Astumian R Dean
Department of Physics , University of Maine , Orono , Maine 04469 , United States.
Acc Chem Res. 2018 Nov 20;51(11):2653-2661. doi: 10.1021/acs.accounts.8b00253. Epub 2018 Oct 11.
A molecular machine is a nanoscale device that provides a mechanism for coupling energy from two (or more) processes that in the absence of the machine would be independent of one another. Examples include walking of a protein in one direction along a polymeric track (process 1, driving "force" X = - F⃗· l⃗) and hydrolyzing ATP (process 2, driving "force" X = Δμ); or synthesis of ATP (process 1, X = -Δμ) and transport of protons from the periplasm to the cytoplasm across a membrane (process 2, X = Δμ); or rotation of a flagellum (process 1, X = -torque) and transport of protons across a membrane (process 2, X = Δμ). In some ways, the function of a molecular machine is similar to that of a macroscopic machine such as a car that couples combustion of gasoline to translational motion. However, the low Reynolds number regime in which molecular machines operate is very different from that relevant for macroscopic machines. Inertia is negligible in comparison to viscous drag, and omnipresent thermal noise causes the machine to undergo continual transition among many states even at thermodynamic equilibrium. Cyclic trajectories among the states of the machine that result in a change in the environment can be broken into two classes: those in which process 1 in either the forward or backward direction ([Formula: see text]) occurs and which thereby exchange work [Formula: see text] with the environment; and those in which process 2 in either the forward or backward direction ([Formula: see text]) occurs and which thereby exchange work [Formula: see text] with the evironment. These two types of trajectories, [Formula: see text] and [Formula: see text], overlap, i.e., there are some trajectories in which both process 1 and process 2 occur, and for which the work exchanged is [Formula: see text]. The four subclasses of overlap trajectories [(+1,+2), (+1,-2), (-1,+2), (-1,-2)] are the coupled processes. The net probabilities for process 1 and process 2 are designated π - π and π - π, respectively. The probabilities [Formula: see text] for any single trajectory [Formula: see text] and [Formula: see text] for its microscopic reverse [Formula: see text] are related by microscopic reversibility (MR), [Formula: see text], an equality that holds arbitrarily far from thermodynamic equilibrium, i.e., irrespective of the magnitudes of X and X, and where [Formula: see text]. Using this formalism, we arrive at a remarkably simple and general expression for the rates of the processes, [Formula: see text], i = 1, 2, where the angle brackets indicate an average over the ensemble of all microscopic reverse trajectories. Stochastic description of coupling is doubtless less familiar than typical mechanical depictions of chemical coupling in terms of ATP induced violent kicks, judo throws, force generation and power-strokes. While the mechanical description of molecular machines is comforting in its familiarity, conclusions based on such a phenomenological perspective are often wrong. Specifically, a "power-stroke" model (i.e., a model based on energy driven "promotion" of a molecular machine to a high energy state followed by directional relaxation to a lower energy state) that has been the focus of mechanistic discussions of biomolecular machines for over a half century is, for catalysis driven molecular machines, incorrect. Instead, the key principle by which catalysis driven motors work is kinetic gating by a mechanism known as an information ratchet. Amazingly, this same principle is that by which catalytic molecular systems undergo adaptation to new steady states while facilitating an exergonic chemical reaction.
分子机器是一种纳米级装置,它提供了一种机制,用于耦合来自两个(或更多)过程的能量,在没有该机器的情况下,这些过程将彼此独立。示例包括蛋白质沿着聚合物轨道在一个方向上移动(过程1,驱动“力”X = -F⃗·l⃗)和水解ATP(过程2,驱动“力”X = Δμ);或者合成ATP(过程1,X = -Δμ)以及质子从周质穿过膜运输到细胞质(过程2,X = Δμ);或者鞭毛的旋转(过程1,X = -扭矩)和质子跨膜运输(过程2,X = Δμ)。在某些方面,分子机器的功能类似于宏观机器,如将汽油燃烧与平移运动耦合的汽车。然而,分子机器运行的低雷诺数 regime 与宏观机器相关的 regime 非常不同。与粘性阻力相比,惯性可以忽略不计,并且无处不在的热噪声导致机器即使在热力学平衡时也会在许多状态之间持续转变。机器状态之间导致环境变化的循环轨迹可以分为两类:一类是过程1在向前或向后方向([公式:见原文])发生,从而与环境交换功[公式:见原文];另一类是过程2在向前或向后方向([公式:见原文])发生,从而与环境交换功[公式:见原文]。这两种类型的轨迹,[公式:见原文]和[公式:见原文],相互重叠,即存在一些轨迹,其中过程1和过程2都发生,并且交换的功为[公式:见原文]。重叠轨迹的四个子类[(+1,+2), (+1,-2), (-1,+2), (-1,-2)]是耦合过程。过程1和过程2的净概率分别表示为π - π和π - π。任何单个轨迹[公式:见原文]的概率[公式:见原文]及其微观反向[公式:见原文]的概率[公式:见原文]通过微观可逆性(MR)相关联,[公式:见原文],这个等式在任意远离热力学平衡的情况下都成立,即与X和X的大小无关,并且其中[公式:见原文]。使用这种形式主义,我们得到了过程速率的一个非常简单和通用的表达式,[公式:见原文],i = 1, 2,其中尖括号表示对所有微观反向轨迹的集合进行平均。耦合的随机描述无疑比根据ATP诱导的剧烈冲击、柔道投掷、力的产生和动力冲程等典型机械描述的化学耦合更不为人所熟悉。虽然分子机器的机械描述因其熟悉性而令人安心,但基于这种现象学观点得出的结论往往是错误的。具体而言,一个“动力冲程”模型(即一个基于能量驱动分子机器“提升”到高能状态然后定向弛豫到低能状态的模型)在半个多世纪以来一直是生物分子机器机制讨论的焦点,但对于催化驱动的分子机器来说是不正确的。相反,催化驱动的马达工作的关键原理是通过一种称为信息棘轮的机制进行动力学门控。令人惊讶地是,这同样也是催化分子系统在促进放能化学反应的同时适应新稳态的原理。