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      Human Three-Finger Protein Lypd6 Is a Negative Modulator of the Cholinergic System in the Brain

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          Abstract

          Lypd6 is a GPI-tethered protein from the Ly-6/uPAR family expressed in the brain. Lypd6 enhances the Wnt/β-catenin signaling, although its action on nicotinic acetylcholine receptors (nAChRs) have been also proposed. To investigate a cholinergic activity of Lypd6, we studied a recombinant water-soluble variant of the human protein (ws-Lypd6) containing isolated “three-finger” LU-domain. Experiments at different nAChR subtypes expressed in Xenopus oocytes revealed the negative allosteric modulatory activity of ws-Lypd6. Ws-Lypd6 inhibited ACh-evoked currents at α3β4- and α7-nAChRs with IC 50 of ∼35 and 10 μM, respectively, and the maximal amplitude of inhibition of 30–50%. EC 50 of ACh at α3β4-nAChRs (∼30 μM) was not changed in the presence of 35 μM ws-Lypd6, while the maximal amplitude of ACh-evoked current was reduced by ∼20%. Ws-Lypd6 did not elicit currents through nAChRs in the absence of ACh. Application of 1 μM ws-Lypd6 significantly inhibited (up to ∼28%) choline-evoked current at α7-nAChRs in rat hippocampal slices. Similar to snake neurotoxin α-bungarotoxin, ws-Lypd6 suppressed the long-term potentiation (LTP) in mouse hippocampal slices. Colocalization of endogenous GPI-tethered Lypd6 with α3β4- and α7-nAChRs was detected in primary cortical and hippocampal neurons. Ws-Lypd6 interaction with the extracellular domain of α7-nAChR was modeled using the ensemble protein-protein docking protocol. The interaction of all three Lypd6 loops (“fingers”) with the entrance to the orthosteric ligand-binding site and the loop C of the primary receptor subunit was predicted. The results obtained allow us to consider Lypd6 as the endogenous negative modulator involved in the regulation of the cholinergic system in the brain.

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          GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

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            JPred4: a protein secondary structure prediction server

            JPred4 (http://www.compbio.dundee.ac.uk/jpred4) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction. In addition to protein secondary structure, JPred also makes predictions of solvent accessibility and coiled-coil regions. The JPred service runs up to 94 000 jobs per month and has carried out over 1.5 million predictions in total for users in 179 countries. The JPred4 web server has been re-implemented in the Bootstrap framework and JavaScript to improve its design, usability and accessibility from mobile devices. JPred4 features higher accuracy, with a blind three-state (α-helix, β-strand and coil) secondary structure prediction accuracy of 82.0% while solvent accessibility prediction accuracy has been raised to 90% for residues <5% accessible. Reporting of results is enhanced both on the website and through the optional email summaries and batch submission results. Predictions are now presented in SVG format with options to view full multiple sequence alignments with and without gaps and insertions. Finally, the help-pages have been updated and tool-tips added as well as step-by-step tutorials.
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              ZDOCK: an initial-stage protein-docking algorithm.

              The development of scoring functions is of great importance to protein docking. Here we present a new scoring function for the initial stage of unbound docking. It combines our recently developed pairwise shape complementarity with desolvation and electrostatics. We compare this scoring function with three other functions on a large benchmark of 49 nonredundant test cases and show its superior performance, especially for the antibody-antigen category of test cases. For 44 test cases (90% of the benchmark), we can retain at least one near-native structure within the top 2000 predictions at the 6 degrees rotational sampling density, with an average of 52 near-native structures per test case. The remaining five difficult test cases can be explained by a combination of poor binding affinity, large backbone conformational changes, and our algorithm's strong tendency for identifying large concave binding pockets. All four scoring functions have been integrated into our Fast Fourier Transform based docking algorithm ZDOCK, which is freely available to academic users at http://zlab.bu.edu/~ rong/dock. Copyright 2003 Wiley-Liss, Inc.
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                Author and article information

                Contributors
                Journal
                Front Cell Dev Biol
                Front Cell Dev Biol
                Front. Cell Dev. Biol.
                Frontiers in Cell and Developmental Biology
                Frontiers Media S.A.
                2296-634X
                21 September 2021
                2021
                : 9
                : 662227
                Affiliations
                [1] 1Bioengineering Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences (RAS) , Moscow, Russia
                [2] 2Structural Biology Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences (RAS) , Moscow, Russia
                [3] 3Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology , Moscow, Russia
                [4] 4Department of Molecular Neurobiology, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences (RAS) , Moscow, Russia
                [5] 5Brain Research Department, Research Center of Neurology , Moscow, Russia
                [6] 6Institute of Neuroscience, Nizhny Novgorod University , Nizhny Novgorod, Russia
                [7] 7Toxicology and Pharmacology, University of Leuven (KU Leuven) , Leuven, Belgium
                [8] 8International Laboratory for Supercomputer Atomistic Modelling and Multi-Scale Analysis, National Research University Higher School of Economics , Moscow, Russia
                [9] 9Biological Faculty, Lomonosov Moscow State University , Moscow, Russia
                Author notes

                Edited by: Anil K. Bamezai, Villanova University, United States

                Reviewed by: Irene Yan, University of São Paulo, Brazil; Maegan Weltzin, University of Alaska Fairbanks, United States

                *Correspondence: Ekaterina Lyukmanova, ekaterina-lyukmanova@ 123456yandex.ru

                These authors have contributed equally to this work

                This article was submitted to Signaling, a section of the journal Frontiers in Cell and Developmental Biology

                Article
                10.3389/fcell.2021.662227
                8494132
                34631692
                715961c9-b122-447d-957e-101a0cc094d1
                Copyright © 2021 Kulbatskii, Shenkarev, Bychkov, Loktyushov, Shulepko, Koshelev, Povarov, Popov, Peigneur, Chugunov, Kozlov, Sharonova, Efremov, Skrebitsky, Tytgat, Kirpichnikov and Lyukmanova.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 January 2021
                : 30 August 2021
                Page count
                Figures: 9, Tables: 0, Equations: 0, References: 65, Pages: 17, Words: 13979
                Funding
                Funded by: Russian Foundation for Basic Research, doi 10.13039/501100002261;
                Categories
                Cell and Developmental Biology
                Original Research

                lypd6,nachr,cognitive function,synaptic plasticity,ly6/upar,three-finger,lynx1,lypd6b

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