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Journal articles on the topic 'Enzyme-Substrate Interactions'

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Published: 4 June 2021
Last updated: 15 February 2022

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1

Kumar, Vinay, and K. K. Kannan. "Enzyme-Substrate Interactions." Journal of Molecular Biology 241, no. 2 (August 1994): 226–32. http://dx.doi.org/10.1006/jmbi.1994.1491.

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2

MILNER-WHITE, E. JAMES. "Displaying enzyme-substrate interactions." Biochemical Society Transactions 17, no. 4 (August 1, 1989): 681–82. http://dx.doi.org/10.1042/bst0170681.

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3

Lee, Ida, Barbara R. Evans, Lynette M. Lane, and Jonathan Woodward. "Substrate-enzyme interactions in cellulase systems." Bioresource Technology 58, no. 2 (November 1996): 163–69. http://dx.doi.org/10.1016/s0960-8524(96)00095-8.

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4

Guo, Qing, Yufan He, and H. Peter Lu. "Manipulating and probing enzymatic conformational fluctuations and enzyme–substrate interactions by single-molecule FRET-magnetic tweezers microscopy." Phys. Chem. Chem. Phys. 16, no. 26 (2014): 13052–58. http://dx.doi.org/10.1039/c4cp01454e.

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To investigate the critical role of the enzyme–substrate interactions in enzymatic reactions, the enzymatic conformation and enzyme–substrate interaction at a single-molecule level are manipulated by magnetic tweezers, and the impact of the manipulation on enzyme–substrate interactions are simultaneously probed by single-molecule FRET spectroscopy.
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5

Guerrier-Takada, C., N. Lumelsky, and S. Altman. "Specific interactions in RNA enzyme-substrate complexes." Science 246, no. 4937 (December 22, 1989): 1578–84. http://dx.doi.org/10.1126/science.2480641.

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6

Li, Huiying, and Thomas Poulos. "Crystallization of Cytochromes P450 and Substrate-Enzyme Interactions." Current Topics in Medicinal Chemistry 4, no. 16 (December 1, 2004): 1789–802. http://dx.doi.org/10.2174/1568026043387205.

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7

Freitag, Ruth. "Utilization of enzyme–substrate interactions in analytical chemistry." Journal of Chromatography B: Biomedical Sciences and Applications 722, no. 1-2 (February 1999): 279–301. http://dx.doi.org/10.1016/s0378-4347(98)00507-6.

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8

Bretz, Stacey Lowery, and Kimberly J. Linenberger. "Development of the enzyme-substrate interactions concept inventory." Biochemistry and Molecular Biology Education 40, no. 4 (June 18, 2012): 229–33. http://dx.doi.org/10.1002/bmb.20622.

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9

Peluso, Carolyn E., David Umulis, Young-Jun Kim, Michael B. O'Connor, and Mihaela Serpe. "Shaping BMP Morphogen Gradients through Enzyme-Substrate Interactions." Developmental Cell 21, no. 2 (August 2011): 375–83. http://dx.doi.org/10.1016/j.devcel.2011.06.025.

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10

Suzuki, T., Y. Zhang, T. Koyama, and K. Kurihara. "1P093 Specific Interactions between Enzyme-Substrate Complexes Depending on Substrate Chain Length." Seibutsu Butsuri 44, supplement (2004): S53. http://dx.doi.org/10.2142/biophys.44.s53_1.

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11

Wade, R. C. "Simulation of enzyme-substrate interactions: the diffusional encounter step." Acta Biochimica Polonica 42, no. 4 (December 31, 1995): 419–25. http://dx.doi.org/10.18388/abp.1995_4895.

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Enzymes are targets for structure-based redesign and drug design. One potentially important design strategy is to create molecules--enzymes and ligands--with desired diffusional encounter properties. Rates of diffusive bimolecular encounter can be calculated by Brownian dynamics simulation. This methodology and its application to study the factors influencing the rates of diffusion-influenced enzymes are described here.
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12

Lopes, José L. S., Thatyane M. Nobre, Eduardo M. Cilli, Leila M. Beltramini, Ana P. U. Araújo, and B. A. Wallace. "Deconstructing the DGAT1 enzyme: Binding sites and substrate interactions." Biochimica et Biophysica Acta (BBA) - Biomembranes 1838, no. 12 (December 2014): 3145–52. http://dx.doi.org/10.1016/j.bbamem.2014.08.017.

