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      Virtual Screening of Peptide and Peptidomimetic Fragments Targeted to Inhibit Bacterial Dithiol Oxidase DsbA

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          Abstract

          Antibacterial drugs with novel scaffolds and new mechanisms of action are desperately needed to address the growing problem of antibiotic resistance. The periplasmic oxidative folding system in Gram-negative bacteria represents a possible target for anti-virulence antibacterials. By targeting virulence rather than viability, development of resistance and side effects (through killing host native microbiota) might be minimized. Here, we undertook the design of peptidomimetic inhibitors targeting the interaction between the two key enzymes of oxidative folding, DsbA and DsbB, with the ultimate goal of preventing virulence factor assembly. Structures of DsbB - or peptides - complexed with DsbA revealed key interactions with the DsbA active site cysteine, and with a hydrophobic groove adjacent to the active site. The present work aimed to discover peptidomimetics that target the hydrophobic groove to generate non-covalent DsbA inhibitors. The previously reported structure of a Proteus mirabilis DsbA active site cysteine mutant, in a non-covalent complex with the heptapeptide PWATCDS, was used as an in silico template for virtual screening of a peptidomimetic fragment library. The highest scoring fragment compound and nine derivatives were synthesized and evaluated for DsbA binding and inhibition. These experiments discovered peptidomimetic fragments with inhibitory activity at millimolar concentrations. Although only weakly potent relative to larger covalent peptide inhibitors that interact through the active site cysteine, these fragments offer new opportunities as templates to build non-covalent inhibitors. The results suggest that non-covalent peptidomimetics may need to interact with sites beyond the hydrophobic groove in order to produce potent DsbA inhibitors.

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          Most cited references53

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          Improved protein-ligand docking using GOLD.

          The Chemscore function was implemented as a scoring function for the protein-ligand docking program GOLD, and its performance compared to the original Goldscore function and two consensus docking protocols, "Goldscore-CS" and "Chemscore-GS," in terms of docking accuracy, prediction of binding affinities, and speed. In the "Goldscore-CS" protocol, dockings produced with the Goldscore function are scored and ranked with the Chemscore function; in the "Chemscore-GS" protocol, dockings produced with the Chemscore function are scored and ranked with the Goldscore function. Comparisons were made for a "clean" set of 224 protein-ligand complexes, and for two subsets of this set, one for which the ligands are "drug-like," the other for which they are "fragment-like." For "drug-like" and "fragment-like" ligands, the docking accuracies obtained with Chemscore and Goldscore functions are similar. For larger ligands, Goldscore gives superior results. Docking with the Chemscore function is up to three times faster than docking with the Goldscore function. Both combined docking protocols give significant improvements in docking accuracy over the use of the Goldscore or Chemscore function alone. "Goldscore-CS" gives success rates of up to 81% (top-ranked GOLD solution within 2.0 A of the experimental binding mode) for the "clean list," but at the cost of long search times. For most virtual screening applications, "Chemscore-GS" seems optimal; search settings that give docking speeds of around 0.25-1.3 min/compound have success rates of about 78% for "drug-like" compounds and 85% for "fragment-like" compounds. In terms of producing binding energy estimates, the Goldscore function appears to perform better than the Chemscore function and the two consensus protocols, particularly for faster search settings. Even at docking speeds of around 1-2 min/compound, the Goldscore function predicts binding energies with a standard deviation of approximately 10.5 kJ/mol. Copyright 2003 Wiley-Liss, Inc.
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            The expanding scope of antimicrobial peptide structures and their modes of action.

            Antimicrobial peptides (AMPs) are an integral part of the innate immune system that protect a host from invading pathogenic bacteria. To help overcome the problem of antimicrobial resistance, cationic AMPs are currently being considered as potential alternatives for antibiotics. Although extremely variable in length, amino acid composition and secondary structure, all peptides can adopt a distinct membrane-bound amphipathic conformation. Recent studies demonstrate that they achieve their antimicrobial activity by disrupting various key cellular processes. Some peptides can even use multiple mechanisms. Moreover, several intact proteins or protein fragments are now being shown to have inherent antimicrobial activity. A better understanding of the structure-activity relationships of AMPs is required to facilitate the rational design of novel antimicrobial agents. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database

              Here, we present the algorithm and validation for OMEGA, a systematic, knowledge-based conformer generator. The algorithm consists of three phases: assembly of an initial 3D structure from a library of fragments; exhaustive enumeration of all rotatable torsions using values drawn from a knowledge-based list of angles, thereby generating a large set of conformations; and sampling of this set by geometric and energy criteria. Validation of conformer generators like OMEGA has often been undertaken by comparing computed conformer sets to experimental molecular conformations from crystallography, usually from the Protein Databank (PDB). Such an approach is fraught with difficulty due to the systematic problems with small molecule structures in the PDB. Methods are presented to identify a diverse set of small molecule structures from cocomplexes in the PDB that has maximal reliability. A challenging set of 197 high quality, carefully selected ligand structures from well-solved models was obtained using these methods. This set will provide a sound basis for comparison and validation of conformer generators in the future. Validation results from this set are compared to the results using structures of a set of druglike molecules extracted from the Cambridge Structural Database (CSD). OMEGA is found to perform very well in reproducing the crystallographic conformations from both these data sets using two complementary metrics of success.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                30 July 2015
                2015
                : 10
                : 7
                : e0133805
                Affiliations
                [001]Division of Chemistry and Structural Biology, Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
                University of Minnesota, UNITED STATES
                Author notes

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

                Conceived and designed the experiments: WD PB MJS DPF JLM. Performed the experiments: WD PB MJS ST RMM. Analyzed the data: WD PB MJS ST RMM DPF JLM. Wrote the paper: WD PB MJS RMM DPF JLM.

                Article
                PONE-D-15-20526
                10.1371/journal.pone.0133805
                4520593
                26225423
                1af83e35-ac83-4c41-9d72-c13ffb1303d3
                Copyright @ 2015

                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
                : 12 May 2015
                : 13 June 2015
                Page count
                Figures: 5, Tables: 0, Pages: 16
                Funding
                Australian Research Council Laureate Fellowship FL0992138 to JLM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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