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Computer program for the kinetic equations of enzyme reactions. The case in which more than one enzyme species is present at the onset of the reaction.

ABSTRACT: This paper presents an extension of the program developed by Varón, Havsteen, García, García-Cánovas & Tudela [(1990) Biochem. J. 270, 825-828] for the expression of the transient-phase and steady-state kinetic equations of a general enzyme system in which the only enzyme species present at the onset of the reaction is the free enzyme. The program has been extended to situations in which more than one enzyme species may be present at the onset of the reaction. The program is given in Supplementary Publication SUP50165 (5 pages), which has been deposited at the British Library Document Supply Centre, Boston Spa, Wetherby, West Yorkshire LS23 7BQ, U.K., from whom copies can be obtained on the terms indicated in Biochem. J. (1991) 273, 5.

SUBMITTER: Varon R

PROVIDER: S-EPMC1151453 | biostudies-other | 1991 Aug

REPOSITORIES: biostudies-other

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Project description:Stability and biological activity of proteins is highly dependent on their physicochemical environment. The development of realistic models of biological systems necessitates quantitative information on the response to changes of external conditions like pH, salinity and concentrations of substrates and allosteric modulators. Changes in just a few variable parameters rapidly lead to large numbers of experimental conditions, which go beyond the experimental capacity of most research groups. We implemented a computer-aided experimenting framework ("robot lab assistant") that allows us to parameterize abstract, human-readable descriptions of micro-plate based experiments with variable parameters and execute them on a conventional 8 channel liquid handling robot fitted with a sensitive plate reader. A set of newly developed R-packages translates the instructions into machine commands, executes them, collects the data and processes it without user-interaction. By combining script-driven experimental planning, execution and data-analysis, our system can react to experimental outcomes autonomously, allowing outcome-based iterative experimental strategies. The framework was applied in a response-surface model based iterative optimization of buffer conditions and investigation of substrate, allosteric effector, pH and salt dependent activity profiles of pyruvate kinase (PYK). A diprotic model of enzyme kinetics was used to model the combined effects of changing pH and substrate concentrations. The 8 parameters of the model could be estimated from a single two-hour experiment using nonlinear least-squares regression. The model with the estimated parameters successfully predicted pH and PEP dependence of initial reaction rates, while the PEP concentration dependent shift of optimal pH could only be reproduced with a set of manually tweaked parameters. Differences between model-predictions and experimental observations at low pH suggest additional protonation-sites at the enzyme or substrates critical for enzymatic activity. The developed framework is a powerful tool to investigate enzyme reaction specifics and explore biological system behaviour in a wide range of experimental conditions.

Project description:Mycobacterium tuberculosis(Mtu), a successful pathogen, has developed resistance against the existing anti-tubercular drugs necessitating discovery of drugs with novel action. Enzymes involved in peptidoglycan biosynthesis are attractive targets for antibacterial drug discovery. The bifunctional enzyme mycobacterial GlmU (Glucosamine 1-phosphate N-acetyltransferase/ N-acetylglucosamine-1-phosphate uridyltransferase) has been a target enzyme for drug discovery. Its C- and N- terminal domains catalyze acetyltransferase (rxn-1) and uridyltransferase (rxn-2) activities respectively and the final product is involved in peptidoglycan synthesis. However, the bifunctional nature of GlmU poses difficulty in deciding which function to be intervened for therapeutic advantage. Genetic analysis showed this as an essential gene but it is still unclear whether any one or both of the activities are critical for cell survival. Often enzymatic activity with suitable high-throughput assay is chosen for random screening, which may not be the appropriate biological function inhibited for maximal effect. Prediction of rate-limiting function by dynamic network analysis of reactions could be an option to identify the appropriate function. With a view to provide insights into biochemical assays with appropriate activity for inhibitor screening, kinetic modelling studies on GlmU were undertaken. Kinetic model of Mtu GlmU-catalyzed reactions was built based on the available kinetic data on Mtu and deduction from Escherichia coli data. Several model variants were constructed including coupled/decoupled, varying metabolite concentrations and presence/absence of product inhibitions. This study demonstrates that in coupled model at low metabolite concentrations, inhibition of either of the GlmU reactions cause significant decrement in the overall GlmU rate. However at higher metabolite concentrations, rxn-2 showed higher decrement. Moreover, with available intracellular concentration of the metabolites and in vivo variant of model, uncompetitive inhibition of rxn-2 caused highest decrement. Thus, at physiologically relevant metabolite concentrations, targeting uridyltranferase activity of Mtu GlmU would be a better choice for therapeutic intervention.

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Computer program for the kinetic equations of enzyme reactions. The case in which more than one enzyme species is present at the onset of the reaction.

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