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13

Szklarz, Grazyna D., and Mark D. Paulsen. "Molecular Modeling of Cytochrome P450 1A1: Enzyme-Substrate Interactions and Substrate Binding Affinities." Journal of Biomolecular Structure and Dynamics 20, no. 2 (October 2002): 155–62. http://dx.doi.org/10.1080/07391102.2002.10506831.

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14

Burns, Kristi L., and Sheldon W. May. "Separation methods applicable to the evaluation of enzyme–inhibitor and enzyme–substrate interactions." Journal of Chromatography B 797, no. 1-2 (November 2003): 175–90. http://dx.doi.org/10.1016/j.jchromb.2003.08.038.

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15

Klotz, Irving M. "Ligand–receptor interactions: facts and fantasies." Quarterly Reviews of Biophysics 18, no. 3 (August 1985): 227–59. http://dx.doi.org/10.1017/s0033583500000354.

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Except when radiation participates, all biological activities involve contact interactions between constituent reactants. At the molecular level, if one of the participants is smaller than its complementary partner, the former is usually designated the ‘ligand’ and the latter the ‘receptor’. Thus in an enzyme–substrate complex, the substrate is the ligand, the enzyme is the receptor. In immunological interactions, the ligand is the hapten or antigen, the receptor is the immunoglobulin. Neurotransmitters or hormones are effector ligands when they are bound to receptor sites at synapses or on cell membranes.
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16

Pohl, Jan, and Ben M. Dunn. "Secondary enzyme-substrate interactions: kinetic evidence for ionic interactions between substrate side chains and the pepsin active site." Biochemistry 27, no. 13 (June 28, 1988): 4827–34. http://dx.doi.org/10.1021/bi00413a037.

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17

Götte, Matthias, Jason W. Rausch, Bruno Marchand, Stefan Sarafianos, and Stuart F. J. Le Grice. "Reverse transcriptase in motion: Conformational dynamics of enzyme–substrate interactions." Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics 1804, no. 5 (May 2010): 1202–12. http://dx.doi.org/10.1016/j.bbapap.2009.07.020.

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18

Lopes, Jose L. S., Leila M. Beltramini, Bonnie A. Wallace, and Ana P. U. Araujo. "Deconstructing the DGAT1 Enzyme: Membrane Interactions at Substrate Binding Sites." PLOS ONE 10, no. 2 (February 26, 2015): e0118407. http://dx.doi.org/10.1371/journal.pone.0118407.

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19

Venanzi, Carol A., Harel Weinstein, Georgina Corongiu, and Enrico Clementi. "The solvent effect in enzyme-substrate interactions: Models of carboxypeptidase." International Journal of Quantum Chemistry 22, S9 (June 19, 2009): 355–65. http://dx.doi.org/10.1002/qua.560220733.

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20

BACQUET, R. J., and J. A. McCAMMON. "Salt Effects on Enzyme-Substrate Interactions by Monte Carlo Simulation." Annals of the New York Academy of Sciences 482, no. 1 Computer Simu (December 1986): 245–47. http://dx.doi.org/10.1111/j.1749-6632.1986.tb20955.x.

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21

Natchev, Ivan A. "SYNTHESIS AND ENZYME-SUBSTRATE INTERACTIONS OFN-PHOSPHINO-, PHOSPHONOMETHYLGLYCINE ETHYL ESTERS." Phosphorous and Sulfur and the Related Elements 37, no. 3-4 (June 1988): 133–41. http://dx.doi.org/10.1080/03086648808079028.

