{"title":"A facile method to determine intrinsic kinetic parameters of ω-transaminase displaying substrate inhibition","authors":"Sang-Woo Han, Jong-Shik Shin","doi":"10.1016/j.molcatb.2017.05.001","DOIUrl":null,"url":null,"abstract":"<div><p>It is usually time-consuming to determine intrinsic kinetic parameters of bisubstrate enzymes, especially when experimental kinetic data deviate from a linear Lineweaver-Burk plot due to complex inhibition patterns. A typical example is ω-transaminase (ω-TA) which is an industrially important enzyme for asymmetric synthesis of chiral amines. ω-TA catalyzes transfer of an amino group between a donor (D) and an acceptor (A) via a ping-pong bi-bi mechanism and often displays substrate inhibitions by reactive amino acceptors, which leads one to prefer to determine apparent kinetic parameters rather than intrinsic ones despite limited applicability for precise understanding of enzyme properties. Here, we developed a new method to determine intrinsic kinetic parameters of ω-TA by double-reciprocal analysis using only two sets of kinetic data. First, linear regression of 1/initial rate (<em>v</em><sub>i</sub>) against 1/[A] was carried out with one set of kinetic data measured at a fixed [D] while [A] lay far below the concentration range under the influence of substrate inhibition. Second, another linear regression of 1/[D] vs 1/<em>v</em><sub>i</sub> was conducted with one set of kinetic data obtained at a fixed [A] within a substantial substrate inhibition range. The resulting four equations obtained from the y-intercepts and slopes of the two regression lines were used for determination of four intrinsic kinetic parameters, i.e. turnover number (<em>k</em><sub>cat</sub>), substrate inhibition constant (<em>K</em><sub>SI</sub>) for A and Michaelis constants (<em>K</em><sub>M</sub>) for D and A. To evaluate reliability of the intrinsic parameters, a validity test was taken by comparing experimental and computational results for the maximum point on a concave-down substrate inhibition curve. Once the intrinsic parameters were determined for a substrate pair, intrinsic parameters for other substrates were simply assessed by constituting a new substrate pair with the kinetically characterized substrate and carrying out linear regression with one set of kinetic data. Our method is expected to be applicable to a wide range of bisubstrate enzymes for facile determination of intrinsic kinetic parameters including <em>K</em><sub>SI</sub>.</p></div>","PeriodicalId":16416,"journal":{"name":"Journal of Molecular Catalysis B-enzymatic","volume":"133 ","pages":"Pages S500-S507"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.molcatb.2017.05.001","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Molecular Catalysis B-enzymatic","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1381117717300474","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Chemical Engineering","Score":null,"Total":0}
引用次数: 4
Abstract
It is usually time-consuming to determine intrinsic kinetic parameters of bisubstrate enzymes, especially when experimental kinetic data deviate from a linear Lineweaver-Burk plot due to complex inhibition patterns. A typical example is ω-transaminase (ω-TA) which is an industrially important enzyme for asymmetric synthesis of chiral amines. ω-TA catalyzes transfer of an amino group between a donor (D) and an acceptor (A) via a ping-pong bi-bi mechanism and often displays substrate inhibitions by reactive amino acceptors, which leads one to prefer to determine apparent kinetic parameters rather than intrinsic ones despite limited applicability for precise understanding of enzyme properties. Here, we developed a new method to determine intrinsic kinetic parameters of ω-TA by double-reciprocal analysis using only two sets of kinetic data. First, linear regression of 1/initial rate (vi) against 1/[A] was carried out with one set of kinetic data measured at a fixed [D] while [A] lay far below the concentration range under the influence of substrate inhibition. Second, another linear regression of 1/[D] vs 1/vi was conducted with one set of kinetic data obtained at a fixed [A] within a substantial substrate inhibition range. The resulting four equations obtained from the y-intercepts and slopes of the two regression lines were used for determination of four intrinsic kinetic parameters, i.e. turnover number (kcat), substrate inhibition constant (KSI) for A and Michaelis constants (KM) for D and A. To evaluate reliability of the intrinsic parameters, a validity test was taken by comparing experimental and computational results for the maximum point on a concave-down substrate inhibition curve. Once the intrinsic parameters were determined for a substrate pair, intrinsic parameters for other substrates were simply assessed by constituting a new substrate pair with the kinetically characterized substrate and carrying out linear regression with one set of kinetic data. Our method is expected to be applicable to a wide range of bisubstrate enzymes for facile determination of intrinsic kinetic parameters including KSI.
期刊介绍:
Journal of Molecular Catalysis B: Enzymatic is an international forum for researchers and product developers in the applications of whole-cell and cell-free enzymes as catalysts in organic synthesis. Emphasis is on mechanistic and synthetic aspects of the biocatalytic transformation.
Papers should report novel and significant advances in one or more of the following topics;
Applied and fundamental studies of enzymes used for biocatalysis;
Industrial applications of enzymatic processes, e.g. in fine chemical synthesis;
Chemo-, regio- and enantioselective transformations;
Screening for biocatalysts;
Integration of biocatalytic and chemical steps in organic syntheses;
Novel biocatalysts, e.g. enzymes from extremophiles and catalytic antibodies;
Enzyme immobilization and stabilization, particularly in non-conventional media;
Bioprocess engineering aspects, e.g. membrane bioreactors;
Improvement of catalytic performance of enzymes, e.g. by protein engineering or chemical modification;
Structural studies, including computer simulation, relating to substrate specificity and reaction selectivity;
Biomimetic studies related to enzymatic transformations.