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首页> 外文期刊>EURASIP journal on bioinformatics and systems biology >Relationships between kinetic constants and the amino acid composition of enzymes from the yeast Saccharomyces cerevisiae glycolysis pathway
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Relationships between kinetic constants and the amino acid composition of enzymes from the yeast Saccharomyces cerevisiae glycolysis pathway

机译:酵母菌糖酵解途径的酶动力学常数与氨基酸组成的关系

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摘要

The kinetic models of metabolic pathways represent a system of biochemical reactions in terms of metabolic fluxes and enzyme kinetics. Therefore, the apparent differences of metabolic fluxes might reflect distinctive kinetic characteristics, as well as sequence-dependent properties of the employed enzymes. This study aims to examine possible linkages between kinetic constants and the amino acid (AA) composition (AAC) for enzymes from the yeast Saccharomyces cerevisiae glycolytic pathway. The values of Michaelis-Menten constant (K M), turnover number (k cat), and specificity constant (k sp?=?k cat/K M) were taken from BRENDA (15, 17, and 16 values, respectively) and protein sequences of nine enzymes (HXK, GADH, PGK, PGM, ENO, PK, PDC, TIM, and PYC) from UniProtKB. The AAC and sequence properties were computed by ExPASy/ProtParam tool and data processed by conventional methods of multivariate statistics. Multiple linear regressions were found between the log-values of k cat (3 models, 85.74%?
机译:代谢途径的动力学模型代表了根据代谢通量和酶动力学的生化反应系统。因此,代谢通量的表观差异可能反映了独特的动力学特性以及所用酶的序列依赖性。这项研究旨在检查酵母菌糖酵解途径的酶的动力学常数与氨基酸(AA)组成(AAC)之间的可能联系。 Michaelis-Menten常数(KM),周转数(k cat)和特异性常数(k sp?=?k cat / KM)的值分别取自BRENDA(分别为15、17和16)和蛋白质序列。 UniProtKB的九种酶(HXK,GADH,PGK,PGM,ENO,PK,PDC,TIM和PYC)中的一种。通过ExPASy / ProtParam工具计算AAC和序列属性,并通过常规的多元统计方法处理数据。在k cat(3个模型,85.74%?<?R adj.2 <94.11%,p?<?0.00001),KM(1个模型,R adj.2?=?96.70 %,p?<?0.00001),k sp(3个模型,96.15%?<?R调整2?<?96.50%,p?<?0.00001)和AA频率集(每个模型四到六个) )从酶序列中选择,同时评估变量之间潜在的多重共线性。还发现在多元回归模型中选择自变量可能反映了确定的AA的理化和结构倾向的某些优势,这可能会影响序列的性质。该结果支持了关于催化,结合和结构残基的实际相互依赖性以确保生物催化剂效率的观点,因为酵母酶的动力学常数似乎与序列的总体AAC密切相关。

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