A General Guide for the Optimization of Enzyme Assay Conditions Using the Design of Experiments Approach

Favour Chinyere Onyeogaziri, Christos Papaneophytou

Research output: Contribution to journalArticle

Abstract

Many factors must be considered during the optimization of an enzyme assay. These include the choice of buffer and its composition, the type of enzyme and its concentration, as well as the type of substrate and concentrations, the reaction conditions, and the appropriate assay technology. The process of an enzyme assay optimization, in our experience, can take more than 12 weeks using the traditional one-factor-at-a-time approach. In contrast, the design of experiments (DoE) approaches have the potential to speed up the assay optimization process and provide a more detailed evaluation of tested variables. However, not all researchers are aware of DoE approaches or believe that it is easy to employ a DoE approach for the optimization of an assay. In order to facilitate enzyme assay developers to use DoE methodologies, we present in detail the steps required to identify in less than 3 days (1) the factors that significantly affect the activity of an enzyme and (2) the optimal assay conditions using a fractional factorial approach and response surface methodology. This is exemplified with the optimization of assay conditions for the human rhinovirus-3C protease, and the methodology used could be employed as a basic guide for the speedy identification of the optimum assay conditions for any enzyme.

Original languageEnglish
JournalSLAS Discovery
DOIs
Publication statusPublished - 1 Jan 2019

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Enzyme Assays
Design of experiments
Assays
Enzymes
Buffers
Research Personnel
Technology
Substrates
Chemical analysis

Keywords

  • assay optimization
  • design of experiments
  • enzyme activity
  • fractional factorial
  • response surface methodology

Cite this

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A General Guide for the Optimization of Enzyme Assay Conditions Using the Design of Experiments Approach. / Onyeogaziri, Favour Chinyere; Papaneophytou, Christos.

In: SLAS Discovery, 01.01.2019.

Research output: Contribution to journalArticle

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