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22

Pontoni, Gabriele, Caterina Manna, Antonio Salluzzo, Luisa del Piano, Patrizia Galletti, Mario De Rosa, and Vincenzo Zappia. "Studies on enzyme-substrate interactions of cholinephosphotransferase from rat liver." Biochimica et Biophysica Acta (BBA) - Lipids and Lipid Metabolism 836, no. 2 (September 1985): 222–32. http://dx.doi.org/10.1016/0005-2760(85)90070-0.

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23

Rotili, Dante, Mikael Altun, Refaat B. Hamed, Christoph Loenarz, Armin Thalhammer, Richard J. Hopkinson, Ya-Min Tian, et al. "Photoactivable peptides for identifying enzyme–substrate and protein–protein interactions." Chem. Commun. 47, no. 5 (2011): 1488–90. http://dx.doi.org/10.1039/c0cc04457a.

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24

McAllister, T. E., T. L. Yeh, M. I. Abboud, I. K. H. Leung, E. S. Hookway, O. N. F. King, B. Bhushan, et al. "Non-competitive cyclic peptides for targeting enzyme–substrate complexes." Chemical Science 9, no. 20 (2018): 4569–78. http://dx.doi.org/10.1039/c8sc00286j.

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25

KITAOKU, Yoshihito, and Takayuki OHNUMA. "Thermodynamic Analysis of Enzyme–Substrate Interactions by Isothermal Titration Calorimetry (ITC)." KAGAKU TO SEIBUTSU 53, no. 12 (2015): 834–42. http://dx.doi.org/10.1271/kagakutoseibutsu.53.834.

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26

Linenberger, Kimberly J., and Stacey Lowery Bretz. "Biochemistry students' ideas about shape and charge in enzyme-substrate interactions." Biochemistry and Molecular Biology Education 42, no. 3 (February 17, 2014): 203–12. http://dx.doi.org/10.1002/bmb.20776.

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27

Linenberger, Kimberly J., and Stacey Lowery Bretz. "Biochemistry Students' Ideas About Shape and Charge in Enzyme-Substrate Interactions." Biochemistry and Molecular Biology Education 42, no. 4 (July 8, 2014): 366–67. http://dx.doi.org/10.1002/bmb.20804.

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28

Versées, Wim, Klaas Decanniere, Els Van Holsbeke, Neel Devroede, and Jan Steyaert. "Enzyme-Substrate Interactions in the Purine-specific Nucleoside Hydrolase fromTrypanosoma vivax." Journal of Biological Chemistry 277, no. 18 (February 19, 2002): 15938–46. http://dx.doi.org/10.1074/jbc.m111735200.

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29

Ozbil, Mehmet, Arghya Barman, Ram Prasad Bora, and Rajeev Prabhakar. "Computational Insights into Dynamics of Protein Aggregation and Enzyme–Substrate Interactions." Journal of Physical Chemistry Letters 3, no. 23 (November 14, 2012): 3460–69. http://dx.doi.org/10.1021/jz301597k.

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30

Roopesh, Krishnankutty, Joseph Abhilash, M. Haridas, Abdulhameed Sabu, Perraud Gaime Isabelle, Sevastianos Roussos, and Christopher Augur. "Dioxygenase fromAspergillus fumigatusMC8: molecular modelling andin silicostudies on enzyme–substrate interactions." Molecular Simulation 38, no. 2 (February 2012): 144–51. http://dx.doi.org/10.1080/08927022.2011.608672.

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31

Ferrall-Fairbanks, Meghan C., Chris A. Kieslich, and Manu O. Platt. "Reassessing enzyme kinetics: Considering protease-as-substrate interactions in proteolytic networks." Proceedings of the National Academy of Sciences 117, no. 6 (January 24, 2020): 3307–18. http://dx.doi.org/10.1073/pnas.1912207117.

