TY - JOUR

T1 - A robust methodology for kinetic model parameter estimation for biocatalytic reactions

A1 - Al-Haque,Naweed

A1 - Andrade Santacoloma,Paloma de Gracia

A1 - Lima Afonso Neto,Watson

A1 - Tufvesson,Pär

A1 - Gani,Rafiqul

A1 - Woodley,John

AU - Al-Haque,Naweed

AU - Andrade Santacoloma,Paloma de Gracia

AU - Lima Afonso Neto,Watson

AU - Tufvesson,Pär

AU - Gani,Rafiqul

AU - Woodley,John

PB - Wiley-Blackwell Publishing, Inc.

PY - 2012

Y1 - 2012

N2 - Effective estimation of parameters in biocatalytic reaction kinetic expressions are very important when building process models to enable evaluation of process technology options and alternative biocatalysts. The kinetic models used to describe enzyme-catalyzed reactions generally include several parameters, which are strongly correlated with each other. State-of-the-art methodologies such as nonlinear regression (using progress curves) or graphical analysis (using initial rate data, for example, the Lineweaver-Burke plot, Hanes plot or Dixon plot) often incorporate errors in the estimates and rarely lead to globally optimized parameter values. In this article, a robust methodology to estimate parameters for biocatalytic reaction kinetic expressions is proposed. The methodology determines the parameters in a systematic manner by exploiting the best features of several of the current approaches. The parameter estimation problem is decomposed into five hierarchical steps, where the solution of each of the steps becomes the input for the subsequent step to achieve the final model with the corresponding regressed parameters. The model is further used for validating its performance and determining the correlation of the parameters. The final model with the fitted parameters is able to describe both initial rate and dynamic experiments. Application of the methodology is illustrated with a case study using the x-transaminase catalyzed synthesis of 1-phenylethylamine from acetophenone and 2-propylamine.

AB - Effective estimation of parameters in biocatalytic reaction kinetic expressions are very important when building process models to enable evaluation of process technology options and alternative biocatalysts. The kinetic models used to describe enzyme-catalyzed reactions generally include several parameters, which are strongly correlated with each other. State-of-the-art methodologies such as nonlinear regression (using progress curves) or graphical analysis (using initial rate data, for example, the Lineweaver-Burke plot, Hanes plot or Dixon plot) often incorporate errors in the estimates and rarely lead to globally optimized parameter values. In this article, a robust methodology to estimate parameters for biocatalytic reaction kinetic expressions is proposed. The methodology determines the parameters in a systematic manner by exploiting the best features of several of the current approaches. The parameter estimation problem is decomposed into five hierarchical steps, where the solution of each of the steps becomes the input for the subsequent step to achieve the final model with the corresponding regressed parameters. The model is further used for validating its performance and determining the correlation of the parameters. The final model with the fitted parameters is able to describe both initial rate and dynamic experiments. Application of the methodology is illustrated with a case study using the x-transaminase catalyzed synthesis of 1-phenylethylamine from acetophenone and 2-propylamine.

KW - Biocatalysis

KW - Parameter estimation

KW - Kinetic modeling

KW - Omega-transaminases

U2 - 10.1002/btpr.1588

DO - 10.1002/btpr.1588

JO - Biotechnology Progress

JF - Biotechnology Progress

SN - 8756-7938

IS - 5

VL - 28

SP - 1186

EP - 1196

ER -