8-Barrel Enzymes John a Gerlt and Frank M Raushely
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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. -
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. -
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 -
Folding-TIM Barrel
Protein Folding Practical September 2011 Folding up the TIM barrel Preliminary Examine the parallel beta barrel that you constructed, noting the stagger of the strands that was needed to connect the ends of the 8-stranded parallel beta sheet into the 8-stranded beta barrel. Notice that the stagger dictates which side of the sheet is on the inside and which is on the outside. This will be key information in folding the complete TIM linear peptide into the TIM barrel. Assembling the full linear peptide 1. Make sure the white beta strands are extended correctly, and the 8 yellow helices (with the green loops at each end) are correctly folded into an alpha helix (right handed with H-bonds to the 4th ahead in the chain). 2. starting with a beta strand connect an alpha helix and green loop to make the blue-red connecting peptide bond. Making sure that you connect the carbonyl (red) end of the beta strand to the amino (blue) end of the loop-helix-loop. Secure the just connected peptide bond bond with a twist-tie as shown. 3. complete step 2 for all beta strand/loop-helix-loop pairs, working in parallel with your partners 4. As pairs are completed attach the carboxy end of the strand- loop-helix-loop to the amino end of the next strand-loop-helix-loop module and secure the new peptide bond with a twist-tie as before. Repeat until the full linear TIM polypeptide chain is assembled. Make sure all strands and helices are still in the correct conformations. -
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. -
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 -
Functional and Physiological Discovery in the Mannonate Dehydratase Subgroup of the Enolase Superfamily
FUNCTIONAL AND PHYSIOLOGICAL DISCOVERY IN THE MANNONATE DEHYDRATASE SUBGROUP OF THE ENOLASE SUPERFAMILY BY DANIEL JOSEPH WICHELECKI DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biochemistry in the Graduate College of the University of Illinois at Urbana-Champaign, 2014 Urbana, Illinois Doctoral Committee: Professor John Gerlt, Chair Professor John Cronan Professor Scott Silverman Professor Wilfred van der Donk ABSTRACT In the current post-genomic world, the exponential amassing of protein sequences is overwhelming the scientific community’s ability to experimentally assign each protein’s function. The use of automated, homology-based annotations has allowed a reprieve from this efflux of data, but has led to widespread misannotation and nonannotation in protein sequence databases. This dissertation details the functional and physiological characterization of the mannonate dehydratase subgroup (ManD) of the enolase superfamily (ENS). The outcome affirms the dangers of homology-based annotations while discovering novel metabolic pathways. Furthermore, the experimental verification of these pathways ( in vitro and in vivo ) has provided a platform to test the general strategies for improved functional and metabolic characterization being developed by the Enzyme Function Initiative (EFI). Prior to this study, one member of the ManD subgroup had been characterized and was shown to dehydrate D-mannonate to 2-keto-3-deoxy-D-gluconate. Forty-two additional members of the ManD, selected from across the sequence space of the subgroup, were screened for activity and kinetic constants were determined. The members of the once isofunctional subgroup were found to differ in both catalytic efficiency and substrate specificity: 1) high 3 4 -1 -1 efficiency (k cat /K M = 10 to 10 M s ) dehydration of D-mannonate, 2) low efficiency (k cat /K M = 10 1 to 10 2 M-1s-1) dehydration of D-mannonate and/or D-gluconate, and 3) no-activity with either D-mannonate or D-gluconate (or any other acid sugar tested). -
Tertiary Structure
