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      Pharmacological characterisation of the highly Na V1.7 selective spider venom peptide Pn3a

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          Abstract

          Human genetic studies have implicated the voltage-gated sodium channel Na V1.7 as a therapeutic target for the treatment of pain. A novel peptide, μ-theraphotoxin-Pn3a, isolated from venom of the tarantula Pamphobeteus nigricolor, potently inhibits Na V1.7 (IC 50 0.9 nM) with at least 40–1000-fold selectivity over all other Na V subtypes. Despite on-target activity in small-diameter dorsal root ganglia, spinal slices, and in a mouse model of pain induced by Na V1.7 activation, Pn3a alone displayed no analgesic activity in formalin-, carrageenan- or FCA-induced pain in rodents when administered systemically. A broad lack of analgesic activity was also found for the selective Na V1.7 inhibitors PF-04856264 and phlotoxin 1. However, when administered with subtherapeutic doses of opioids or the enkephalinase inhibitor thiorphan, these subtype-selective Na V1.7 inhibitors produced profound analgesia. Our results suggest that in these inflammatory models, acute administration of peripherally restricted Na V1.7 inhibitors can only produce analgesia when administered in combination with an opioid.

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          Most cited references 53

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          MOLMOL: A program for display and analysis of macromolecular structures

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            MOLMOL: a program for display and analysis of macromolecular structures.

            MOLMOL is a molecular graphics program for display, analysis, and manipulation of three-dimensional structures of biological macromolecules, with special emphasis on nuclear magnetic resonance (NMR) solution structures of proteins and nucleic acids. MOLMOL has a graphical user interface with menus, dialog boxes, and on-line help. The display possibilities include conventional presentation, as well as novel schematic drawings, with the option of combining different presentations in one view of a molecule. Covalent molecular structures can be modified by addition or removal of individual atoms and bonds, and three-dimensional structures can be manipulated by interactive rotation about individual bonds. Special efforts were made to allow for appropriate display and analysis of the sets of typically 20-40 conformers that are conventionally used to represent the result of an NMR structure determination, using functions for superimposing sets of conformers, calculation of root mean square distance (RMSD) values, identification of hydrogen bonds, checking and displaying violations of NMR constraints, and identification and listing of short distances between pairs of hydrogen atoms.
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              Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks.

              A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (ϕ, ψ) torsion angles of ca 12º. TALOS-N also reports sidechain χ(1) rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                20 January 2017
                2017
                : 7
                Affiliations
                [1 ]IMB Centre for Pain Research, Institute for Molecular Bioscience, 306 Carmody Rd (Building 80), The University of Queensland, St Lucia , Queensland, 4072, Australia
                [2 ]Discipline of Pharmacology, School of Medical Sciences, The University of Sydney, Sydney , New South Wales, 2006, Australia
                [3 ]School of Biomedical Sciences, The University of Queensland, St Lucia , Queensland, 4072, Australia
                [4 ]Department of Physiology & Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, School of Medicine , Baltimore, MD 21205, USA
                [5 ]Department of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, Connecticut 06510, Rehabilitation Research Center, Veterans Administration Connecticut Healthcare System , West Haven, Connecticut 06516, USA
                [6 ]Venomtech, Sophie-Antipolis , 06560, Valbonne, France
                [7 ]Molecular Nociception Group, Wolfson Institute for Biomedical Research, University College London , London WC1E 6BT, UK
                [8 ]School of Pharmacy, The University of Queensland, Pharmacy Australia Centre of Excellence, 20 Cornwall St, Woolloongabba , Queensland, 4102, Australia
                Author notes
                Article
                srep40883
                10.1038/srep40883
                5247677
                28106092
                f0cc9548-fb93-4e05-bc8b-559031349d9d
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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