The Enolase Superfamily: a General Strategy for Enzyme-Catalyzed Abstraction of the R-Protons of Carboxylic Acids†
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Dr. Martin St. Maurice's Publications
Dr. Martin St. Maurice’s Publications 2013 Lin, Y., and St. Maurice, M. 2013. The structure of allophanate hydrolase from Granulibacter bethesdensis provides insights into substrate specificity in the amidase signature family. Biochemistry. 52: 690-700. 2012 Waldrop, G.L., Holden, H.M., and St. Maurice, M. 2012. The enzymes of biotin dependent CO2 metabolism: What structures reveal about their reaction mechanisms. Protein Science 21(11):1597-1619. Adina-Zada, A., Sereeruk, C., Jitrapakdee, S., Zeczycki, T.N., St. Maurice, M., Cleland, W.W., Wallace, J.C., and Attwood, P.V. 2012. Roles of Arg427 and Arg472 in the binding and allosteric effects of acetyl CoA in pyruvate carboxylase. Biochemistry 51(41): 1597-1619. 2011 Adina-Zada, A., Hazra, R., Sereeruk, C., Jitrapakdee, S., Zeczycki, T.N., St. Maurice, M., Cleland, W.W., Wallace, J.C., and Attwood, P.V. 2011. Probing the allosteric activation of pyruvate carboxylase using 2′,3′-O-(2,4,6-trinitrophenyl) adenosine 5′-triphosphate as a fluorescent mimic of the allosteric activator acetyl CoA. Arch. Biochem. Biophys. 117-126. Zeczycki, T.N., Menefee, A.L., Jitrapakdee, S., Wallace, J.C., Attwood, P.V., St. Maurice, M. and Cleland, W.W. 2011. Activation and inhibition of pyruvate carboxylase from Rhizobium etli. Biochemistry. 9694-9707. Lietzan, A.D., Menefee, A.L., Zeczycki, T.N., Kumar, S., Attwood, P.V., Wallace, J.C., Cleland, W.W. and St. Maurice, M. 2011. Interaction between the biotin carrier domain and the biotin carboxylase domain in the structure of Rhizobium etli pyruvate carboxylase. Biochemistry. 9708-9723. Zeczycki, T.N., Menefee, A.L., Adina-Zada, A., Surinya, K.H., Wallace, J.C., Attwood, P.V., St. -
Assembly of an Active Enzyme by the Linkage of Two Protein Modules
Proc. Natl. Acad. Sci. USA Vol. 94, pp. 1069–1073, February 1997 Biochemistry Assembly of an active enzyme by the linkage of two protein modules A. E. NIXON,M.S.WARREN, AND S. J. BENKOVIC* 152 Davey Laboratory, Department of Chemistry, Pennsylvania State University, University Park, PA 16802-6300 Contributed by S. J. Benkovic, December 9, 1996 ABSTRACT The feasibility of creating new enzyme activ- design enzymes with novel properties. Previous approaches to ities from enzymes of known function has precedence in view the design of proteins with novel activities have included of protein evolution based on the concepts of molecular catalytic antibodies (8, 9); introduction of metal ion binding recruitment and exon shuffling. The enzymes encoded by the sites, such as the one engineered into trypsin to allow either Escherichia coli genes purU and purN, N10-formyltetrahydro- control of the proteolytic activity (10) or to regulate specificity folate hydrolase and glycinamide ribonucleotide (GAR) trans- (11); creation of hybrid enzymes through exchange of subunits formylase, respectively, catalyze similiar yet distinct reactions. to create hybrid oligomers (12); replacement of structural N10-formyltetrahydrofolate hydrolase uses water to cleave elements such as the DNA binding domain of GCN4 with that N10-formyltetrahydrofolate into tetrahydrofolate and for- of CyEBP (13); mutation of multiple individual residues to mate, whereas GAR transformylase catalyses the transfer of change the cofactor specificity of glutathione reductase from formyl from N10-formyltetrahydrofolate to GAR to yield NADPH to NADH (14), modulation of the substrate speci- formyl-GAR and tetrahydrofolate. The two enzymes show ficity of aspartate aminotransferase (15); and changing the significant homology ('60%) in the carboxyl-terminal region specificity of subtilisin (16) and a-lytic protease (17) through which, from the GAR transformylase crystal structure and mutation of single functional groups. -
Resolution of Carbon Metabolism and Sulfur-Oxidation Pathways of Metallosphaera Cuprina Ar-4 Via Comparative Proteomics
