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      A structural dynamics model for how CPEB3 binding to SUMO2 can regulate translational control in dendritic spines

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          Abstract

          A prion-like RNA-binding protein, CPEB3, can regulate local translation in dendritic spines. CPEB3 monomers repress translation, whereas CPEB3 aggregates activate translation of its target mRNAs. However, the CPEB3 aggregates, as long-lasting prions, may raise the problem of unregulated translational activation. Here, we propose a computational model of the complex structure between CPEB3 RNA-binding domain (CPEB3-RBD) and small ubiquitin-like modifier protein 2 (SUMO2). Free energy calculations suggest that the allosteric effect of CPEB3-RBD/SUMO2 interaction can amplify the RNA-binding affinity of CPEB3. Combining with previous experimental observations on the SUMOylation mode of CPEB3, this model suggests an equilibrium shift of mRNA from binding to deSUMOylated CPEB3 aggregates to binding to SUMOylated CPEB3 monomers in basal synapses. This work shows how a burst of local translation in synapses can be silenced following a stimulation pulse, and explores the CPEB3/SUMO2 interplay underlying the structural change of synapses and the formation of long-term memories.

          Author summary

          Local translation of specific synaptic proteins provides the molecular basis for the structural change in dendritic spines, which is essential for long-term memories. A functional prion-like RNA-binding protein, CPEB3, has been proposed as a synaptic tag to regulate local translation in dendritic spines. More interestingly, the soluble CPEB3 monomers repress translation, whereas the CPEB3 aggregates activate the translation of its target mRNAs. The CPEB3 aggregates, however, that act as long-lasting prions providing “conformational memory”, may raise the problem of translational activation being unregulated. Here, we propose a computational model of the complex structure between CPEB3 RNA-binding domain (CPEB3-RBD) and small ubiquitin-like modifier protein 2 (SUMO2). Free energy calculations suggest that the allosteric binding of CPEB3 with SUMO2 can confine the CPEB3-RBD to a conformation that favors RNA-binding, and thereby can amplify its RNA-binding affinity. Combining this model with previous experiments showing that CPEB3 monomers are SUMOylated in basal synapses but become deSUMOylated and start to aggregate upon stimulation, we suggest a way in which the translational control of CPEB3 can be switched back to a repressive mode after a stimulation pulse, through an RNA binding shift from binding to CPEB3 fibers to binding to SUMOylated CPEB3 monomers in basal synapses.

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          Most cited references31

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          Modeller: generation and refinement of homology-based protein structure models.

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            Actin-based plasticity in dendritic spines.

            I A Matus (2000)
            The central nervous system functions primarily to convert patterns of activity in sensory receptors into patterns of muscle activity that constitute appropriate behavior. At the anatomical level this requires two complementary processes: a set of genetically encoded rules for building the basic network of connections, and a mechanism for subsequently fine tuning these connections on the basis of experience. Identifying the locus and mechanism of these structural changes has long been among neurobiology's major objectives. Evidence has accumulated implicating a particular class of contacts, excitatory synapses made onto dendritic spines, as the sites where connective plasticity occurs. New developments in light microscopy allow changes in spine morphology to be directly visualized in living neurons and suggest that a common mechanism, based on dynamic actin filaments, is involved in both the formation of dendritic spines during development and their structural plasticity at mature synapses.
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              Theory of protein folding: the energy landscape perspective.

              The energy landscape theory of protein folding is a statistical description of a protein's potential surface. It assumes that folding occurs through organizing an ensemble of structures rather than through only a few uniquely defined structural intermediates. It suggests that the most realistic model of a protein is a minimally frustrated heteropolymer with a rugged funnel-like landscape biased toward the native structure. This statistical description has been developed using tools from the statistical mechanics of disordered systems, polymers, and phase transitions of finite systems. We review here its analytical background and contrast the phenomena in homopolymers, random heteropolymers, and protein-like heteropolymers that are kinetically and thermodynamically capable of folding. The connection between these statistical concepts and the results of minimalist models used in computer simulations is discussed. The review concludes with a brief discussion of how the theory helps in the interpretation of results from fast folding experiments and in the practical task of protein structure prediction.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput Biol
                plos
                PLOS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                November 2022
                8 November 2022
                : 18
                : 11
                : e1010657
                Affiliations
                [1 ] Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America
                [2 ] Department of Chemistry, Rice University, Houston, Texas, United States of America
                University of Missouri, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-7975-9287
                Article
                PCOMPBIOL-D-22-01067
                10.1371/journal.pcbi.1010657
                9674179
                36346822
                e363aff9-1a03-4256-bc93-d46da7a55b0b
                © 2022 Gu 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
                : 12 July 2022
                : 14 October 2022
                Page count
                Figures: 8, Tables: 0, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: CHE-1743392
                Award Recipient :
                Funded by: National Science Foundation
                Award ID: PHY-2019745
                Award Recipient :
                Funded by: The D.R. Bullard Welch Chair at Rice University
                Award ID: C-0016
                Award Recipient :
                XG, NPS, CB, WL, and PGW were supported by the NSF Division of Chemistry RAISE grant CHE-1743392 and by the Center for Theoretical Biological Physics, sponsored by the NSF Division of Physics grant PHY-2019745. CB was also supported by the PoLS Student Research Network sponsored by the NSF Division of Physics grant 1522550. PGW was supported by the D. R. Bullard-Welch Chair at Rice University, Grant C-0016. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and life sciences
                Molecular biology
                Macromolecular structure analysis
                RNA structure
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                RNA structure
                Physical Sciences
                Physics
                Thermodynamics
                Free Energy
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Messenger RNA
                Biology and Life Sciences
                Genetics
                Gene Expression
                Protein Translation
                Biology and Life Sciences
                Anatomy
                Nervous System
                Synapses
                Medicine and Health Sciences
                Anatomy
                Nervous System
                Synapses
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Synapses
                Biology and Life Sciences
                Neuroscience
                Neurophysiology
                Synapses
                Biology and life sciences
                Biochemistry
                Proteins
                Post-translational modification
                SUMOylation
                Biology and Life Sciences
                Molecular Biology
                Macromolecular Structure Analysis
                Protein Structure
                Protein Structure Prediction
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Structure
                Protein Structure Prediction
                Biology and Life Sciences
                Molecular Biology
                Macromolecular Structure Analysis
                Protein Structure
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Structure
                Custom metadata
                vor-update-to-uncorrected-proof
                2022-11-18
                Original data and codes are available at https://doi.org/10.5281/zenodo.5677353.

                Quantitative & Systems biology
                Quantitative & Systems biology

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