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      Stereoselectivity of Aldose Reductase in the Reduction of Glutathionyl-Hydroxynonanal Adduct

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          Abstract

          The formation of the adduct between the lipid peroxidation product 4-hydroxy-2-nonenal (HNE) and glutathione, which leads to the generation of 3-glutathionyl-4-hydroxynonane (GSHNE), is one of the main routes of HNE detoxification. The aldo-keto reductase AKR1B1 is involved in the reduction of the aldehydic group of both HNE and GSHNE. In the present study, the effect of chirality on the recognition by aldose reductase of HNE and GSHNE was evaluated. AKR1B1 discriminates very modestly between the two possible enantiomers of HNE as substrates. Conversely, a combined kinetic analysis of the glutathionyl adducts obtained starting from either 4R- or 4S-HNE and mass spectrometry analysis of GSHNE products obtained from racemic HNE revealed that AKR1B1 possesses a marked preference toward the 3S,4R-GSHNE diastereoisomer. Density functional theory and molecular modeling studies revealed that this diastereoisomer, besides having a higher tendency to be in an open aldehydic form (the one recognized by AKR1B1) in solution than other GSHNE diastereoisomers, is further stabilized in its open form by a specific interaction with the enzyme active site. The relevance of this stereospecificity to the final metabolic fate of GSHNE is discussed.

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          Improved protein-ligand docking using GOLD.

          Marcel Verdonk, Jason Cole, Michael J Hartshorn … (2003)
          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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            Lipid peroxidation of membrane phospholipids generates hydroxy-alkenals and oxidized phospholipids active in physiological and/or pathological conditions.

            Ángel Catalá (2009)
            Polyunsaturated fatty acids (PUFAs) and their metabolites have a variety of physiological roles including: energy provision, membrane structure, cell signaling and regulation of gene expression. Lipids containing polyunsaturated fatty acids are susceptible to free radical-initiated oxidation and can participate in chain reactions that increase damage to biomolecules. Lipid peroxidation, which leads to lipid hydroperoxide formation often, occurs in response to oxidative stress. Hydroperoxides are usually reduced to their corresponding alcohols by glutathione peroxidases. However, these enzymes are decreased in certain diseases resulting in a temporary increase of lipid hydroperoxides that favors their degradation into several compounds, including hydroxy-alkenals. The best known of these are: 4-hydroxy-2-nonenal (4-HNE) and 4-hydroxy-2-hexenal (4-HHE), which derive from lipid peroxidation of n-6 and n-3 fatty acids, respectively. Compared to free radicals, these aldehydes are relatively stable and can diffuse within or even escape from the cell and attack targets far from the site of the original event. These aldehydes exhibit great reactivity with biomolecules, such as proteins, DNA, and phospholipids, generating a variety of intra and intermolecular covalent adducts. At the membrane level, proteins and amino lipids can be covalently modified by lipid peroxidation products (hydoxy-alkenals). These aldehydes can also act as bioactive molecules in physiological and/or pathological conditions. In addition this review is intended to provide an appropriate synopsis of identified effects of hydroxy-alkenals and oxidized phospholipids on cell signaling, from their intracellular production, to their action as intracellular messenger, up to their influence on transcription factors and gene expression.
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              DL-FIND: an open-source geometry optimizer for atomistic simulations.

              Norman J. Carr, Thomas Keal, Paul Sherwood … (2009)
              Geometry optimization, including searching for transition states, accounts for most of the CPU time spent in quantum chemistry, computational surface science, and solid-state physics, and also plays an important role in simulations employing classical force fields. We have implemented a geometry optimizer, called DL-FIND, to be included in atomistic simulation codes. It can optimize structures in Cartesian coordinates, redundant internal coordinates, hybrid-delocalized internal coordinates, and also functions of more variables independent of atomic structures. The implementation of the optimization algorithms is independent of the coordinate transformation used. Steepest descent, conjugate gradient, quasi-Newton, and L-BFGS algorithms as well as damped molecular dynamics are available as minimization methods. The partitioned rational function optimization algorithm, a modified version of the dimer method and the nudged elastic band approach provide capabilities for transition-state search. Penalty function, gradient projection, and Lagrange-Newton methods are implemented for conical intersection optimizations. Various stochastic search methods, including a genetic algorithm, are available for global or local minimization and can be run as parallel algorithms. The code is released under the open-source GNU LGPL license. Some selected applications of DL-FIND are surveyed.
              Article 0 comments Cited 130 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Antioxidants (Basel)
                Journal ID (iso-abbrev): Antioxidants (Basel)
                Journal ID (publisher-id): antioxidants
                Title: Antioxidants
                Publisher: MDPI
                ISSN (Electronic): 2076-3921
                Publication date (Electronic): 22 October 2019
                Publication date Collection: October 2019
                Volume: 8
                Issue: 10
                Electronic Location Identifier: 502
                Affiliations
                [1 ]Biochemistry Unit, Department of Biology, University of Pisa, via S. Zeno 51, 56127 Pisa, Italy; francesco.balestri@ 123456unipi.it (F.B.); vito-00@ 123456hotmail.it (V.B.); mario.cappiello@ 123456unipi.it (M.C.); rossellarotondo@ 123456libero.it (R.R.); umberto.mura@ 123456unipi.it (U.M.); roberta.moschini@ 123456unipi.it (R.M.)
                [2 ]Interdepartmental Research Center Nutrafood “Nutraceuticals and Food for Health”, University of Pisa, 56124 Pisa, Italy
                [3 ]Proteomics & Mass Spectrometry Laboratory, ISPAAM-CNR, Via Argine 1085, 80147 Napoli, Italy; giovanni.renzone@ 123456ispaam.cnr.it (G.R.); andrea.scaloni@ 123456ispaam.cnr.it (A.S.)
                [4 ]Department of Pharmacy, University of Pisa, via Bonanno 6, 56126 Pisa, Italy; tiziano.tuccinardi@ 123456unipi.it (T.T.); christian.pomelli@ 123456unipi.it (C.S.P.)
                [5 ]Department of Chemistry and Industrial Chemistry, University of Pisa, via G. Moruzzi, 13, 56124 Pisa, Italy; marco.lessi@ 123456unipi.it (M.L.); fabio.bellina@ 123456unipi.it (F.B.)
                Author notes
                [* ]Correspondence: antonella.delcorso@ 123456unipi.it ; Tel.: +39-050-2211454
                [†]

                Present address: Pathology Department, IRCCS, CRO Aviano, National Cancer Institute, 33081 Aviano, (PN), Italy.

                Author information
                https://orcid.org/0000-0002-6205-4069
                https://orcid.org/0000-0002-0090-7070
                Article
                Publisher ID: antioxidants-08-00502
                DOI: 10.3390/antiox8100502
                PMC ID: 6827081
                PubMed ID: 31652566
                SO-VID: cefdef32-2fe5-4103-a916-082fed13006e
                Copyright © © 2019 by the authors.
                License:

                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
                Date received : 23 September 2019
                Date accepted : 21 October 2019
                Categories
                Subject: Article

                Keywords: aldose reductase,4-hydroxy-2-nonenal,3-glutathionyl-4-hydroxynonenal,inflammation
                Data availability:
                Keywords: aldose reductase, 4-hydroxy-2-nonenal, 3-glutathionyl-4-hydroxynonenal, inflammation

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