A probabilistic framework for the exploration of enzymatic capabilities based on feasible kinetics and control analysis

Saa, Pedro A. and Nielsen, Lars K. (2016) A probabilistic framework for the exploration of enzymatic capabilities based on feasible kinetics and control analysis. Biochimica et Biophysica Acta - General Subjects, 1860 3: 576-587. doi:10.1016/j.bbagen.2015.12.015

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Author Saa, Pedro A.
Nielsen, Lars K.
Title A probabilistic framework for the exploration of enzymatic capabilities based on feasible kinetics and control analysis
Journal name Biochimica et Biophysica Acta - General Subjects   Check publisher's open access policy
ISSN 1872-8006
Publication date 2016-03
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.bbagen.2015.12.015
Open Access Status File (Author Post-print)
Volume 1860
Issue 3
Start page 576
End page 587
Total pages 12
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Collection year 2016
Language eng
Formatted abstract
Analysis of limiting steps within enzyme-catalyzed reactions is fundamental to understand their behavior and regulation. Methods capable of unravelling control properties and exploring kinetic capabilities of enzymatic reactions would be particularly useful for protein and metabolic engineering. While single-enzyme control analysis formalism has previously been applied to well-studied enzymatic mechanisms, broader application of this formalism is limited in practice by the limited amount of kinetic data and the difficulty of describing complex allosteric mechanisms.

To overcome these limitations, we present here a probabilistic framework enabling control analysis of previously unexplored mechanisms under uncertainty. By combining a thermodynamically consistent parameterization with an efficient Sequential Monte Carlo sampler embedded in a Bayesian setting, this framework yields insights into the capabilities of enzyme-catalyzed reactions with modest kinetic information, provided that the catalytic mechanism and a thermodynamic reference point are defined.

The framework was used to unravel the impact of thermodynamic affinity, substrate saturation levels and effector concentrations on the flux control and response coefficients of a diverse set of enzymatic reactions.

Our results highlight the importance of the metabolic context in the control analysis of isolated enzymes as well as the use of statistically sound methods for their interpretation.

General Significance
This framework significantly expands our current capabilities for unravelling the control properties of general reaction kinetics with limited amount of information. This framework will be useful for both theoreticians and experimentalists in the field.
Keyword Bayesian inference
Control analysis
Enzyme kinetics
Rate-limiting steps
Sequential Monte Carlo
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
Australian Institute for Bioengineering and Nanotechnology Publications
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