An Optimized Activity-Based Probe for the Study of Caspase-6 Activation

Cancer Biology Program, Stanford School of Medicine, 300 Pasteur Drive, Stanford, CA 94305-5324, USA.
Chemistry & biology (Impact Factor: 6.65). 03/2012; 19(3):340-52. DOI: 10.1016/j.chembiol.2011.12.021
Source: PubMed


Although significant efforts have been made to understand the mechanisms of caspase activation during apoptosis, many questions remain regarding how and when executioner caspases get activated. We describe the design and synthesis of an activity-based probe that labels caspase-3/-6/-7, allowing direct monitoring of all executioner caspases simultaneously. This probe has enhanced in vivo properties and reduced cross-reactivity compared to our previously reported probe, AB50. Using this probe, we find that caspase-6 undergoes a conformational change and can bind substrates even in the absence of cleavage of the proenzyme. We also demonstrate that caspase-6 activation does not require active caspase-3/-7, suggesting that it may autoactivate or be cleaved by other proteases. Together, our results suggest that caspase-6 activation proceeds through a unique mechanism that may be important for its diverse biological functions.

Download full-text


Available from: Laura E Edgington-Mitchell, Oct 01, 2015
30 Reads
  • Source
    • "Once dimerized, the caspase is able to cleave target substrates (Boatright et al. 2003). Executioner caspases (e.g., caspase-3, -6, -7) exist as inactive dimers that are activated upon proteolytic cleavage of both monomers at loops containing specific cleavage sites (Berger et al. 2006a; Denault et al. 2006; Edgington et al. 2012). Cleavage of these loops results in structural changes that serve to form the active sites, allowing the executioner caspases to cleave downstream substrates (Chai et al. 2001; Riedl et al. 2001). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Caspases are proteases that initiate and execute apoptotic cell death. These caspase-dependent events are caused by cleavage of specific substrates that propagate the proapoptotic signal. A number of techniques have been developed to follow caspase activity in vitro and from apoptotic cellular extracts. Many of these techniques use molecules that are based on optimal peptide motifs for each caspase and on our understanding of caspase cleavage events that occur during apoptosis. Although these approaches are useful, there are several drawbacks associated with them. The optimal peptide motifs are not unique recognition sites for each caspase, so techniques that use them may yield information about more than one caspase. Furthermore, caspase cleavage does not take into account the different caspase activation mechanisms. Recently, probes having greater specificity for individual caspases have been developed and are being used successfully. This introduction provides background on the various caspases and introduces a set of complementary techniques to examine the activity, substrate specificity, and activation status of caspases from in vitro or cell culture experiments.
    Cold Spring Harbor Protocols 08/2014; 2014(8):pdb.top070359. DOI:10.1101/pdb.top070359 · 4.63 Impact Factor
  • Source
    • "Effector caspases are activated by initiator caspases (e.g., caspase-2, 8, and 9), and then induce apoptotic cell death. Although the initiator and effector caspase cascade is well known, interactions among effector caspases are disputed [26]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Elucidation of protein-protein interaction (PPI) networks is important for understanding disease mechanisms and for drug discovery. Tertiary-structure-based in silico PPI prediction methods have been developed with two typical approaches: a method based on template matching with known protein structures and a method based on de novo protein docking. However, the template-based method has a narrow applicable range because of its use of template information, and the de novo docking based method does not have good prediction performance. In addition, both of these in silico prediction methods have insufficient precision, and require validation of the predicted PPIs by biological experiments, leading to considerable expenditure; therefore, PPI prediction methods with greater precision are needed. We have proposed a new structure-based PPI prediction method by combining template-based prediction and de novo docking prediction. When we applied the method to the human apoptosis signaling pathway, we obtained a precision value of 0.333, which is higher than that achieved using conventional methods (0.231 for PRISM, a template-based method, and 0.145 for MEGADOCK, a non-template-based method), while maintaining an F-measure value (0.285) comparable to that obtained using conventional methods (0.296 for PRISM, and 0.220 for MEGADOCK). Our consensus method successfully predicted a PPI network with greater precision than conventional template/non-template methods, which may thus reduce the cost of validation by laboratory experiments for confirming novel PPIs from predicted PPIs. Therefore, our method may serve as an aid for promoting interactome analysis.
    BMC proceedings 12/2013; 7(Suppl 7):S6. DOI:10.1186/1753-6561-7-S7-S6
  • Source
Show more