JOURNAL OF PROTEOMICS 109 (2014) 276– 289 Available online at www.sciencedirect.com ScienceDirect www.elsevier.com/locate/jprot Resolution of carbon metabolism and sulfur-oxidation pathways of Metallosphaera cuprina Ar-4 via comparative proteomics Cheng-Ying Jianga, Li-Jun Liua, Xu Guoa, Xiao-Yan Youa, Shuang-Jiang Liua,c,⁎, Ansgar Poetschb,⁎⁎ aState Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, PR China bPlant Biochemistry, Ruhr University Bochum, Bochum, Germany cEnvrionmental Microbiology and Biotechnology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, PR China ARTICLE INFO ABSTRACT Article history: Metallosphaera cuprina is able to grow either heterotrophically on organics or autotrophically Received 16 March 2014 on CO2 with reduced sulfur compounds as electron donor. These traits endowed the species Accepted 6 July 2014 desirable for application in biomining. In order to obtain a global overview of physiological Available online 14 July 2014 adaptations on the proteome level, proteomes of cytoplasmic and membrane fractions from cells grown autotrophically on CO2 plus sulfur or heterotrophically on yeast extract Keywords: were compared. 169 proteins were found to change their abundance depending on growth Quantitative proteomics condition. The proteins with increased abundance under autotrophic growth displayed Bioleaching candidate enzymes/proteins of M. cuprina for fixing CO2 through the previously identified Autotrophy 3-hydroxypropionate/4-hydroxybutyrate cycle and for oxidizing elemental sulfur as energy Heterotrophy source. The main enzymes/proteins involved in semi- and non-phosphorylating Entner– Industrial microbiology Doudoroff (ED) pathway and TCA cycle were less abundant under autotrophic growth. Also Extremophile some transporter proteins and proteins of amino acid metabolism changed their abundances, suggesting pivotal roles for growth under the respective conditions. -
Generated by SRI International Pathway Tools Version 25.0, Authors S
Authors: Pallavi Subhraveti Ron Caspi Quang Ong Peter D Karp An online version of this diagram is available at BioCyc.org. Biosynthetic pathways are positioned in the left of the cytoplasm, degradative pathways on the right, and reactions not assigned to any pathway are in the far right of the cytoplasm. Transporters and membrane proteins are shown on the membrane. Ingrid Keseler Periplasmic (where appropriate) and extracellular reactions and proteins may also be shown. Pathways are colored according to their cellular function. Gcf_000725805Cyc: Streptomyces xanthophaeus Cellular Overview Connections between pathways are omitted for legibility. -
Supporting Information High-Throughput Virtual Screening
Supporting Information High-Throughput Virtual Screening of Proteins using GRID Molecular Interaction Fields Simone Sciabola, Robert V. Stanton, James E. Mills, Maria M. Flocco, Massimo Baroni, Gabriele Cruciani, Francesca Perruccio and Jonathan S. Mason Contents Table S1 S2-S21 Figure S1 S22 * To whom correspondence should be addressed: Simone Sciabola, Pfizer Research Technology Center, Cambridge, 02139 MA, USA Phone: +1-617-551-3327; Fax: +1-617-551-3117; E-mail: [email protected] S1 Table S1. Description of the 990 proteins used as decoy for the Protein Virtual Screening analysis. PDB ID Protein family Molecule Res. (Å) 1n24 ISOMERASE (+)-BORNYL DIPHOSPHATE SYNTHASE 2.3 1g4h HYDROLASE 1,3,4,6-TETRACHLORO-1,4-CYCLOHEXADIENE HYDROLASE 1.8 1cel HYDROLASE(O-GLYCOSYL) 1,4-BETA-D-GLUCAN CELLOBIOHYDROLASE I 1.8 1vyf TRANSPORT PROTEIN 14 KDA FATTY ACID BINDING PROTEIN 1.85 1o9f PROTEIN-BINDING 14-3-3-LIKE PROTEIN C 2.7 1t1s OXIDOREDUCTASE 1-DEOXY-D-XYLULOSE 5-PHOSPHATE REDUCTOISOMERASE 2.4 1t1r OXIDOREDUCTASE 1-DEOXY-D-XYLULOSE 5-PHOSPHATE REDUCTOISOMERASE 2.3 1q0q OXIDOREDUCTASE 1-DEOXY-D-XYLULOSE 5-PHOSPHATE REDUCTOISOMERASE 1.9 1jcy LYASE 2-DEHYDRO-3-DEOXYPHOSPHOOCTONATE ALDOLASE 1.9 1fww LYASE 2-DEHYDRO-3-DEOXYPHOSPHOOCTONATE ALDOLASE 1.85 1uk7 HYDROLASE 2-HYDROXY-6-OXO-7-METHYLOCTA-2,4-DIENOATE 1.7 1v11 OXIDOREDUCTASE 2-OXOISOVALERATE DEHYDROGENASE ALPHA SUBUNIT 1.95 1x7w OXIDOREDUCTASE 2-OXOISOVALERATE DEHYDROGENASE ALPHA SUBUNIT 1.73 1d0l TRANSFERASE 35KD SOLUBLE LYTIC TRANSGLYCOSYLASE 1.97 2bt4 LYASE 3-DEHYDROQUINATE DEHYDRATASE -
