Centro Nacional de Biotecnologı́a (CNB-CSIC), Darwin 3, Campus de Cantoblanco, 28049 Madrid, Spain.
Unidad Asociada de Nanobiotecnologı́a IMDEA Nanociencia-CNB, 28049 Madrid, Spain.
Acc Chem Res. 2020 Oct 20;53(10):2180-2188. doi: 10.1021/acs.accounts.0c00322. Epub 2020 Sep 11.
The function of proteins as biological nanomachines relies on their ability to fold into complex 3D structures, bind selectively to partners, and undergo conformational changes on cue. The native functional structures, and the rates of interconversion between conformational states (folded-unfolded, bound-free), are all encoded in the physical chemistry of their amino acid sequence. However, despite extensive research over decades, this code has proven difficult to fully crack, in terms of both prediction and understanding the molecular mechanisms at play.Earlier work on single-domain proteins reported a commonality of slow rates (10-10 s) and simple behavior in both kinetic and thermodynamic unfolding experiments, which suggested the process was all-or-none and thereby analogous to a chemical reaction (e.g., A ⇄ B). In the absence of a first-principles pre-exponential factor for protein (un)folding dynamics, the rates could only be interpreted in relative terms, e.g., the changes induced by mutation, and hence, neither the height of nor the entropic contribution to the free energy barriers was known. The rates were also many orders of magnitude too slow for direct atomistic simulations, and the computational focus was on predicting rate changes induced by mutation via coarse grained simulations. However, even the effects of mutation proved to be strikingly homogeneous with all experimental data clustering at ∼1/3 of the free energy perturbation recovered on folding and ∼2/3 on unfolding.The implementation of ultrafast kinetic methods turned the field upside down because they allowed researchers to measure the time scales of elementary (un)folding motions, which set the pre-exponential factor for protein conformational transitions at ∼1 μs. In parallel, we and others set out to investigate the simplest possible protein structures capable of autonomous folding, which we defined as archetypal folds. The rationale was to recapitulate the hierarchical organization of protein structure, starting from the bottom up. The study of fold archetypes ended up opening new research avenues in protein (un)folding, but also making unexpected connections with the folding upon binding of intrinsically disordered proteins and suggesting their functioning as conformational rheostats.This Account describes our work on the kinetic, thermodynamic, mechanistic, and functional analysis of fold archetypes. We first discuss the kinetic studies, emphasizing their impact on our understanding of (un)folding rates, of barrierless (downhill) folding, and as benchmarks for atomistic simulations. We continue with the thermodynamic analysis, introducing the differential scanning calorimetry, multiprobe, and NMR approaches that we developed to dissect their gradual, minimally cooperative (un)folding transitions and to probe the underlying mechanisms with unprecedented detail. The last two sections cover single-molecule analyses and some recent, mostly computational, results on the exploration of possible biological and technological roles for the gradual conformational transitions of fold archetypes.
蛋白质作为生物纳米机器的功能依赖于它们折叠成复杂 3D 结构、选择性结合伴侣以及根据提示进行构象变化的能力。天然功能结构以及构象状态(折叠-展开、结合-游离)之间的转换速率都编码在其氨基酸序列的物理化学性质中。然而,尽管经过几十年的广泛研究,这个密码在预测和理解发挥作用的分子机制方面都被证明难以完全破解。
早期对单结构域蛋白质的研究报告了在动力学和热力学展开实验中,缓慢的速率(10-10 s)和简单行为的共同性,这表明该过程是全有或全无的,因此类似于化学反应(例如,A ⇄ B)。由于缺乏蛋白质(解)折叠动力学的第一性原理前置指数因子,速率只能在相对意义上进行解释,例如突变引起的变化,因此,既不知道自由能势垒的高度,也不知道熵贡献。速率也慢了好几个数量级,无法直接进行原子模拟,计算的重点是通过粗粒化模拟预测突变引起的速率变化。然而,即使是突变的影响也被证明是惊人的均匀,所有实验数据都聚集在折叠时恢复的自由能扰动的 1/3 和展开时的 2/3。
超快动力学方法的实施颠覆了这个领域,因为它们允许研究人员测量基本(解)折叠运动的时间尺度,这为蛋白质构象转变设置了前置指数因子,约为 1 μs。同时,我们和其他人开始研究能够自主折叠的最简单的蛋白质结构,我们将其定义为典型折叠。其基本原理是从底部开始,逐步构建蛋白质结构的层次组织。折叠原型的研究最终在蛋白质(解)折叠领域开辟了新的研究途径,但也与内在无序蛋白质结合时的折叠形成了出人意料的联系,并暗示它们作为构象节流阀发挥作用。
本报告描述了我们在折叠原型的动力学、热力学、力学和功能分析方面的工作。我们首先讨论了动力学研究,强调了它们对我们理解(解)折叠速率、无势垒(下坡)折叠以及作为原子模拟基准的影响。然后我们继续进行热力学分析,介绍了差示扫描量热法、多探针和 NMR 方法,我们开发了这些方法来剖析它们逐渐的、最小合作(解)折叠转变,并以前所未有的细节探测潜在的机制。最后两个部分涵盖了单分子分析以及最近的一些主要是计算方面的结果,这些结果探索了折叠原型的逐渐构象转变在生物学和技术方面的可能作用。