A chemical thermodynamic model of motor enzymes unifies chemical-Fx and powerstroke models.
A chemical thermodynamic model of motor enzymes unifies chemical-Fx and powerstroke models.
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DOI：
10.1016/j.bpj.2022.02.034
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发表时间：
2022-04-05
影响因子：
3.4
通讯作者：
Baker, Josh E.
中科院分区：
文献类型：
--
作者：
Baker, Josh E.
分子马达在许多生物过程中发挥着核心作用，从泵血和呼吸到生长和伤口愈合。通过电机催化的化学反应，这些纳米机器将 ATP 水解产生的化学自由能转化为两种不同形式的机械功。运动酶通过其催化反应循环中的中间步骤（称为工作步骤）执行可逆功 wrev，并且当它们抵抗力 F 移动距离 x 时执行 Fx 功。在动力冲程模型中，当工作步骤在给定运动酶内拉伸弹簧时执行 wrev。在化学 Fx 模型中，wrev 用于生成在运动酶外部定义的保守 Fx 电位。尽管这两个模型都已被证明能够以合理的精度解释运动酶的机械化学测量，但很难在这些模型之间找到任何共同点。在这里，我表明，通过改变每个模型中的一个简单假设，可以通过化学热力学模型协调动力冲程和化学 Fx 模型。提出了改变这些假设的正式和实验理由。结果是 A.V. 首次提出了运动酶中机械化学耦合的统一模型。 Hill于1938年认为与单分子结构和力学数据一致。
Molecular motors play a central role in many biological processes, ranging from pumping blood and breathing to growth and wound healing. Through motor-catalyzed chemical reactions, these nanomachines convert the chemical free energy from ATP hydrolysis into two different forms of mechanical work. Motor enzymes perform reversible work, wrev, through an intermediate step in their catalyzed reaction cycle referred to as a working step, and they perform Fx work when they move a distance, x, against a force, F. In a powerstroke model, wrev is performed when the working step stretches a spring within a given motor enzyme. In a chemical-Fx model, wrev is performed in generating a conserved Fx potential defined external to the motor enzyme. It is difficult to find any common ground between these models even though both have been shown to account for mechanochemical measurements of motor enzymes with reasonable accuracy. Here, I show that, by changing one simple assumption in each model, the powerstroke and chemical-Fx model can be reconciled through a chemical thermodynamic model. The formal and experimental justifications for changing these assumptions are presented. The result is a unifying model for mechanochemical coupling in motor enzymes first presented by A.V. Hill in 1938 that is consistent with single-molecule structural and mechanical data.
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影响因子：
2.9
作者：
LYMN, RW;TAYLOR, EW
通讯作者：
TAYLOR, EW
影响因子：
3.4
作者：
Astumian, R. Dean
通讯作者：
Astumian, R. Dean
影响因子：
3.4
作者：
Baker, JE;Brosseau, C;Warshaw, DM
通讯作者：
Warshaw, DM
影响因子：
64.8
作者：
FINER, JT;SIMMONS, RM;SPUDICH, JA
通讯作者：
SPUDICH, JA
DOI：
10.1073/pnas.95.6.2944
发表时间：
1998-03-17
影响因子：
11.1
作者：
Baker, JE;Brust-Mascher, I;Thomas, DD
通讯作者：
Thomas, DD