Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA.
Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA.
Science. 2020 Dec 11;370(6522). doi: 10.1126/science.aaz4910.
Determining structures of protein complexes is crucial for understanding cellular functions. Here, we describe an integrative structure determination approach that relies on in vivo measurements of genetic interactions. We construct phenotypic profiles for point mutations crossed against gene deletions or exposed to environmental perturbations, followed by converting similarities between two profiles into an upper bound on the distance between the mutated residues. We determine the structure of the yeast histone H3-H4 complex based on ~500,000 genetic interactions of 350 mutants. We then apply the method to subunits Rpb1-Rpb2 of yeast RNA polymerase II and subunits RpoB-RpoC of bacterial RNA polymerase. The accuracy is comparable to that based on chemical cross-links; using restraints from both genetic interactions and cross-links further improves model accuracy and precision. The approach provides an efficient means to augment integrative structure determination with in vivo observations.
确定蛋白质复合物的结构对于理解细胞功能至关重要。在这里，我们描述了一种依赖于体内遗传相互作用测量的综合结构测定方法。我们构建了针对点突变的表型图谱，这些突变与基因缺失或暴露于环境扰动交叉，然后将两个图谱之间的相似性转换为突变残基之间距离的上限。我们基于 350 个突变体的约 500,000 个遗传相互作用来确定酵母组蛋白 H3-H4 复合物的结构。然后，我们将该方法应用于酵母 RNA 聚合酶 II 的亚基 Rpb1-Rpb2 和细菌 RNA 聚合酶的亚基 RpoB-RpoC。准确性可与基于化学交联的方法相媲美；使用遗传相互作用和交联的约束条件进一步提高了模型的准确性和精度。该方法为利用体内观察结果增强综合结构测定提供了一种有效的手段。
