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      Chemical profile of Lippia thymoides, evaluation of the acetylcholinesterase inhibitory activity of its essential oil, and molecular docking and molecular dynamics simulations

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          Abstract

          The essential oils of the fresh and dry flowers, leaves, branches, and roots of Lippia thymoides were obtained by hydrodistillation and analyzed using gas chromatography (GC) and GC–mass spectrometry (MS). The acetylcholinesterase inhibitory activity of the essential oil of fresh leaves was investigated on silica gel plates. The interactions of the key compounds with acetylcholinesterase were simulated by molecular docking and molecular dynamics studies. In total, 75 compounds were identified, and oxygenated monoterpenes were the dominant components of all the plant parts, ranging from 19.48% to 84.99%. In the roots, the main compounds were saturated and unsaturated fatty acids, having contents varying from 39.5% to 32.17%, respectively. In the evaluation of the anticholinesterase activity, the essential oils (detection limit (DL) = 0.1 ng/spot) were found to be about ten times less active than that of physostigmine (DL = 0.01ng/spot), whereas thymol and thymol acetate presented DL values each of 0.01 ng/spot, equivalent to that of the positive control. Based on the docking and molecular dynamics studies, thymol and thymol acetate interact with the catalytic residues Ser203 and His447 of the active site of acetylcholinesterase. The binding free energies (Δ G bind) for these ligands were -18.49 and -26.88 kcal/mol, demonstrating that the ligands are able to interact with the protein and inhibit their catalytic activity.

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          Very fast empirical prediction and rationalization of protein pKa values.

          A very fast empirical method is presented for structure-based protein pKa prediction and rationalization. The desolvation effects and intra-protein interactions, which cause variations in pKa values of protein ionizable groups, are empirically related to the positions and chemical nature of the groups proximate to the pKa sites. A computer program is written to automatically predict pKa values based on these empirical relationships within a couple of seconds. Unusual pKa values at buried active sites, which are among the most interesting protein pKa values, are predicted very well with the empirical method. A test on 233 carboxyl, 12 cysteine, 45 histidine, and 24 lysine pKa values in various proteins shows a root-mean-square deviation (RMSD) of 0.89 from experimental values. Removal of the 29 pKa values that are upper or lower limits results in an RMSD = 0.79 for the remaining 285 pKa values. Proteins 2005. 2005 Wiley-Liss, Inc.
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            Langevin stabilization of molecular dynamics

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              Acetylcholinesterase: enzyme structure, reaction dynamics, and virtual transition states

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                Author and article information

                Contributors
                Role: Conceptualization
                Role: ConceptualizationRole: Formal analysis
                Role: InvestigationRole: Visualization
                Role: Visualization
                Role: InvestigationRole: MethodologyRole: ValidationRole: Visualization
                Role: Conceptualization
                Role: InvestigationRole: Writing – original draft
                Role: ResourcesRole: Software
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 March 2019
                2019
                : 14
                : 3
                : e0213393
                Affiliations
                [1 ] Program of Post-Graduation in Chemistry, Federal University of Pará, Belém, PA, Brazil
                [2 ] LABEX/FEA (Faculty of Food Engineering), Program of Post-Graduation in Food Science and Technology, Federal University of Para, Belém, PA, Brazil
                [3 ] Laboratory of Preparation and Computation of Nanomaterials, Federal University of Pará, Belém, PA, Brazil
                [4 ] Department of Natural Sciences, State University of Pará, Belém, PA, Brazil
                [5 ] Program of Post-Graduation in Engineering of Natural Resources of Amazon, Federal University of Pará, Belém, PA, Brazil
                [6 ] Adolpho Ducke Laboratory, Botany Coordinating, Museu Paraense Emílio Goeldi, Belém, PA, Brazil
                The University of Alabama, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-4076-2443
                http://orcid.org/0000-0003-0529-3714
                http://orcid.org/0000-0003-1365-3513
                http://orcid.org/0000-0002-9730-3512
                http://orcid.org/0000-0002-4433-6580
                Article
                PONE-D-18-30541
                10.1371/journal.pone.0213393
                6407782
                30849129
                ff7adb08-bad3-4849-8ff7-d3942cb7beaf
                © 2019 Silva 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
                : 22 October 2018
                : 19 February 2019
                Page count
                Figures: 6, Tables: 3, Pages: 17
                Funding
                Funded by: capes
                Award ID: 1662230
                Award Recipient :
                This work was supported by scholarships awarded to SGS. SGS thanks Secretaria Estadual de Educação do Pará.; Oliveira M. S (Process Number: 1662230) and Costa W. A. (Process Number: 1427204), thanks CAPES for the doctorate scholarship. The funder 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
                Biochemistry
                Lipids
                Oils
                Physical Sciences
                Physics
                Thermodynamics
                Free Energy
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Leaves
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Docking
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Flowers
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Dynamics
                Biology and Life Sciences
                Biochemistry
                Enzymology
                Enzymes
                Proteases
                Serine Proteases
                Biology and Life Sciences
                Biochemistry
                Proteins
                Enzymes
                Proteases
                Serine Proteases
                Biology and Life Sciences
                Biochemistry
                Biochemical Simulations
                Biology and Life Sciences
                Computational Biology
                Biochemical Simulations
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

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                Uncategorized

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