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Enzymes are catalysts in biochemical reactions that, by definition, increase rates of reactions without being altered or destroyed. However, when that enzyme is a protease, a subclass of enzymes that hydrolyze other proteins, and that protease is in a multiprotease system, protease-as-substrate dynamics must be included, challenging assumptions of enzyme inertness, shifting kinetic predictions of that system. Protease-on-protease inactivating hydrolysis can alter predicted protease concentrations used to determine pharmaceutical dosing strategies. Cysteine cathepsins are proteases capable of cathepsin cannibalism, where one cathepsin hydrolyzes another with substrate present, and misunderstanding of these dynamics may cause miscalculations of multiple proteases working in one proteolytic network of interactions occurring in a defined compartment. Once rates for individual protease-on-protease binding and catalysis are determined, proteolytic network dynamics can be explored using computational models of cooperative/competitive degradation by multiple proteases in one system, while simultaneously incorporating substrate cleavage. During parameter optimization, it was revealed that additional distraction reactions, where inactivated proteases become competitive inhibitors to remaining, active proteases, occurred, introducing another network reaction node. Taken together, improved predictions of substrate degradation in a multiple protease network were achieved after including reaction terms of autodigestion, inactivation, cannibalism, and distraction, altering kinetic considerations from other enzymatic systems, since enzyme can be lost to proteolytic degradation. We compiled and encoded these dynamics into an online platform (https://plattlab.shinyapps.io/catKLS/) for individual users to test hypotheses of specific perturbations to multiple cathepsins, substrates, and inhibitors, and predict shifts in proteolytic network reactions and system dynamics.
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32

Roberts, Gordon C. K. "The other kind of biological NMR—Studies of enzyme-substrate interactions." Neurochemical Research 21, no. 9 (September 1996): 1117–24. http://dx.doi.org/10.1007/bf02532422.

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33

BENÍTEZ, María J., Gerardo MIER, Fernando BRIONES, Francisco J. MORENO, and Juan S. JIMÉNEZ. "A surface-plasmon-resonance analysis of polylysine interactions with a peptide substrate of protein kinase CK2 and with the enzyme." Biochemical Journal 324, no. 3 (June 15, 1997): 987–94. http://dx.doi.org/10.1042/bj3240987.

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The mechanism of protein kinase CK2 (CK2) activity stimulation by polylysine has been studied by surface plasmon resonance (SPR). The kinetics of the polylysine interaction with a peptide substrate of the enzyme, and with the enzyme itself, have been investigated. A peptide containing a threonine (T) residue surrounded by a cluster of negatively charged acidic [arginine (R) and glutamic acid (E)] residues, RRREEETEEE, and specifically phosphorylated by CK2, was selected. Polylysine interacts with both the enzyme and the peptide substrate. The rate constant, the stoichiometry of the polylysine–peptide substrate interaction and the kinetic parameters of the stimulated enzyme were used to calculate the polylysine-dependent stimulation of CK2. The results are in agreement with experimentally determined polylysine-dependent stimulation. The polylysine–enzyme interaction is too slow to account for enzyme stimulation. The behaviour of polylysine is not reproduced by the polyamine spermine. The results are consistent with a substrate-mediated mechanism of CK2 stimulation by polylysine, and they suggest that the CK2 stimulation by polyamines occurs by a different mechanism.
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34

Kadirvelraj, Renuka, Jeong-Yeh Yang, Justin H. Sanders, Lin Liu, Annapoorani Ramiah, Pradeep Kumar Prabhakar, Geert-Jan Boons, Zachary A. Wood, and Kelley W. Moremen. "Human N-acetylglucosaminyltransferase II substrate recognition uses a modular architecture that includes a convergent exosite." Proceedings of the National Academy of Sciences 115, no. 18 (April 16, 2018): 4637–42. http://dx.doi.org/10.1073/pnas.1716988115.

