),, and the -(2-aminoethyl)-5-chloroisoquinoline-8-sulfonamide (CK1-7) with IC of 0.3, 1.0 and 6μM, respectively. In recent years, we have performed an intensive screening campaign combining in silico and in vitro enzymology approaches. In particular, we have focused our attention on the CK1δ isoform due to its key role in the possible pathogenesis of several neurodegenerative diseases and cancer. Following some recent successful examples of new kinase inhibitors identification through structure-based virtual screening (SBVS) approches,, we have performed an in silico study targeting the ATP-binding site of CK1 by browsing our in-house molecular database (defined as MMsINC) which contains around 4 millions of synthetic and natural compounds. Generally speaking, SBVC approach could represent a useful strategy to prioritize the synthesis and the biological screening of novel drug candidates. In our virtual screening protocol, we have used a combination of different docking protocols with a consensus scoring strategy, as summarized in . In particular, due to the fact that no crystal structure is available for the human CK1δ, an homology modeling approach has been carried out to obtain a suitable three-dimensional model of the CK1δ catalytic subunit. The choice of combining different docking protocols has been dictated by the awareness that scoring is typically more important than docking in database screening, and that scoring functions performances often depend on the target active site features. However, since docking poses may significantly affect the scoring, multiple scoring functions are simultaneously used in the hit selection process, and improvements can be achieved by compensating for the deficiencies of each function. Specifically, a combination of four docking protocols (MOE-Dock, Glide, Gold and FlexX) and five scoring functions (MOE-Score, GlideScore, Gold-Score, ChemScore and Xscore) has been used to appropriately dock and score all MMsINC entries with a leadlikeness profile. In particular, we have implemented a ‘ consensus scoring function’ to appropriately rank the possible hit compounds. This function represents the number of scoring functions for which a certain candidate docking pose is scored among the top % of the database (see for details).