Archives

  • 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
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-06
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • One extraordinary parameter that emerged

    2020-07-28

    One extraordinary parameter that emerged from the modeling is that in the absence of bound substrate, CUL1 undergoes an entire exchange cycle in less than 1 min. Even more astonishingly, if all FPBs have equal access to CUL1, the entire pool of FPBs would sample CUL1 in less than 4 min in 293T medetomidine sale (Liu et al., 2018). Such rapid and indiscriminate cycling could safeguard the SCF system from bias against FBPs that are expressed at low levels or that display weak affinity for CUL1. In a grander sense, the implications of these numbers are profound and suggest that CUL1-RBX1 and, by inference, other cullin-RING complexes are on an endless search-and-rescue mission continuously on the hunt for substrate-bound FBPs, ensuring active SCF assembly only upon increased substrate demand. In order to gauge the model’s predictive strength, Liu et al. (2018) simulated effects of varying the concentrations of SCF components and predicted that overexpression of CUL1, but not the FBP that targets phosphorylated IκBα, would rescue defects in the rate of its degradation in DKO cells. Experimental validation of these predictions presented a new paradox: if CUL1 upregulation can obviate the need for CAND exchange, why does such a complex system exist in the first place? A potential answer came from calculating a matrix of response coefficients, which suggested that increasing the total FBP concentration would delay substrate degradation specifically in DKO cells. Indeed, gross overexpression of an FBP in DKO cells that lack dynamic CAND-mediated exchange clogs the system: this restricts CUL1 from accessing other FBPs, thereby stabilizing their ubiquitylation substrates (Liu et al., 2018). The authors conclude that CAND-driven exchange permits the SCF system to tolerate changes in FBP expression associated with development, without requiring CUL1 levels to change in diverse regulatory settings. Nonetheless, some SCF substrates (p27, CyclinE) are stabilized in DKO cells only when total FBP levels are increased by overexpression, implying that these substrates can be efficiently degraded independently of CAND exchange. Why some SCF substrates do not require CAND-dependent FBP exchange is unclear, but could reflect variations in the levels of their cognate FBPs, or differences in dissociation rates of these substrates versus phosphorylated IκBα. Whatever the case, it will be interesting to see whether this model can predict threshold conditions for substrates that require CAND-dependent exchange. Moving forward, the new mathematical model opens doors for understanding the SCF network, where activity of a component is blunted through mutation or altered in expression in diseased states, and during therapeutic intervention. Computational modeling could reveal underappreciated secondary or tertiary effects of network perturbation and how these might contribute to disease. It will also be interesting to see how CAND-driven exchange functions, and to what extent it is required, in organisms like C. elegans and D. melanogaster that express multiple Skp1-related genes with divergent sequences in CUL1-binding loops that prevent simultaneous binding to CAND1. With the availability of an accurate mathematical model, these and other mysteries of SCF and CRL networks CAN(D) now be solved.