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Asn-linked oligosaccharides are extensively modified during transit through the secretory pathway, first by trimming of the nascent glycan chains and subsequently by initiating and extending multiple oligosaccharide branches from the trimannosyl glycan core. Trimming and branching pathway steps are highly ordered and hierarchal based on the precise substrate specificities of the individual biosynthetic enzymes. A key committed step in the synthesis of complex-type glycans is catalyzed by N-acetylglucosaminyltransferase II (MGAT2), an enzyme that generates the second GlcNAcβ1,2- branch from the trimannosyl glycan core using UDP-GlcNAc as the sugar donor. We determined the structure of human MGAT2 as a Mn2+-UDP donor analog complex and as a GlcNAcMan3GlcNAc2-Asn acceptor complex to reveal the structural basis for substrate recognition and catalysis. The enzyme exhibits a GT-A Rossmann-like fold that employs conserved divalent cation-dependent substrate interactions with the UDP-GlcNAc donor. MGAT2 interactions with the extended glycan acceptor are distinct from other related glycosyltransferases. These interactions are composed of a catalytic subsite that binds the Man-α1,6- monosaccharide acceptor and a distal exosite pocket that binds the GlcNAc-β1,2Man-α1,3Manβ- substrate “recognition arm.” Recognition arm interactions are similar to the enzyme–substrate interactions for Golgi α-mannosidase II, a glycoside hydrolase that acts just before MGAT2 in the Asn-linked glycan biosynthetic pathway. These data suggest that substrate binding by MGAT2 employs both conserved and convergent catalytic subsite modules to provide substrate selectivity and catalysis. More broadly, the MGAT2 active-site architecture demonstrates how glycosyltransferases create complementary modular templates for regiospecific extension of glycan structures in mammalian cells.
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35

Guo, Qing, Yufan He, and H. Peter Lu. "Interrogating the activities of conformational deformed enzyme by single-molecule fluorescence-magnetic tweezers microscopy." Proceedings of the National Academy of Sciences 112, no. 45 (October 28, 2015): 13904–9. http://dx.doi.org/10.1073/pnas.1506405112.

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Characterizing the impact of fluctuating enzyme conformation on enzymatic activity is critical in understanding the structure–function relationship and enzymatic reaction dynamics. Different from studying enzyme conformations under a denaturing condition, it is highly informative to manipulate the conformation of an enzyme under an enzymatic reaction condition while monitoring the real-time enzymatic activity changes simultaneously. By perturbing conformation of horseradish peroxidase (HRP) molecules using our home-developed single-molecule total internal reflection magnetic tweezers, we successfully manipulated the enzymatic conformation and probed the enzymatic activity changes of HRP in a catalyzed H2O2–amplex red reaction. We also observed a significant tolerance of the enzyme activity to the enzyme conformational perturbation. Our results provide a further understanding of the relation between enzyme behavior and enzymatic conformational fluctuation, enzyme–substrate interactions, enzyme–substrate active complex formation, and protein folding–binding interactions.
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36

Sihi, Debjani, Stefan Gerber, Patrick W. Inglett, and Kanika Sharma Inglett. "Comparing models of microbial–substrate interactions and their response to warming." Biogeosciences 13, no. 6 (March 21, 2016): 1733–52. http://dx.doi.org/10.5194/bg-13-1733-2016.

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Abstract. Recent developments in modelling soil organic carbon decomposition include the explicit incorporation of enzyme and microbial dynamics. A characteristic of these models is a positive feedback between substrate and consumers, which is absent in traditional first-order decay models. With sufficiently large substrate, this feedback allows an unconstrained growth of microbial biomass. We explore mechanisms that curb unrestricted microbial growth by including finite potential sites where enzymes can bind and by allowing microbial scavenging for enzymes. We further developed a model where enzyme synthesis is not scaled to microbial biomass but associated with a respiratory cost and microbial population adjusts enzyme production in order to optimise their growth. We then tested short- and long-term responses of these models to a step increase in temperature and find that these models differ in the long-term when short-term responses are harmonised. We show that several mechanisms, including substrate limitation, variable production of microbial enzymes, and microbes feeding on extracellular enzymes eliminate oscillations arising from a positive feedback between microbial biomass and depolymerisation. The model where enzyme production is optimised to yield maximum microbial growth shows the strongest reduction in soil organic carbon in response to warming, and the trajectory of soil carbon largely follows that of a first-order decomposition model. Modifications to separate growth and maintenance respiration generally yield short-term differences, but results converge over time because microbial biomass approaches a quasi-equilibrium with the new conditions of carbon supply and temperature.
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37

Grabarczyk, Daniel B., Paul E. Chappell, Steven Johnson, Lukas S. Stelzl, Susan M. Lea, and Ben C. Berks. "Structural basis for specificity and promiscuity in a carrier protein/enzyme system from the sulfur cycle." Proceedings of the National Academy of Sciences 112, no. 52 (December 11, 2015): E7166—E7175. http://dx.doi.org/10.1073/pnas.1506386112.