Supplementary Information
Supplementary information (a) (b) Figure S1. Resistant (a) and sensitive (b) gene scores plotted against subsystems involved in cell regulation. The small circles represent the individual hits and the large circles represent the mean of each subsystem. Each individual score signifies the mean of 12 trials – three biological and four technical. The p-value was calculated as a two-tailed t-test and significance was determined using the Benjamini-Hochberg procedure; false discovery rate was selected to be 0.1. Plots constructed using Pathway Tools, Omics Dashboard. Figure S2. Connectivity map displaying the predicted functional associations between the silver-resistant gene hits; disconnected gene hits not shown. The thicknesses of the lines indicate the degree of confidence prediction for the given interaction, based on fusion, co-occurrence, experimental and co-expression data. Figure produced using STRING (version 10.5) and a medium confidence score (approximate probability) of 0.4. Figure S3. Connectivity map displaying the predicted functional associations between the silver-sensitive gene hits; disconnected gene hits not shown. The thicknesses of the lines indicate the degree of confidence prediction for the given interaction, based on fusion, co-occurrence, experimental and co-expression data. Figure produced using STRING (version 10.5) and a medium confidence score (approximate probability) of 0.4. Figure S4. Metabolic overview of the pathways in Escherichia coli. The pathways involved in silver-resistance are coloured according to respective normalized score. Each individual score represents the mean of 12 trials – three biological and four technical. Amino acid – upward pointing triangle, carbohydrate – square, proteins – diamond, purines – vertical ellipse, cofactor – downward pointing triangle, tRNA – tee, and other – circle. -
Molecular and Functional Analysis of Nicotinate Catabolism in Eubacterium Barkeri
Molecular and functional analysis of nicotinate catabolism in Eubacterium barkeri Ashraf Alhapel, Daniel J. Darley, Nadine Wagener, Elke Eckel, Nora Elsner, and Antonio J. Pierik* Laboratorium fu¨r Mikrobielle Biochemie, Fachbereich Biologie, Philipps Universita¨t, D-35032 Marburg, Germany Edited by Perry A. Frey, University of Wisconsin, Madison, WI, and approved June 29, 2006 (received for review March 1, 2006) The anaerobic soil bacterium Eubacterium barkeri catabolizes nic- complex (see Fig. 1). Based on the identified intermediates, otinate to pyruvate and propionate via a unique fermentation. A several anticipated enzymes were purified and characterized: full molecular characterization of nicotinate fermentation in this nicotinate dehydrogenase (12), 6-hydroxynicotinate reductase organism was accomplished by the following results: (i) A 23.2-kb (7), 2-methyleneglutarate mutase, and 3-methylitaconate DNA segment with a gene cluster encoding all nine enzymes was isomerase (13, 14). These findings outlined the nicotinate fer- cloned and sequenced, (ii) two chiral intermediates were discov- mentation pathway and placed the identified intermediates in an ered, and (iii) three enzymes were found, completing the hitherto enzymatic framework. unknown part of the pathway. Nicotinate dehydrogenase, a (non- The nicotinate dehydrogenase contains [2Fe-2S] clusters (15), selenocysteine) selenium-containing four-subunit enzyme, is en- FAD and molybdopterin cytosine dinucleotide (16), and has an coded by ndhF (FAD subunit), ndhS (2 x [2Fe-2S] subunit), and by unusual subunit composition [50, 37, 33, and 23 kDa (17)]. It has the ndhL͞ndhM genes. In contrast to all enzymes of the xanthine labile (nonselenocysteine) selenium (18) also identified in pu- dehydrogenase family, the latter two encode a two-subunit mo- rine dehydrogenase from Clostridium purinolyticum and xanthine lybdopterin protein. -
Supplementary Informations SI2. Supplementary Table 1