Comments Structural motif v sequence motif polyproline (“PXXP”) motif for SH3 binding “RGD” motif for integrin binding “GXXXG” motif within the TM domain of membrane protein Most common type I’ beta turn sequences: X – (N/D/G)G – X Most common type II’ beta turn sequences: X – G(S/T) – X 1 Putting it together Alpha helices and beta sheets are not proteins—only marginally stable by themselves … Extremely small “proteins” can’t do much 2 Tertiary structure • Concerns with how the secondary structure units within a single polypeptide chain associate with each other to give a three- dimensional structure • Secondary structure, super secondary structure, and loops come together to form “domains”, the smallest tertiary structural unit • Structural domains (“domains”) usually contain 100 – 200 amino acids and fold stably. • Domains may be considered to be connected units which are to varying extents independent in terms of their structure, function and folding behavior. Each domain can be described by its fold, i.e. how the secondary structural elements are arranged. • Tertiary structure also includes the way domains fit together 3 Domains are modular •Because they are self-stabilizing, domains can be swapped both in nature and in the laboratory PI3 kinase beta-barrel GFP Branden & Tooze 4 fluorescence localization experiment Chimeras Recombinant proteins are often expressed and purified as fusion proteins (“chimeras”) with – glutathione S-transferase – maltose binding protein – or peptide tags, e.g. hexa-histidine, FLAG epitope helps with solubility, stability, and purification 5 Structural Classification All classifications are done at the domain level In many cases, structural similarity implies a common evolutionary origin – structural similarity without evolutionary relationship is possible – but no structural similarity means no evolutionary relationship Each domain has its corresponding “fold”, i.e. -
Supplementary Table S1. the Key Enzymes for Autotrophic Growth in C
Electronic Supplementary Material (ESI) for Metallomics. This journal is © The Royal Society of Chemistry 2015 Supplementary Table S1. The key enzymes for autotrophic growth in C. metallidurans Name Rmet-number Spec. Predicted Mass, (kDa) Determined Mass, (kDa) Activity HOS Rmet_1522 to Rmet_1525 28.7 65.2, 25.4, 23.4, 52.8 = 166.8 62.4±1.8, 26.4±1.3, 24.0±0.6, 54.1±2.5, =235±20a HOP Rmet_1297, Rmet_1298, 67.0 69.0 + 38.6 = 108 148±24a CAX Rmet_1500, Rmet_1501 2.82 8 * (13.6 + 52.5) = 529 475±36a PRK Rmet_1512 0.994 8 * 32.4 = 259 256±11a aMean value of masses determined by S300 size exclusion chromatography and sucrose gradient centrifugation. HOS, NAD-reducing soluble hydrogenase; HOP, membrane-bound hydrogenase; CAX, ribulose-bis-phosphate carboxylase/oxygenase; PRK, phosphoribulokinase. Specific activity in U/mg protein. Supplementary Table S2. Genes expressed differently in AE104 compared to CH34 wild typea Operon Region Name Gene Q D Description UP Op1321r Rmet_4594 zntA 1.72 2.88 Q1LEH0 Heavy metal translocating P -type ATPase Op1322f Rmet_4595 czcI2 2.03 2.92 Q1LEG9 Putative uncharacterized protein Op1322f Rmet_4596 czcC2 23.34 5.36 Q1LEG8 Outer membrane efflux protein Op1322f Rmet_4597 czcB2' 15.36 9.68 Q1LEG7 Secretion protein HlyD Op0075f Rmet_0260 - 2.31 2.48 Q1LRT0 Putative transmembrane protein Op0075f Rmet_0261 coxB 2.08 2.49 Q1LRS9 Cytochrome c oxidase subunit 2 Adjacent to CMGI-7 Op0335f Rmet_1171 tnpA 7.03 21.74 Q9F8S6 Transposase (Transposase, IS4 family) CMGI-2 Op0362r Rmet_1251 tnp 4.08 0.61 Q1LNY9 Putative uncharacterized -
BMC Structural Biology Biomed Central
BMC Structural Biology BioMed Central Research article Open Access Natural history of S-adenosylmethionine-binding proteins Piotr Z Kozbial*1 and Arcady R Mushegian1,2 Address: 1Stowers Institute for Medical Research, 1000 E. 50th St., Kansas City, MO 64110, USA and 2Department of Microbiology, Molecular Genetics, and Immunology, University of Kansas Medical Center, Kansas City, Kansas 66160, USA Email: Piotr Z Kozbial* - [email protected]; Arcady R Mushegian - [email protected] * Corresponding author Published: 14 October 2005 Received: 21 July 2005 Accepted: 14 October 2005 BMC Structural Biology 2005, 5:19 doi:10.1186/1472-6807-5-19 This article is available from: http://www.biomedcentral.com/1472-6807/5/19 © 2005 Kozbial and Mushegian; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: S-adenosylmethionine is a source of diverse chemical groups used in biosynthesis and modification of virtually every class of biomolecules. The most notable reaction requiring S- adenosylmethionine, transfer of methyl group, is performed by a large class of enzymes, S- adenosylmethionine-dependent methyltransferases, which have been the focus of considerable structure-function studies. Evolutionary trajectories of these enzymes, and especially of other classes of S-adenosylmethionine-binding proteins, nevertheless, remain poorly understood. We addressed this issue by computational comparison of sequences and structures of various S- adenosylmethionine-binding proteins. Results: Two widespread folds, Rossmann fold and TIM barrel, have been repeatedly used in evolution for diverse types of S-adenosylmethionine conversion.