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The bacterial Sox (sulfur oxidation) pathway is an important route for the oxidation of inorganic sulfur compounds. Intermediates in the Sox pathway are covalently attached to the heterodimeric carrier protein SoxYZ through conjugation to a cysteine on a protein swinging arm. We have investigated how the carrier protein shuttles intermediates between the enzymes of the Sox pathway using the interaction between SoxYZ and the enzyme SoxB as our model. The carrier protein and enzyme interact only weakly, but we have trapped their complex by using a “suicide enzyme” strategy in which an engineered cysteine in the SoxB active site forms a disulfide bond with the incoming carrier arm cysteine. The structure of this trapped complex, together with calorimetric data, identifies sites of protein–protein interaction both at the entrance to the enzyme active site tunnel and at a second, distal, site. We find that the enzyme distinguishes between the substrate and product forms of the carrier protein through differences in their interaction kinetics and deduce that this behavior arises from substrate-specific stabilization of a conformational change in the enzyme active site. Our analysis also suggests how the carrier arm-bound substrate group is able to outcompete the adjacent C-terminal carboxylate of the carrier arm for binding to the active site metal ions. We infer that similar principles underlie carrier protein interactions with other enzymes of the Sox pathway.
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38

Sihi, D., S. Gerber, P. W. Inglett, and K. S. Inglett. "Comparing models of microbial-substrate interactions and their response to warming." Biogeosciences Discussions 12, no. 13 (July 10, 2015): 10857–97. http://dx.doi.org/10.5194/bgd-12-10857-2015.

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Abstract. Recent developments in modelling soil organic carbon decomposition include the explicit incorporation of enzyme and microbial dynamics. A characteristic of these models is a positive feedback between substrate and consumers which is absent in traditional first order decay models. Under sufficient large substrate, this new feedback allows an unconstrained growth of microbial biomass. A second phenomenon incorporated in the microbial decomposition models is decreased carbon use efficiency (CUE) with increasing temperature. Here, first we analyse microbial decomposition models by parameterising changes in CUE based on the differentiation between growth and maintenance respiration. We then explore mechanisms that curb unrestricted microbial growth by including finite potential sites where enzymes can bind and by allowing microbial scavenging for enzymes. Finally, we propose a model where enzyme synthesis is associated with a respiratory cost and microbial population adjusts enzyme production in order to optimise their growth. When applying a step increase in temperature, we find fast responses that reflect adjustments to enzyme dynamics and maintenance respiration, a short-term adjustment in microbial growth, and the long-term change in carbon storage. We find that mechanisms that prevent unrestricted microbial growth lead to a similar response to warming as traditional first order decomposition models.
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39

Wolfenden, Richard. "Conformational aspects of inhibitor design: enzyme–substrate interactions in the transition state." Bioorganic & Medicinal Chemistry 7, no. 5 (May 1999): 647–52. http://dx.doi.org/10.1016/s0968-0896(98)00247-8.

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40

Neuhauser, Wilfried, Dietmar Haltrich, Klaus D. Kulbe, and Bernd Nidetzky. "Noncovalent Enzyme−Substrate Interactions in the Catalytic Mechanism of Yeast Aldose Reductase†." Biochemistry 37, no. 4 (January 1998): 1116–23. http://dx.doi.org/10.1021/bi9717800.

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41

Mulakala, Chandrika, and Peter J. Reilly. "Force calculations in automated docking: Enzyme-substrate interactions in Fusarium oxysporum Cel7B." Proteins: Structure, Function, and Bioinformatics 61, no. 3 (September 1, 2005): 590–96. http://dx.doi.org/10.1002/prot.20632.

