Center of Life Sciences, Skolkovo Institute of Science and Technology, 121205 Moscow, Russia.
Institute of Protein Research, Russian Academy of Sciences, 142290 Pushchino, Moscow Region, Russia.
Biomolecules. 2020 Feb 6;10(2):250. doi: 10.3390/biom10020250.
"How do proteins fold?" Researchers have been studying different aspects of this question for more than 50 years. The most conceptual aspect of the problem is how protein can find the global free energy minimum in a biologically reasonable time, without exhaustive enumeration of all possible conformations, the so-called "Levinthal's paradox." Less conceptual but still critical are aspects about factors defining folding times of particular proteins and about perspectives of machine learning for their prediction. We will discuss in this review the key ideas and discoveries leading to the current understanding of folding kinetics, including the solution of Levinthal's paradox, as well as the current state of the art in the prediction of protein folding times.
“蛋白质如何折叠?” 研究人员已经研究这个问题超过 50 年了。这个问题最具概念性的方面是蛋白质如何在合理的时间内找到全局自由能最小的状态,而无需穷举所有可能的构象,这就是所谓的“莱文塔尔悖论”。虽然不那么具有概念性,但仍然至关重要的是,特定蛋白质的折叠时间的定义因素以及机器学习在其预测方面的应用。我们将在这篇综述中讨论导致目前对折叠动力学理解的关键思想和发现,包括莱文塔尔悖论的解决方案,以及蛋白质折叠时间预测的最新技术。