Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India.
Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, India.
J Mol Biol. 2021 Dec 3;433(24):167325. doi: 10.1016/j.jmb.2021.167325. Epub 2021 Oct 22.
Single domain proteins fold via diverse mechanisms emphasizing the intricate relationship between energetics and structure, which is a direct consequence of functional constraints and demands imposed at the level of sequence. On the other hand, elucidating the interplay between folding mechanisms and function is challenging in large proteins, given the inherent shortcomings in identifying metastable states experimentally and the sampling limitations associated with computational methods. Here, we show that free energy profiles and surfaces of large systems (>150 residues), as predicted by a statistical mechanical model, display a wide array of folding mechanisms with ubiquitous folding intermediates and heterogeneous native ensembles. Importantly, residues around the ligand binding or enzyme active site display a larger tendency to partially unfold and this manifests as intermediates or excited states along the folding coordinate in ligand binding domains, transcription repressors, and representative enzymes from all the six classes, including the SARS-CoV-2 receptor binding domain (RBD) of the spike protein and the protease M. It thus appears that it is relatively easier to distill the imprints of function on the folding landscape of larger proteins as opposed to smaller systems. We discuss how an understanding of energetic-entropic features in ordered proteins can pinpoint specific avenues through which folding mechanisms, populations of partially structured states and function can be engineered.
单域蛋白质通过多种机制折叠,这强调了能量学和结构之间的复杂关系,这是序列水平上功能约束和需求的直接结果。另一方面,在大型蛋白质中,阐明折叠机制与功能之间的相互作用具有挑战性,这是由于在实验中识别亚稳态的固有缺点以及与计算方法相关的采样限制所致。在这里,我们表明,由统计力学模型预测的大型系统(> 150 个残基)的自由能曲线和表面显示出广泛的折叠机制,具有普遍存在的折叠中间体和异构的天然集合。重要的是,配体结合或酶活性部位周围的残基显示出部分展开的更大趋势,这表现为配体结合域、转录抑制剂以及来自所有六个类别的代表性酶(包括 SARS-CoV-2 刺突蛋白的受体结合域(RBD)和蛋白酶 M)的折叠坐标中的中间体或激发态。因此,似乎相对更容易从较大蛋白质的折叠景观中提取功能的印记,而不是从较小的系统中提取。我们讨论了如何理解有序蛋白质中的能量熵特征,可以指出通过哪些途径可以设计折叠机制、部分结构状态和功能。