Supplementary Informations SI2. Supplementary Table 1. M9, soil, and rhizosphere media composition. LB in Compound Name Exchange Reaction LB in soil LBin M9 rhizosphere H2O EX_cpd00001_e0 -15 -15 -10 O2 EX_cpd00007_e0 -15 -15 -10 Phosphate EX_cpd00009_e0 -15 -15 -10 CO2 EX_cpd00011_e0 -15 -15 0 Ammonia EX_cpd00013_e0 -7.5 -7.5 -10 L-glutamate EX_cpd00023_e0 0 -0.0283302 0 D-glucose EX_cpd00027_e0 -0.61972444 -0.04098397 0 Mn2 EX_cpd00030_e0 -15 -15 -10 Glycine EX_cpd00033_e0 -0.0068175 -0.00693094 0 Zn2 EX_cpd00034_e0 -15 -15 -10 L-alanine EX_cpd00035_e0 -0.02780553 -0.00823049 0 Succinate EX_cpd00036_e0 -0.0056245 -0.12240603 0 L-lysine EX_cpd00039_e0 0 -10 0 L-aspartate EX_cpd00041_e0 0 -0.03205557 0 Sulfate EX_cpd00048_e0 -15 -15 -10 L-arginine EX_cpd00051_e0 -0.0068175 -0.00948672 0 L-serine EX_cpd00054_e0 0 -0.01004986 0 Cu2+ EX_cpd00058_e0 -15 -15 -10 Ca2+ EX_cpd00063_e0 -15 -100 -10 L-ornithine EX_cpd00064_e0 -0.0068175 -0.00831712 0 H+ EX_cpd00067_e0 -15 -15 -10 L-tyrosine EX_cpd00069_e0 -0.0068175 -0.00233919 0 Sucrose EX_cpd00076_e0 0 -0.02049199 0 L-cysteine EX_cpd00084_e0 -0.0068175 0 0 Cl- EX_cpd00099_e0 -15 -15 -10 Glycerol EX_cpd00100_e0 0 0 -10 Biotin EX_cpd00104_e0 -15 -15 0 D-ribose EX_cpd00105_e0 -0.01862144 0 0 L-leucine EX_cpd00107_e0 -0.03596182 -0.00303228 0 D-galactose EX_cpd00108_e0 -0.25290619 -0.18317325 0 L-histidine EX_cpd00119_e0 -0.0068175 -0.00506825 0 L-proline EX_cpd00129_e0 -0.01102953 0 0 L-malate EX_cpd00130_e0 -0.03649016 -0.79413596 0 D-mannose EX_cpd00138_e0 -0.2540567 -0.05436649 0 Co2 EX_cpd00149_e0 -
Supplementary Information
Supplementary Information Laboratory cultivation of acidophilic nanoorganisms. Physiological and bioinformatic dissection of a stable laboratory co-culture. Susanne Krause [1], Andreas Bremges [3,4], Philipp C. Münch [3,5], Alice C. McHardy [3] and Johannes Gescher* [1,2] [1] Department of Applied Biology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany [2] Institute for Biological Interfaces, Karlsruhe Institute of Technology (KIT), Eggenstein- Leopoldshafen, Germany [3] Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany [4] German Center for Infection Research (DZIF), partner site Hannover-Braunschweig, Braunschweig, Germany [5] Max von Pettenkofer-Institute of Hygiene and Medical Microbiology, Ludwig-Maximilians- University of Munich, Munich, Germany SI Materials and Methods Quantification of cells using quantitative PCR The target sequences were amplified by PCR from genomic DNA of the enrichment cultures using primers see table S8. The amplified fragments contained overlapping regions as well as a BamHI site at the 5’ end and a SacI site at the 3’ end. Using the overlaps, the fragments were combined and cloned via the added restrictions sites into plasmid pAH95 1. Integration in the genome of E. coli DH5alphaZ1 was conducted as described before 1. For standard curve design, serial dilutions of E. coli DH5alphaZ1 cells containing the merged 23S target sequences of the ARMAN und Thermoplasmatales enrichments were prepared and cells were counted in a Neubauer counting chamber (Marienfeld, Lauda-Königshofen, Germany). DNA of the dilution series as well as of enrichment-cultures was extracted using the innuSPEED soil DNA kit (Analytic Jena, Jena, Germany) with minor modifications to the manufacturer´s instructions. -
SI Appendix Index 1
SI Appendix Index Calculating chemical attributes using EC-BLAST ................................................................................ 2 Chemical attributes in isomerase reactions ............................................................................................ 3 Bond changes …..................................................................................................................................... 3 Reaction centres …................................................................................................................................. 5 Substrates and products …..................................................................................................................... 6 Comparative analysis …........................................................................................................................ 7 Racemases and epimerases (EC 5.1) ….................................................................................................. 7 Intramolecular oxidoreductases (EC 5.3) …........................................................................................... 8 Intramolecular transferases (EC 5.4) ….................................................................................................. 9 Supporting references …....................................................................................................................... 10 Fig. S1. Overview …............................................................................................................................ -
