Protein conformations à la carte, a step further in de novo protein design
Protein conformations à la carte, a step further in de novo protein design
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蛋白质构象按菜单点菜，蛋白质从头设计更进一步
DOI：
10.1073/pnas.2004188117
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Morcos, Faruck
中科院分区：
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作者：
Morcos, Faruck
蛋白质在细胞内执行一系列功能，从能量利用到酶活性到信号传导，以及结构和机械作用等。多年来，大量的研究工作集中在分子水平上理解这些现象以及影响其发展的进化过程。这些努力的一部分包括阐明蛋白质结构的基本原理。由于蛋白质的功能是在蛋白质的三维（3D）排列中编码的，因此多年来，确定蛋白质折叠，结构和动力学的原则一直是蛋白质科学研究的重点。理查德·费曼的最后一块黑板上刻着这句话：“我不能创造的，我不能理解。这种思维方式激励科学家们不满足于揭示基本原理，而是应用它们来创造具有所需特性的新型蛋白质。Wei et al. (2)在PNAS是一个相关的例子，这样的努力，以证明蛋白质结构和动力学的生物物理原理的理解，通过设计一种蛋白质，可以改变其形状在特定的解决方案条件下。蛋白质设计领域面临着潜在蛋白质序列及其折叠的巨大空间的挑战。正因为如此，大多数努力都集中在研究自然界中发现的现存的大量序列和结构上，这些序列和结构是数百万年进化历史的结果。使用天然蛋白质及其序列作为模板来设计新的蛋白质提供了搜索空间的关键减少，并为结构特征和功能行为提供了基础。这一概念在定向进化（3）和基于计算模板的蛋白质结构建模（4）领域的实验和理论上都得到了成功的探索。这就是使用进化原理来设计蛋白质的影响，2018年，Frances Arnold因其在使用定向进化设计新型酶方面的开创性贡献而被授予诺贝尔化学奖。由于蛋白质结构预测领域与阐明新蛋白质的想法密切相关，因此该领域的进展也是基础性的。特别是，进化信息的使用也有重要的贡献，特别是通过识别编码在蛋白质序列中的共同进化信号，为3D空间中氨基酸相互作用的模型提供信息（5-8）。例如，在我的小组中，我们使用进化信号来设计合成生物学应用的杂交阻遏物的反应（9）。将其与蛋白质折叠的广泛理论发展（10）和蛋白质自由能计算的计算建模（11，12）相结合，为从头蛋白质设计提供了更清晰的途径（13）。从头蛋白质设计与之前描述的进展不同，因为它旨在探索一个在进化过程中以前没有访问过的空间，但其基本的物理和化学原理得到了维护。Wei et al. (2)属于这种努力，以创造所需的性质，从探索的第一原则。在他们的研究中，他们建立了一个广泛的蛋白质建模和设计框架，该框架由贝克实验室和华盛顿大学蛋白质设计研究所的成员带头贡献（12，14，15）。在过去的一项研究中，该小组创建了一个从头六螺旋束，即由相同的α螺旋组成的蛋白质复合物，它们相互作用形成类似于细长玫瑰束的结构（14）。Wei et.
Proteins perform a spectrum of functions inside the cell, ranging from energy utilization to enzymatic activity to signaling, as well as structural and mechanical roles, among many others. Substantial research efforts throughout the years have focused on understanding these phenomena at the molecular level as well as the evolutionary processes that influenced their development. Part of these efforts include the elucidation of the fundamental principles that give shape to protein structures. Since function is encoded in the three-dimensional (3D) arrangement of proteins, identifying the principles of protein folding, structure, and dynamics has been a priority for research in protein science for many years. Inscribed on the last blackboard of Richard Feynman is the phrase “What I cannot create, I cannot understand”(1). This way of thinking has inspired scientists to not be satisfied with revealing fundamental principles but to apply them to create novel proteins with desired properties. The work of Wei et al.(2) in PNAS is a relevant example of such efforts to demonstrate understanding of biophysical principles of protein structure and dynamics by designing a protein that can change its shape under specific solution conditions. The field of protein design is challenged by the enormous space of potential protein sequences and their folds. Because of this, most efforts have been focused on studying the extant plethora of sequences and structures found in nature that were the result of millions of years of evolutionary history. Using natural proteins and their sequences as templates to engineer new proteins provides a key reduction of search space and a basis for both structural features and functional behavior. This concept has been explored successfully both experimentally and theoretically in the field of directed evolution (3) and computational templatebased modeling of protein structure (4). Such has been the impact of the use of evolutionary principles to engineer proteins that, in 2018, Frances Arnold was awarded the Nobel Prize in Chemistry for her pioneering contributions to designing novel enzymes using directed evolution. Since the field of protein structure prediction is closely related to the idea of elucidating novel proteins, advances in this field have been fundamental, too. Particularly, the use of evolutionary information has also had important contributions, especially through the identification of coevolutionary signals encoded in protein sequences that inform models on amino acid interactions in 3D space (5–8). For example, in my group, we have used evolutionary signals to engineer the response of hybrid repressors for synthetic biology applications (9). Combining this with the extensive theoretical developments of protein folding (10) and computational modeling of protein free energy calculations (11, 12) has given rise to a clearer pathway for de novo protein design (13). De novo protein design is different from the advances described before because it aims to explore a space that has not been previously visited in the evolutionary process but whose fundamental physical and chemical principles are maintained. The work of Wei et al.(2) belongs to this effort to create desired properties from the exploration of first principles. In their research, they build from an extensive framework for protein modeling and design spearheaded by contributions of the Baker laboratory and members of the Institute for Protein Design at the University of Washington (12, 14, 15). In a past study, the group created a de novo six-helix bundle, that is, a protein complex consisting of identical alpha helices that interact to form structures analogous to elongated rose bundles (14). Wei et …
影响因子：
5.7
作者：
Lizatovic, Robert;Aurelius, Oskar;Andre, Ingemar
通讯作者：
Andre, Ingemar
Rosetta3：一个面向对象的软件套件，用于大分子的仿真和设计。
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