上位性和多效性形成与耐药相关的生物物理蛋白亚空间

C. Brandon Ogbunugafor, Rafael F. Guerrero, Miles D. Miller-Dickson, Eugene I. Shakhnovich, Matthew D. Shoulders
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引用次数: 0

摘要

蛋白质空间是基因型-表型图谱的丰富类比,其中氨基酸序列被组织成高维空间,突出了蛋白质变体之间的连通性。这是一个有用的抽象来理解进化过程,并努力工程蛋白质向理想的表型。很少有人提到蛋白质空间,考虑如何用它们的生物物理成分来描述蛋白质表型,也没有严格地询问诸如作用(描述突变及其表型后果之间的非线性相互作用)之类的力量如何在这些成分中表现出来。在这项研究中,我们解构了细菌酶的低维蛋白质空间(二氢叶酸还原酶;DHFR)转化为对应于一组动力学和热力学特征的“子空间”[${k}_{\ mathm {cat}}, {k}_{M}, {k}_{i}$,和${T}_{M} $(熔化温度)]。然后,我们研究了三个突变(总共八个等位基因)的组合如何显示多效性,或对单个子空间性状的独特影响。我们研究了三种同源DHFR酶(大肠杆菌、灰色李斯特菌和muridarum衣原体)的蛋白质空间,增加了基因型背景维度,通过该维度,上位性发生在亚空间中。在这样做的过程中,我们揭示了蛋白质空间是一个看似复杂的概念,未来在生物工程中的应用应该考虑氨基酸取代之间的相互作用如何在不同的表型亚空间中表现出来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Epistasis and pleiotropy shape biophysical protein subspaces associated with drug resistance
Protein space is a rich analogy for genotype-phenotype maps, where amino acid sequence is organized into a high-dimensional space that highlights the connectivity between protein variants. It is a useful abstraction for understanding the process of evolution, and for efforts to engineer proteins towards desirable phenotypes. Few mentions of protein space consider how protein phenotypes can be described in terms of their biophysical components, nor do they rigorously interrogate how forces like epistasis---describing the nonlinear interaction between mutations and their phenotypic consequences---manifest across these components. In this study, we deconstruct a low-dimensional protein space of a bacterial enzyme (dihydrofolate reductase; DHFR) into ``subspaces'' corresponding to a set of kinetic and thermodynamic traits [${k}_{\mathrm{cat}}, {K}_{M}, {K}_{i}$, and ${T}_{m}$ (melting temperature)]. We then examine how combinations of three mutations (eight alleles in total) display pleiotropy, or unique effects on individual subspace traits. We examine protein spaces across three orthologous DHFR enzymes (Escherichia coli, Listeria grayi, and Chlamydia muridarum), adding a genotypic context dimension through which epistasis occurs across subspaces. In doing so, we reveal that protein space is a deceptively complex notion, and that future applications to bioengineering should consider how interactions between amino acid substitutions manifest across different phenotypic subspaces.
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