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42

ESTELL, D. A., T. P. GRAYCAR, J. V. MILLER, D. B. POWERS, J. A. WELLS, J. P. BURNIER, and P. G. NG. "Probing Steric and Hydrophobic Effects on Enzyme-Substrate Interactions by Protein Engineering." Science 233, no. 4764 (August 8, 1986): 659–63. http://dx.doi.org/10.1126/science.233.4764.659.

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43

Tran, Lucky, R. William Broadhurst, Manuela Tosin, Andrea Cavalli, and Kira J. Weissman. "Insights into Protein-Protein and Enzyme-Substrate Interactions in Modular Polyketide Synthases." Chemistry & Biology 17, no. 7 (July 2010): 705–16. http://dx.doi.org/10.1016/j.chembiol.2010.05.017.

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44

Singh, Puneet Kumar, and Pratyoosh Shukla. "Molecular Modeling and Docking of Microbial Inulinases Towards Perceptive Enzyme–Substrate Interactions." Indian Journal of Microbiology 52, no. 3 (January 21, 2012): 373–80. http://dx.doi.org/10.1007/s12088-012-0248-0.

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45

VIPARELLI, Paolo, Francesco ALFANI, and Maria CANTARELLA. "Models for enzyme superactivity in aqueous solutions of surfactants." Biochemical Journal 344, no. 3 (December 8, 1999): 765–73. http://dx.doi.org/10.1042/bj3440765.

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Theoretical models are developed here for enzymic activity in the presence of direct micellar aggregates. An approach similar to that of Bru et al. [Bru, Sánchez-Ferrer and Garcia-Carmona (1989) Biochem. J. 259, 355-361] for reverse micelles has been adopted. The system is considered to consist of three pseudo-phases: free water, bound water and surfactant tails. The substrate concentration in each pseudo-phase is related to the total substrate concentration in the reaction medium. In the absence of interactions between the enzyme and the micelles, the model predicts either monotonically increasing or monotonically decreasing trends in the calculated reaction rate as a function of surfactant concentration. With enzyme-micelle interactions included in the formulation (by introducing an equilibrium relation between the enzyme confined in the free water and in the bound water pseudo-phases, and by allowing for different catalytic behaviours for the two forms), the calculated reaction rate can exhibit a bell-shaped dependence on surfactant concentration. The effect of the partition of enzyme and substrate is described, as is that of enzyme efficiency in the various pseudo-phases.
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46

Sueda, Shinji. "Enzyme-based protein-tagging systems for site-specific labeling of proteins in living cells." Microscopy 69, no. 3 (March 13, 2020): 156–66. http://dx.doi.org/10.1093/jmicro/dfaa011.

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Abstract Various protein-labeling methods based on the specific interactions between genetically encoded tags and synthetic probes have been proposed to complement fluorescent protein-based labeling. In particular, labeling methods based on enzyme reactions have been intensively developed by taking advantage of the highly specific interactions between enzymes and their substrates. In this approach, the peptides or proteins are genetically attached to the target proteins as a tag, and the various labels are then incorporated into the tags by enzyme reactions with the substrates carrying those labels. On the other hand, we have been developing an enzyme-based protein-labeling system distinct from the existing ones. In our system, the substrate protein is attached to the target proteins as a tag, and the labels are incorporated into the tag by post-translational modification with an enzyme carrying those labels followed by tight complexation between the enzyme and the substrate protein. In this review, I summarize the enzyme-based protein-labeling systems with a focus on several typical methods and then describe our labeling system based on tight complexation between the enzyme and the substrate protein.
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Preugschat, F., E. M. Lenches, and J. H. Strauss. "Flavivirus enzyme-substrate interactions studied with chimeric proteinases: identification of an intragenic locus important for substrate recognition." Journal of Virology 65, no. 9 (1991): 4749–58. http://dx.doi.org/10.1128/jvi.65.9.4749-4758.1991.

