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Conformational-relaxation models of single-enzyme kinetics

机译:单酶动力学的构象松弛模型

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Fluorescent spectroscopy experiments with single-enzyme molecules yield a large volume of statistical data that can be analyzed and interpreted using stochastic models of enzyme action. Here, we present two models, each based on the mechanism that an enzyme molecule must pass through a sequence of conformational transformations to complete its catalytic turnover cycle. In the simplest model, only one path leading to the release of product is present. In contrast to this, two different catalytic paths are possible in the second considered model. If a cycle is started from an active state, immediately after the previous product release, it follows a different conformational route and is much shorter. Our numerical investigations show that both models generate non-Markovian molecular statistics. However, their memory landscapes and distributions of cycle times are significantly different. The memory landscape of the double-path model bears strong similarity to the recent experimental data for horseradish peroxidase.
机译:使用单酶分子的荧光光谱实验产生了大量的统计数据,可以使用酶作用的随机模型进行分析和解释。在这里,我们提出两个模型,每个模型都基于一种机制,即酶分子必须通过一系列构象转化来完成其催化转换周期。在最简单的模型中,仅存在导致产品发布的一条路径。与此相反,在第二个考虑的模型中可能有两个不同的催化路径。如果从活动状态开始一个周期,则在上一个产品发布之后,它将遵循不同的构象路线,并且周期要短得多。我们的数值研究表明,这两个模型均会生成非马尔可夫分子统计数据。但是,它们的内存状况和周期时间的分布明显不同。双路径模型的记忆格局与辣根过氧化物酶的最新实验数据具有很强的相似性。

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