标题： 酶分子在介观浓度下的催化活性中的非更新统计学 显示英文标题

标题： Non-renewal statistics in the catalytic activity of enzyme molecules at mesoscopic concentrations

摘要： 最近的单酶动力学荧光光谱测量表明，酶促周转形成一个更新随机过程，在这个过程中，周转之间平均等待时间的倒数遵循米氏方程。 然而，在典型的生理条件下，数十到数千个酶参与催化数千到数百万个底物。 我们通过包含随机性和分子离散性的主方程来研究这些生理相关条件下的酶动力学。 从主方程的精确解中，我们发现等待时间既不是独立的，也不是同分布的，这意味着酶促周转形成一个非更新随机过程。 平均等待时间的倒数与米氏方程有显著偏离。 连续周转之间的等待时间是反相关的，其中短间隔更可能被长间隔跟随，反之亦然。 相关性不仅存在于连续的周转之间，还表明多尺度波动主导酶动力学。 显示英文摘要

摘要： Recent fluorescence spectroscopy measurements of single-enzyme kinetics have shown that enzymatic turnovers form a renewal stochastic process in which the inverse of the mean waiting time between turnovers follows the Michaelis-Menten equation. Under typical physiological conditions, however, tens to thousands of enzymes react in catalyzing thousands to millions of substrates. We study enzyme kinetics at these physiologically relevant conditions through a master equation including stochasticity and molecular discreteness. From the exact solution of the master equation we find that the waiting times are neither independent nor are they identically distributed, implying that enzymatic turnovers form a non-renewal stochastic process. The inverse of the mean waiting time shows strong departures from the Michaelis-Menten equation. The waiting times between consecutive turnovers are anti-correlated, where short intervals are more likely to be followed by long intervals and vice versa. Correlations persist beyond consecutive turnovers indicating that multi-scale fluctuations govern enzyme kinetics.