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      Multisite Phosphorylation Provides an Effective and Flexible Mechanism for Switch-Like Protein Degradation

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          Abstract

          Phosphorylation-triggered degradation is a common strategy for elimination of regulatory proteins in many important cell signaling processes. Interesting examples include cyclin-dependent kinase inhibitors such as p27 in human and Sic1 in yeast, which play crucial roles during the G1/S transition in the cell cycle. In this work, we have modeled and analyzed the dynamics of multisite-phosphorylation-triggered protein degradation systematically. Inspired by experimental observations on the Sic1 protein and a previous intriguing theoretical conjecture, we develop a model to examine in detail the degradation dynamics of a protein featuring multiple phosphorylation sites and a threshold site number for elimination in response to a kinase signal. Our model explains the role of multiple phosphorylation sites, compared to a single site, in the regulation of protein degradation. A single-site protein cannot convert a graded input of kinase increase to much sharper output, whereas multisite phosphorylation is capable of generating a highly switch-like temporal profile of the substrate protein with two characteristics: a temporal threshold and rapid decrease beyond the threshold. We introduce a measure termed temporal response coefficient to quantify the extent to which a response in the time domain is switch-like and further investigate how this property is determined by various factors including the kinase input, the total number of sites, the threshold site number for elimination, the order of phosphorylation, the kinetic parameters, and site preference. Some interesting and experimentally verifiable predictions include that the non-degradable fraction of the substrate protein exhibits a more switch-like temporal profile; a sequential system is more switch-like, while a random system has the advantage of increased robustness; all the parameters, including the total number of sites, the threshold site number for elimination and the kinetic parameters synergistically determine the exact extent to which the degradation profile is switch-like. Our results suggest design principles for protein degradation switches which might be a widespread mechanism for precise regulation of cellular processes such as cell cycle progression.

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          Most cited references56

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          A methodology for performing global uncertainty and sensitivity analysis in systems biology.

          Accuracy of results from mathematical and computer models of biological systems is often complicated by the presence of uncertainties in experimental data that are used to estimate parameter values. Current mathematical modeling approaches typically use either single-parameter or local sensitivity analyses. However, these methods do not accurately assess uncertainty and sensitivity in the system as, by default, they hold all other parameters fixed at baseline values. Using techniques described within we demonstrate how a multi-dimensional parameter space can be studied globally so all uncertainties can be identified. Further, uncertainty and sensitivity analysis techniques can help to identify and ultimately control uncertainties. In this work we develop methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models. We compare two specific types of global sensitivity analysis indexes that have proven to be among the most robust and efficient. Through familiar and new examples of mathematical and computer models, we provide a complete methodology for performing these analyses, in both deterministic and stochastic settings, and propose novel techniques to handle problems encountered during these types of analyses.
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            F-box proteins are receptors that recruit phosphorylated substrates to the SCF ubiquitin-ligase complex.

            We have reconstituted the ubiquitination pathway for the Cdk inhibitor Sic1 using recombinant proteins. Skp1, Cdc53, and the F-box protein Cdc4 form a complex, SCFCdc4, which functions as a Sic1 ubiquitin-ligase (E3) in combination with the ubiquitin conjugating enzyme (E2) Cdc34 and E1. Cdc4 assembled with Skp1 functions as the receptor that selectively binds phosphorylated Sic1. Grr1, an F-box protein involved in Cln destruction, forms complexes with Skp1 and Cdc53 and binds phosphorylated Cln1 and Cln2, but not Sic1. Because the constituents of the SCF complex are members of protein families, SCFCdc4 is likely to serve as the prototype for a large class of E3s formed by combinatorial interactions of related family members. SCF complexes couple protein kinase signaling pathways to the control of protein abundance.
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              p27(Kip1) ubiquitination and degradation is regulated by the SCF(Skp2) complex through phosphorylated Thr187 in p27.

              Many tumorigenic processes affect cell-cycle progression by their effects on the levels of the cyclin-dependent kinase inhibitor p27(Kip1) [1,2]. The phosphorylation- and ubiquitination-dependent proteolysis of p27 is implicated in control of the G1-S transition in the cell cycle [3-6]. To determine the factors that control p27 stability, we established a cell-free extract assay that recapitulates the degradation of p27. Phosphorylation of p27 at Thr187 was essential for its degradation. Degradation was also dependent on SCF(Skp2), a protein complex implicated in targeting phosphorylated proteins for ubiquitination [7-10]. Immunodepletion of components of the complex - Cul-1, Skp1, or Skp2 - from the extract abolished p27 degradation, while addition of purified SCF(Skp2) to Skp2- depleted extract restored the capacity to degrade p27. A specific association was observed between Skp2 and a p27 carboxy-terminal peptide containing phosphorylated Thr187, but not between Skp2 and the non-phosphorylated peptide. Skp2-dependent associations between Skp1 or Cul-1 and the p27 phosphopeptide were also detected. Isolated SCF(Skp2) contained an E3 ubiquitin ligase activity towards p27. Our data thus suggest that SCF(Skp2) specifically targets p27 for degradation during cell-cycle progression.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2010
                13 December 2010
                : 5
                : 12
                : e14029
                Affiliations
                [1 ]Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
                [2 ]Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan, United States of America
                [3 ]Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
                [4 ]Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
                Fondazione Telethon, Italy
                Author notes

                Conceived and designed the experiments: SMVK XNL. Performed the experiments: SMVK. Analyzed the data: SMVK XNL. Contributed reagents/materials/analysis tools: ACV SDM. Wrote the paper: SMVK ACV XNL.

                Article
                10-PONE-RA-20329R1
                10.1371/journal.pone.0014029
                3001445
                21179196
                1c6eacf7-83ad-43ad-8587-c6e46f7ab762
                Varedi K. et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 17 June 2010
                : 20 October 2010
                Page count
                Pages: 18
                Categories
                Research Article
                Biophysics/Theory and Simulation
                Cell Biology/Cell Growth and Division
                Computational Biology/Signaling Networks
                Computational Biology/Systems Biology

                Uncategorized
                Uncategorized

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