一种测定ω-转氨酶表现底物抑制的内在动力学参数的简便方法

Sang-Woo Han, Jong-Shik Shin
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引用次数: 4

摘要

确定双底物酶的内在动力学参数通常是耗时的,特别是当实验动力学数据偏离线性Lineweaver-Burk图时,由于复杂的抑制模式。一个典型的例子是ω-转氨酶(ω-TA),它是一种重要的工业酶,用于不对称合成手性胺。ω-TA通过乒乓- bi-bi机制催化一个氨基在供体(D)和受体(a)之间的转移,并且经常表现出活性氨基受体对底物的抑制作用,这导致人们更倾向于确定表观动力学参数而不是内在动力学参数,尽管对酶性质的精确理解适用性有限。本文提出了一种利用双倒易分析方法确定ω-TA本征动力学参数的新方法。首先,用一组固定[D]下测定的动力学数据对1/初始速率(vi)与1/[A]进行线性回归,而[A]受底物抑制作用的影响远低于浓度范围。其次,在相当大的底物抑制范围内,在固定的[a]处获得一组动力学数据,对1/[D]与1/vi进行线性回归。利用两条回归线的y截距和斜率得到的4个方程来确定A的周转数(kcat)、底物抑制常数(KSI)和D和A的Michaelis常数(KM)这4个本然动力学参数。为了评估本然参数的可靠性,通过对比实验结果和计算结果对底物抑制曲线的最大值点进行了效度检验。一旦确定了一个底物对的内在参数,其他底物的内在参数就可以简单地通过与具有动力学特征的底物组成一个新的底物对并对一组动力学数据进行线性回归来评估。我们的方法有望适用于广泛的双底物酶,以方便地测定包括KSI在内的内在动力学参数。
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A facile method to determine intrinsic kinetic parameters of ω-transaminase displaying substrate inhibition

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.

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来源期刊
Journal of Molecular Catalysis B-enzymatic
Journal of Molecular Catalysis B-enzymatic 生物-生化与分子生物学
CiteScore
2.58
自引率
0.00%
发文量
0
审稿时长
3.4 months
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.
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