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48

Kim, Jong Won, Mi Young Seo, Anang Shelat, Chon Saeng Kim, Tae Woo Kwon, Hui-hua Lu, Demetri Theodore Moustakas, Jeonghoon Sun, and Jang H. Han. "Structurally Conserved Amino Acid W501 Is Required for RNA Helicase Activity but Is Not Essential for DNA Helicase Activity of Hepatitis C Virus NS3 Protein." Journal of Virology 77, no. 1 (January 1, 2003): 571–82. http://dx.doi.org/10.1128/jvi.77.1.571-582.2003.

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ABSTRACT Hepatitis C virus (HCV) is a positive-strand RNA virus that encodes a helicase required for viral replication. Although HCV does not replicate through a DNA intermediate, HCV helicase unwinds both RNA and DNA duplexes. An X-ray crystal structure of the HCV helicase complexed with (dU)8 has been solved, and the substrate-amino acids interactions within the catalytic pocket were shown. Among these, residues W501 and V432 were reported to have base stacking interactions and to be important for the unwinding function of HCV helicase. It has been hypothesized that specific interactions between the enzyme and substrate in the catalytic pocket are responsible for the substrate specificity phenotype. We therefore mutagenized W501 and V432 to investigate their role in substrate specificity in HCV helicase. Replacement of W501, but not V432, with nonaromatic residues resulted in complete loss of RNA unwinding activity, whereas DNA unwinding activity was largely unaffected. The loss of unwinding activity was fully restored in the W501F mutant, indicating that the aromatic ring is crucial for RNA helicase function. Analysis of ATPase and nucleic acid binding activities in the W501 mutant enzymes revealed that these activities are not directly responsible for the substrate specificity phenotype. Molecular modeling of the enzyme-substrate interaction at W501 revealed a putative π-facial hydrogen bond between the 2′-OH of ribose and the aromatic tryptophan ring. This evidence correlates with biochemical results suggesting that the π-facial bond may play an important role in the RNA unwinding activity of the HCV NS3 protein.
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Bell, E. T., C. LiMuti, C. L. Renz, and J. E. Bell. "Negative co-operativity in glutamate dehydrogenase. Involvement of the 2-position in glutamate in the induction of conformational changes." Biochemical Journal 225, no. 1 (January 1, 1985): 209–17. http://dx.doi.org/10.1042/bj2250209.

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The 2-position substituent on substrates or substrate analogues for glutamate dehydrogenase is shown to be intimately involved in the induction of conformational changes between subunits in the hexamer by coenzyme. These conformational changes are associated with the negative co-operativity exhibited by this enzyme. 2-Oxoglutarate and L-2-hydroxyglutarate induce indications of co-operativity similar to those induced by the substrate of oxidative deamination, glutamate, in kinetic studies. Glutarate (2-position CH2) does not. A comparison of the effects of L-2-hydroxyglutarate and D-2-hydroxyglutarate or D-glutamate indicates that the 2-position substituent must be in the L-configuration for these conformational changes to be triggered. In addition, glutarate and L-glutamate in ternary enzyme-NAD(P)H-substrate complexes induce very different coenzyme fluorescence properties, showing that glutamate induces a different conformation of the enzyme-coenzyme complex from that induced by glutarate. Although glutamate and glutarate both tighten the binding of reduced coenzyme to the active site, the effect is much greater with glutamate, and the binding is described by two dissociation constants when glutamate is present. The data suggest that the two carboxy groups on the substrate are required to allow synergistic binding of coenzyme and substrate to the active site, but that interactions between the 2-position on the substrate and the enzyme trigger the conformational changes that result in subunit-subunit interactions and in the catalytic co-operativity exhibited by this enzyme.
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50

Jansen, Herwig, Bernd Müller, and Karl Knobloch. "Alliin Lyase from Garlic,Allium sativum:Investigations on Enzyme/Substrate, Enzyme/Inhibitor Interactions, and on a New Coenzyme." Planta Medica 55, no. 05 (October 1989): 440–45. http://dx.doi.org/10.1055/s-2006-962060.

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