Department of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.
Methods Mol Biol. 2022;2376:373-386. doi: 10.1007/978-1-0716-1716-8_21.
Mutational perturbations of protein structures, i.e., phi-value analysis, are commonly employed to probe the extent of involvement of a particular residue in the rate-determining step(s) of folding. This generally involves the measurement of folding thermodynamic parameters and kinetic rate constants for the wild-type and mutant proteins. While computational approaches have been reasonably successful in understanding and predicting the effect of mutations on folding thermodynamics, it has been challenging to explore the same on kinetics due to confounding structural, energetic, and dynamic factors. Accordingly, the frequent observation of fractional phi-values (mean of ~0.3) has resisted a precise and consistent interpretation. Here, we describe how to construct, parameterize, and employ a simple one-dimensional free energy surface model that is grounded in the basic tenets of the energy landscape theory to predict and simulate the effect of mutations on folding kinetics. As a proof of principle, we simulate one-dimensional free energy profiles of 806 mutations from 24 different proteins employing just the experimental destabilization as input, reproduce the relative unfolding activation free energies with a correlation of 0.91, and show that the mean phi-value of 0.3 essentially corresponds to the extent of stabilization energy gained at the barrier top while folding.
蛋白质结构的突变扰动,即 phi 值分析,通常用于探测特定残基在折叠速率决定步骤中的参与程度。这通常涉及对野生型和突变型蛋白质的折叠热力学参数和动力学速率常数的测量。虽然计算方法在理解和预测突变对折叠热力学的影响方面取得了相当大的成功,但由于结构、能量和动力学因素的混杂,探索同样的因素在动力学方面具有挑战性。因此,分数 phi 值(平均值约为 0.3)的频繁观察抵制了精确和一致的解释。在这里,我们描述了如何构建、参数化和使用一个简单的一维自由能表面模型,该模型基于能量景观理论的基本原理,以预测和模拟突变对折叠动力学的影响。作为一个原理的证明,我们仅使用实验失稳作为输入,模拟了 24 种不同蛋白质的 806 种突变的一维自由能分布,再现了相对展开激活自由能的相关性为 0.91,并表明 0.3 的平均 phi 值本质上对应于折叠时在势垒顶部获得的稳定化能量的程度。