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      PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries

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          Abstract

          Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein’s ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libraries using angiotensin-converting enzyme and GABAB receptor as targets. A reasonable agreement between the computational and experimental data suggests that PeptoGrid is suitable for discovering functional leads.

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          Understanding behavioral and physiological phenotypes of stress and anxiety in zebrafish.

          The zebrafish (Danio rerio) is emerging as a promising model organism for experimental studies of stress and anxiety. Here we further validate zebrafish models of stress by analyzing how environmental and pharmacological manipulations affect their behavioral and physiological phenotypes. Experimental manipulations included exposure to alarm pheromone, chronic exposure to fluoxetine, acute exposure to caffeine, as well as acute and chronic exposure to ethanol. Acute (but not chronic) alarm pheromone and acute caffeine produced robust anxiogenic effects, including reduced exploration, increased erratic movements and freezing behavior in zebrafish tested in the novel tank diving test. In contrast, ethanol and fluoxetine had robust anxiolytic effects, including increased exploration and reduced erratic movements. The behavior of several zebrafish strains was also quantified to ascertain differences in their behavioral profiles, revealing high-anxiety (leopard, albino) and low-anxiety (wild type) strains. We also used LocoScan (CleverSys Inc.) video-tracking tool to quantify anxiety-related behaviors in zebrafish, and dissect anxiety-related phenotypes from locomotor activity. Finally, we developed a simple and effective method of measuring zebrafish physiological stress responses (based on a human salivary cortisol assay), and showed that alterations in whole-body cortisol levels in zebrafish parallel behavioral indices of anxiety. Collectively, our results confirm zebrafish as a valid, reliable, and high-throughput model of stress and affective disorders.
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            Towards a comprehensive catalog of zebrafish behavior 1.0 and beyond.

            Zebrafish (Danio rerio) are rapidly gaining popularity in translational neuroscience and behavioral research. Physiological similarity to mammals, ease of genetic manipulations, sensitivity to pharmacological and genetic factors, robust behavior, low cost, and potential for high-throughput screening contribute to the growing utility of zebrafish models in this field. Understanding zebrafish behavioral phenotypes provides important insights into neural pathways, physiological biomarkers, and genetic underpinnings of normal and pathological brain function. Novel zebrafish paradigms continue to appear with an encouraging pace, thus necessitating a consistent terminology and improved understanding of the behavioral repertoire. What can zebrafish 'do', and how does their altered brain function translate into behavioral actions? To help address these questions, we have developed a detailed catalog of zebrafish behaviors (Zebrafish Behavior Catalog, ZBC) that covers both larval and adult models. Representing a beginning of creating a more comprehensive ethogram of zebrafish behavior, this effort will improve interpretation of published findings, foster cross-species behavioral modeling, and encourage new groups to apply zebrafish neurobehavioral paradigms in their research. In addition, this glossary creates a framework for developing a zebrafish neurobehavioral ontology, ultimately to become part of a unified animal neurobehavioral ontology, which collectively will contribute to better integration of biological data within and across species.
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              Molecular structure and physiological functions of GABA(B) receptors.

              GABA(B) receptors are broadly expressed in the nervous system and have been implicated in a wide variety of neurological and psychiatric disorders. The cloning of the first GABA(B) receptor cDNAs in 1997 revived interest in these receptors and their potential as therapeutic targets. With the availability of molecular tools, rapid progress was made in our understanding of the GABA(B) system. This led to the surprising discovery that GABA(B) receptors need to assemble from distinct subunits to function and provided exciting new insights into the structure of G protein-coupled receptors (GPCRs) in general. As a consequence of this discovery, it is now widely accepted that GPCRs can exist as heterodimers. The cloning of GABA(B) receptors allowed some important questions in the field to be answered. It is now clear that molecular studies do not support the existence of pharmacologically distinct GABA(B) receptors, as predicted by work on native receptors. Advances were also made in clarifying the relationship between GABA(B) receptors and the receptors for gamma-hydroxybutyrate, an emerging drug of abuse. There are now the first indications linking GABA(B) receptor polymorphisms to epilepsy. Significantly, the cloning of GABA(B) receptors enabled identification of the first allosteric GABA(B) receptor compounds, which is expected to broaden the spectrum of therapeutic applications. Here we review current concepts on the molecular composition and function of GABA(B) receptors and discuss ongoing drug-discovery efforts.
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                Author and article information

                Journal
                Molecules
                Molecules
                molecules
                Molecules
                MDPI
                1420-3049
                13 January 2019
                January 2019
                : 24
                : 2
                : 277
                Affiliations
                [1 ]Faculty of Bioengineering, Lomonosov Moscow State University, Moscow 119234, Russia; alexander.zlobin@ 123456fbb.msu.ru (A.S.Z.); golovin.andrey@ 123456gmail.com (A.V.G.)
                [2 ]Ineractomics Lab, Institute of Molecular Medicine, Sechenov First Moscow State Medical University, Moscow 119146, Russia; r.reshetnikov@ 123456gmail.com
                [3 ]Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow 117997, Russia
                [4 ]Lactocore Inc., Plymouth, MI 48170, USA; vrgedzun@ 123456gmail.com (V.R.G.); malyshev@ 123456lactocore.com (A.V.M.); doronin@ 123456lactocore.com (I.I.D.); gbabkin3@ 123456mail.ru (G.A.B.)
                [5 ]Department of Human and Animal Physiology, Faculty of Biology, Lomonosov Moscow State University, Moscow 119899, Russia; lovat@ 123456mail.ru
                [6 ]Faculty of Computer Science, National Research University Higher School of Economics, Moscow 101000, Russia
                Author notes
                [* ]Correspondence: aozalevsky@ 123456fbb.msu.ru ; Tel.: +7-926-829-9066
                Author information
                https://orcid.org/0000-0001-6987-8119
                https://orcid.org/0000-0001-5500-3549
                https://orcid.org/0000-0002-8908-4268
                Article
                molecules-24-00277
                10.3390/molecules24020277
                6359344
                30642123
                717fc3fe-0488-496e-8f1d-7d0e6018e55e
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 26 November 2018
                : 09 January 2019
                Categories
                Communication

                docking,peptides,rescoring,gabab receptor,danio rerio
                docking, peptides, rescoring, gabab receptor, danio rerio

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