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      Structural basis and energy landscape for the Ca 2+ gating and calmodulation of the Kv7.2 K + channel

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          Significance

          Ion channels are sophisticated proteins that exert control over a plethora of body functions. Specifically, the members of the Kv7 family are prominent components of the nervous systems, responsible for the ion fluxes that regulate the electrical signaling in neurons and cardiac myocytes. Albeit its relevance, there are still several questions, including the Ca 2+/calmodulin (CaM)-mediated gating mechanism. We found that Ca 2+ binding to CaM triggers a segmental rotation that allosterically transmits the signal from the cytosol up to the transmembrane region. NMR-derived analysis of the dynamics demonstrates that it occurs through a conformational selection mechanism. Energetically, CaM association with the channel tunes the affinities of the CaM lobes (calmodulation) so that the channel can sense the specific changes in [Ca 2+] resulting after an action potential.

          Abstract

          The Kv7.2 (KCNQ2) channel is the principal molecular component of the slow voltage-gated, noninactivating K + M-current, a key controller of neuronal excitability. To investigate the calmodulin (CaM)-mediated Ca 2+ gating of the channel, we used NMR spectroscopy to structurally and dynamically describe the association of helices hA and hB of Kv7.2 with CaM, as a function of Ca 2+ concentration. The structures of the CaM/Kv7.2-hAB complex at two different calcification states are reported here. In the presence of a basal cytosolic Ca 2+ concentration (10–100 nM), only the N-lobe of CaM is Ca 2+-loaded and the complex (representative of the open channel) exhibits collective dynamics on the millisecond time scale toward a low-populated excited state (1.5%) that corresponds to the inactive state of the channel. In response to a chemical or electrical signal, intracellular Ca 2+ levels rise up to 1–10 μM, triggering Ca 2+ association with the C-lobe. The associated conformational rearrangement is the key biological signal that shifts populations to the closed/inactive channel. This reorientation affects the C-lobe of CaM and both helices in Kv7.2, allosterically transducing the information from the Ca 2+-binding site to the transmembrane region of the channel.

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          Most cited references 28

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          Intrinsic dynamics of an enzyme underlies catalysis.

          A unique feature of chemical catalysis mediated by enzymes is that the catalytically reactive atoms are embedded within a folded protein. Although current understanding of enzyme function has been focused on the chemical reactions and static three-dimensional structures, the dynamic nature of proteins has been proposed to have a function in catalysis. The concept of conformational substates has been described; however, the challenge is to unravel the intimate linkage between protein flexibility and enzymatic function. Here we show that the intrinsic plasticity of the protein is a key characteristic of catalysis. The dynamics of the prolyl cis-trans isomerase cyclophilin A (CypA) in its substrate-free state and during catalysis were characterized with NMR relaxation experiments. The characteristic enzyme motions detected during catalysis are already present in the free enzyme with frequencies corresponding to the catalytic turnover rates. This correlation suggests that the protein motions necessary for catalysis are an intrinsic property of the enzyme and may even limit the overall turnover rate. Motion is localized not only to the active site but also to a wider dynamic network. Whereas coupled networks in proteins have been proposed previously, we experimentally measured the collective nature of motions with the use of mutant forms of CypA. We propose that the pre-existence of collective dynamics in enzymes before catalysis is a common feature of biocatalysts and that proteins have evolved under synergistic pressure between structure and dynamics.
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            ARIA2: automated NOE assignment and data integration in NMR structure calculation.

            Modern structural genomics projects demand for integrated methods for the interpretation and storage of nuclear magnetic resonance (NMR) data. Here we present version 2.1 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and NMR structure calculation. We report on recent developments, most notably a graphical user interface, and the incorporation of the object-oriented data model of the Collaborative Computing Project for NMR (CCPN). The CCPN data model defines a storage model for NMR data, which greatly facilitates the transfer of data between different NMR software packages. A distribution with the source code of ARIA 2.1 is freely available at http://www.pasteur.fr/recherche/unites/Binfs/aria2.
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              Small-conductance Ca2+-activated K+ channels: form and function.

              Small-conductance Ca(2+)-activated K(+) channels (SK channels) are widely expressed throughout the central nervous system. These channels are activated solely by increases in intracellular Ca(2+). SK channels are stable macromolecular complexes of the ion pore-forming subunits with calmodulin, which serves as the intrinsic Ca(2+) gating subunit, as well as with protein kinase CK2 and protein phosphatase 2A, which modulate Ca(2+) sensitivity. Well-known for their roles in regulating somatic excitability in central neurons, SK channels are also expressed in the postsynaptic membrane of glutamatergic synapses, where their activation and regulated trafficking modulate synaptic transmission and the induction and expression of synaptic plasticity, thereby affecting learning and memory. In this review we discuss the molecular and functional properties of SK channels and their physiological roles in central neurons.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                6 March 2018
                20 February 2018
                20 February 2018
                : 115
                : 10
                : 2395-2400
                Affiliations
                aProtein Stability and Inherited Disease Laboratory, Center for Cooperative Research in Biosciences CIC bioGUNE , 48170 Derio, Spain;
                bInstituto Biofisika (Consejo Superior de Investigaciones Científicas, Universidad del País Vasco), University of Basque Country , 48940 Leioa, Spain
                Author notes
                1To whom correspondence may be addressed. Email: alvaro.villarroel@ 123456csic.es or omillet@ 123456cicbiogune.es .

                Edited by Richard W. Aldrich, The University of Texas at Austin, Austin, TX, and approved January 24, 2018 (received for review January 10, 2018)

                Author contributions: Á.V. and O.M. designed research; G.B.-S., E.N., and C.G. performed research; C.M. contributed new reagents/analytic tools; G.B.-S. analyzed data; and Á.V. and O.M. wrote the paper.

                Article
                201800235
                10.1073/pnas.1800235115
                5873240
                29463698
                Copyright © 2018 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                Page count
                Pages: 6
                Product
                Funding
                Funded by: Ministerio de Economía y Competitividad (MINECO) 501100003329
                Award ID: CTQ2015-68756-R
                Funded by: Ministerio de Economía y Competitividad (MINECO) 501100003329
                Award ID: BFU2015-66910-R
                Funded by: MINECO | Secretaría de Estado de Investigación, Desarrollo e Innovación (SEIDI) 501100007136
                Award ID: CSD2008-00005
                Categories
                Biological Sciences
                Biophysics and Computational Biology

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