Supplemental Table 7. Every Significant Association
Supplemental Table 7. Every significant association between an individual covariate and functional group (assigned to the KO level) as determined by CPGLM regression analysis. Variable Unit RelationshipLabel See also CBCL Aggressive Behavior K05914 + CBCL Emotionally Reactive K05914 + CBCL Externalizing Behavior K05914 + K15665 K15658 CBCL Total K05914 + K15660 K16130 KO: E1.13.12.7; photinus-luciferin 4-monooxygenase (ATP-hydrolysing) [EC:1.13.12.7] :: PFAMS: AMP-binding enzyme; CBQ Inhibitory Control K05914 - K12239 K16120 Condensation domain; Methyltransferase domain; Thioesterase domain; AMP-binding enzyme C-terminal domain LEC Family Separation/Social Services K05914 + K16129 K16416 LEC Poverty Related Events K05914 + K16124 LEC Total K05914 + LEC Turmoil K05914 + CBCL Aggressive Behavior K15665 + CBCL Anxious Depressed K15665 + CBCL Emotionally Reactive K15665 + K05914 K15658 CBCL Externalizing Behavior K15665 + K15660 K16130 KO: K15665, ppsB, fenD; fengycin family lipopeptide synthetase B :: PFAMS: Condensation domain; AMP-binding enzyme; CBCL Total K15665 + K12239 K16120 Phosphopantetheine attachment site; AMP-binding enzyme C-terminal domain; Transferase family CBQ Inhibitory Control K15665 - K16129 K16416 LEC Poverty Related Events K15665 + K16124 LEC Total K15665 + LEC Turmoil K15665 + CBCL Aggressive Behavior K11903 + CBCL Anxiety Problems K11903 + CBCL Anxious Depressed K11903 + CBCL Depressive Problems K11903 + LEC Turmoil K11903 + MODS: Type VI secretion system K01220 K01058 CBCL Anxiety Problems K11906 + CBCL Depressive -
Loss of Quaternary Structure Is Associated with Rapid Sequence Divergence in the OSBS Family
Loss of quaternary structure is associated with rapid sequence divergence in the OSBS family Denis Odokonyeroa, Ayano Sakaib, Yury Patskovskyc, Vladimir N. Malashkevichc, Alexander A. Fedorovc, Jeffrey B. Bonannoc, Elena V. Fedorovc, Rafael Toroc, Rakhi Agarwald, Chenxi Wanga, Nicole D. S. Ozerovaa, Wen Shan Yewe, J. Michael Sauderf, Subramanyam Swaminathand, Stephen K. Burleyg,h,i,j,k, Steven C. Almoc,l, and Margaret E. Glasnera,1 aDepartment of Biochemistry and Biophysics, Texas A&M University, College Station, TX 77843-2128; bInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Departments of cBiochemistry and lPhysiology and Biophysics, Albert Einstein College of Medicine, Bronx, NY 10461; dBiosciences Department, Brookhaven National Laboratory, Upton, NY 11973; eDepartment of Biochemistry, National University of Singapore, Singapore 117597; fLilly Biotechnology Center, San Diego, CA 92121; gBioMaPS Institute for Quantitative Biology, hResearch Collaboratory for Structural Bioinformatics Protein Data Bank, iCenter for Integrative Proteomics Research, jRutgers Cancer Institute of New Jersey, and kDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ 08854-8076 Edited by Douglas L. Theobald, Brandeis University, Waltham, MA, and accepted by the Editorial Board May 2, 2014 (received for review October 3, 2013) The rate of protein evolution is determined by a combination of OSBS family is much faster than other families in the enolase su- selective pressure on protein function and biophysical constraints perfamily. For example, the average pairwise amino acid sequence on protein folding and structure. Determining the relative con- identity of OSBSs from 66 species is 26%, and the most divergent tributions of these properties is an unsolved problem in molecular family members share <15% identity.