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  Direct determination of enzyme kinetic parameters from single reactions using a new progress curve analysis tool

Bäuerle, F., Zotter, A., & Schreiber, G. (2017). Direct determination of enzyme kinetic parameters from single reactions using a new progress curve analysis tool. Protein Engineering Design and Selection, 30(3), 151-158. doi:10.1093/protein/gzw053.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-5A13-A Version Permalink: http://hdl.handle.net/21.11116/0000-0001-2C63-F
Genre: Journal Article

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 Creators:
Bäuerle, Felix1, Author              
Zotter, A., Author
Schreiber, G., Author
Affiliations:
1Max Planck Research Group Biological Physics and Morphogenesis, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2266692              

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Free keywords: Michaelis-Menten; enzyme kinetics; single reaction curve
 Abstract: With computer-based data-fitting methods becoming a standard tool in biochemistry, progress curve analysis of enzyme kinetics is a feasible, yet seldom used tool. Here we present a versatile Matlab-based tool (PCAT) to analyze catalysis progress curves with three complementary model approaches. The first two models are based on the known closed-form solution for this problem: the first describes the required Lambert W function with an analytical approximation and the second provides a numerical solution of the Lambert W function. The third model is a direct simulation of the enzyme kinetics. Depending on the chosen model, the tools excel in speed, accuracy or initial value requirements. Using simulated and experimental data, we show the strengths and pitfalls of the different fitting models. Direct simulation proves to have the highest level of accuracy, but it also requires reasonable initial values to converge. Finally, we propose a standard procedure to obtain optimized enzyme kinetic parameters from single progress curves.

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Language(s): eng - English
 Dates: 2016-01-112017-03-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1093/protein/gzw053
 Degree: -

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Title: Protein Engineering Design and Selection
Source Genre: Journal
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Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 30 (3) Sequence Number: - Start / End Page: 151 - 158 Identifier: ISSN: 1741-0126