Computational Biomolecular Dynamics Group, Max-Planck Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany.
J Phys Chem Lett. 2021 Apr 1;12(12):3195-3201. doi: 10.1021/acs.jpclett.1c00380. Epub 2021 Mar 24.
Correlated mutations have played a pivotal role in the recent success in protein fold prediction. Understanding nonadditive effects of mutations is crucial for altering protein structure, as mutations of multiple residues may change protein stability or binding affinity in a manner unforeseen by the investigation of single mutants. While the couplings between amino acids can be inferred from homologous protein sequences, the physical mechanisms underlying these correlations remain elusive. In this work we demonstrate that calculations based on the first-principles of statistical mechanics are capable of capturing the effects of nonadditivities in protein mutations. The identified thermodynamic couplings cover the short-range as well as previously unknown long-range correlations. We further explore a set of mutations in staphyloccocal nuclease to unravel an intricate interaction pathway underlying the correlations between amino acid mutations.
相关突变在蛋白质折叠预测的近期成功中发挥了关键作用。了解突变的非加性效应对于改变蛋白质结构至关重要，因为多个残基的突变可能会以单突变体研究无法预见的方式改变蛋白质稳定性或结合亲和力。虽然氨基酸之间的耦合可以从同源蛋白质序列中推断出来，但这些相关性背后的物理机制仍然难以捉摸。在这项工作中，我们证明了基于统计力学的第一性原理计算能够捕捉蛋白质突变中非加性的影响。所确定的热力学耦合涵盖了短程以及以前未知的长程相关性。我们进一步研究了葡萄球菌核酸酶中的一组突变，以揭示氨基酸突变之间相关性的复杂相互作用途径。
