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Calculation of substrate binding affinities for a bacterial GH78 rhamnosidase through molecular dynamics simulations

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      •Structural model of rhamnosidase Ram2 of Pediococcus acidilactici.•Calculated binding free energies of rutinose and p-NPR agree with experiments.•Suggested binding poses of rutinose and p-NPR are distinctly different.•Different binding poses of rutinose and p-NPR are supported by experiments.•Active site residues are proposed for further mutagenesis studies

      Abstract

      Ram2 from Pediococcus acidilactici is a rhamnosidase from the glycoside hydrolase family 78. It shows remarkable selectivity for rutinose rather than para-nitrophenyl-alpha-l-rhamnopyranoside (p-NPR). Molecular dynamics simulations were performed using a homology model of this enzyme, in complex with both substrates. Free energy calculations lead to predicted binding affinities of −34.4 and −30.6 kJ mol−1 respectively, agreeing well with an experimentally estimated relative free energy of 5.4 kJ mol−1. Further, the most relevant binding poses could be determined. While p-NPR preferably orients its rhamnose moiety toward the active site, rutinose interacts most strongly with its glucose moiety. A detailed hydrogen bond analysis confirms previously implicated residues in the active site (Asp217, Asp222, Trp226, Asp229 and Glu488) and quantifies the importance of individual residues for the binding. The most important amino acids are Asp229 and Phe339 which are involved in many interactions during the simulations. While Phe339 was observed in more simulations, Asp229 was involved in more persistent interactions (forming an average of at least 2 hydrogen bonds during the simulation). These analyses directly suggest mutations that could be used in a further experimental characterization of the enzyme. This study shows once more the strength of computer simulations to rationalize and guide experiments at an atomic level.

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      Most cited references 43

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      Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features.

       C. Sander,  W Kabsch (1983)
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        The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling.

        Homology models of proteins are of great interest for planning and analysing biological experiments when no experimental three-dimensional structures are available. Building homology models requires specialized programs and up-to-date sequence and structural databases. Integrating all required tools, programs and databases into a single web-based workspace facilitates access to homology modelling from a computer with web connection without the need of downloading and installing large program packages and databases. SWISS-MODEL workspace is a web-based integrated service dedicated to protein structure homology modelling. It assists and guides the user in building protein homology models at different levels of complexity. A personal working environment is provided for each user where several modelling projects can be carried out in parallel. Protein sequence and structure databases necessary for modelling are accessible from the workspace and are updated in regular intervals. Tools for template selection, model building and structure quality evaluation can be invoked from within the workspace. Workflow and usage of the workspace are illustrated by modelling human Cyclin A1 and human Transmembrane Protease 3. The SWISS-MODEL workspace can be accessed freely at http://swissmodel.expasy.org/workspace/
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          Is Open Access

          The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics

          The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates. As of September 2008, the database describes the present knowledge on 113 glycoside hydrolase, 91 glycosyltransferase, 19 polysaccharide lyase, 15 carbohydrate esterase and 52 carbohydrate-binding module families. These families are created based on experimentally characterized proteins and are populated by sequences from public databases with significant similarity. Protein biochemical information is continuously curated based on the available literature and structural information. Over 6400 proteins have assigned EC numbers and 700 proteins have a PDB structure. The classification (i) reflects the structural features of these enzymes better than their sole substrate specificity, (ii) helps to reveal the evolutionary relationships between these enzymes and (iii) provides a convenient framework to understand mechanistic properties. This resource has been available for over 10 years to the scientific community, contributing to information dissemination and providing a transversal nomenclature to glycobiologists. More recently, this resource has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation. The CAZy resource resides at URL: http://www.cazy.org/.
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            Author and article information

            Affiliations
            Department of Material Sciences and Process Engineering, Institute of Molecular Modeling and Simulation, University of Natural Resources and Life Sciences Vienna, Muthgasse 18, A-1190 Vienna, Austria
            Department of Food Science and Technology, Institute of Food Technology, University of Natural Resources and Life Sciences Vienna, Muthgasse 18, A-1190 Vienna, Austria
            Author notes
            [* ]Corresponding author. Tel.: +43 1 47654 8302; fax: +43 1 47654 8309. chris.oostenbrink@ 123456boku.ac.at
            Contributors
            Journal
            J Mol Catal B Enzym
            J. Mol. Catal., B Enzym
            Journal of Molecular Catalysis. B, Enzymatic
            Elsevier Science
            1381-1177
            1873-3158
            1 August 2013
            August 2013
            : 92
            : 100
            : 34-43
            23914137
            3663046
            MOLCAB2652
            10.1016/j.molcatb.2013.03.012
            © 2013 Elsevier B.V.

            This document may be redistributed and reused, subject to certain conditions.

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