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      Novel Bacterial Topoisomerase Inhibitors Exploit Asp83 and the Intrinsic Flexibility of the DNA Gyrase Binding Site

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          Abstract

          DNA gyrases are enzymes that control the topology of DNA in bacteria cells. This is a vital function for bacteria. For this reason, DNA gyrases are targeted by widely used antibiotics such as quinolones. Recently, structural and biochemical investigations identified a new class of DNA gyrase inhibitors called NBTIs (i.e., novel bacterial topoisomerase inhibitors). NBTIs are particularly promising because they are active against multi-drug resistant bacteria, an alarming clinical issue. Structural data recently demonstrated that these NBTIs bind tightly to a newly identified pocket at the dimer interface of the DNA–protein complex. In the present study, we used molecular dynamics (MD) simulations and docking calculations to shed new light on the binding of NBTIs to this site. Interestingly, our MD simulations demonstrate the intrinsic flexibility of this binding site, which allows the pocket to adapt its conformation and form optimal interactions with the ligand. In particular, we examined two ligands, AM8085 and AM8191, which induced a repositioning of a key aspartate (Asp83B), whose side chain can rotate within the binding site. The conformational rearrangement of Asp83B allows the formation of a newly identified H-bond interaction with an NH on the bound NBTI, which seems important for the binding of NBTIs having such functionality. We validated these findings through docking calculations using an extended set of cognate oxabicyclooctane-linked NBTIs derivatives (~150, in total), screened against multiple target conformations. The newly identified H-bond interaction significantly improves the docking enrichment. These insights could be helpful for future virtual screening campaigns against DNA gyrase.

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          Most cited references45

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          PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions.

          In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.
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            Epik: a software program for pK( a ) prediction and protonation state generation for drug-like molecules.

            Epik is a computer program for predicting pK(a) values for drug-like molecules. Epik can use this capability in combination with technology for tautomerization to adjust the protonation state of small drug-like molecules to automatically generate one or more of the most probable forms for use in further molecular modeling studies. Many medicinal chemicals can exchange protons with their environment, resulting in various ionization and tautomeric states, collectively known as protonation states. The protonation state of a drug can affect its solubility and membrane permeability. In modeling, the protonation state of a ligand will also affect which conformations are predicted for the molecule, as well as predictions for binding modes and ligand affinities based upon protein-ligand interactions. Despite the importance of the protonation state, many databases of candidate molecules used in drug development do not store reliable information on the most probable protonation states. Epik is sufficiently rapid and accurate to process large databases of drug-like molecules to provide this information. Several new technologies are employed. Extensions to the well-established Hammett and Taft approaches are used for pK(a) prediction, namely, mesomer standardization, charge cancellation, and charge spreading to make the predicted results reflect the nature of the molecule itself rather just for the particular Lewis structure used on input. In addition, a new iterative technology for generating, ranking and culling the generated protonation states is employed.
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              Mechanism of Quinolone Action and Resistance

              Quinolones are one of the most commonly prescribed classes of antibacterials in the world and are used to treat a variety of bacterial infections in humans. Because of the wide use (and overuse) of these drugs, the number of quinolone-resistant bacterial strains has been growing steadily since the 1990s. As is the case with other antibacterial agents, the rise in quinolone resistance threatens the clinical utility of this important drug class. Quinolones act by converting their targets, gyrase and topoisomerase IV, into toxic enzymes that fragment the bacterial chromosome. This review describes the development of the quinolones as antibacterials, the structure and function of gyrase and topoisomerase IV, and the mechanistic basis for quinolone action against their enzyme targets. It will then discuss the following three mechanisms that decrease the sensitivity of bacterial cells to quinolones. Target-mediated resistance is the most common and clinically significant form of resistance. It is caused by specific mutations in gyrase and topoisomerase IV that weaken interactions between quinolones and these enzymes. Plasmid-mediated resistance results from extrachromosomal elements that encode proteins that disrupt quinolone–enzyme interactions, alter drug metabolism, or increase quinolone efflux. Chromosome-mediated resistance results from the underexpression of porins or the overexpression of cellular efflux pumps, both of which decrease cellular concentrations of quinolones. Finally, this review will discuss recent advancements in our understanding of how quinolones interact with gyrase and topoisomerase IV and how mutations in these enzymes cause resistance. These last findings suggest approaches to designing new drugs that display improved activity against resistant strains.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                03 February 2018
                February 2018
                : 19
                : 2
                : 453
                Affiliations
                [1 ]COBO Computational Bio-Organic Chemistry Bogotá, Chemistry Department, Universidad de los Andes, Cra 1 No 18A-12, 111711 Bogotá, Colombia; sebastian.franco@ 123456iit.it
                [2 ]Laboratory of Molecular Modeling and Drug Discovery, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genova, Italy; giuseppina.lasala@ 123456bikitech.com
                [3 ]IAS-5/INM-9 Computational Biomedicine Forschungszentrum Jülich Wilhelm-Johnen-Straße, 52428 Jülich, Germany
                Author notes
                [†]

                These authors contributed equally to this work.

                [‡]

                Current Address: BiKi Technologies S.r.l., Via XX Settembre 33, 16121 Genoa, Italy.

                Author information
                https://orcid.org/0000-0003-2262-9179
                https://orcid.org/0000-0003-4022-5661
                Article
                ijms-19-00453
                10.3390/ijms19020453
                5855675
                29401640
                a175cb8b-36c7-4d19-9136-3f3cebf3c56d
                © 2018 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
                : 24 January 2018
                : 30 January 2018
                Categories
                Article

                Molecular biology
                dna gyrase,nbti,topoisomerases,drug resistance,md simulation,docking,antibiotics
                Molecular biology
                dna gyrase, nbti, topoisomerases, drug resistance, md simulation, docking, antibiotics

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