Protein–protein interactions (PPIs) regulate many cellular processes and engineered PPIs have cell and gene therapy applications. Here, we introduce massively parallel PPI measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Lastly, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics-based energy terms to predict MP3-seq values. We find that AF-M-based models could be valuable for prescreening interactions but experimentally measuring interactions remains necessary to rank their strengths quantitatively.

蛋白质-蛋白质相互作用 （PPI） 调节许多细胞过程，工程化 PPI 具有细胞和基因治疗应用。在这里，我们介绍了通过测序进行大规模并行 PPI 测量 （MP3-seq），这是一种易于使用且高度可扩展的酵母双杂交方法，用于测量 PPI。在 MP3-seq 中，DNA 条形码与特定的蛋白质对相关联，并且可以通过测序读取条形码富集，从而直接测量相互作用强度。我们表明 MP3-seq 是高度定量的，并且可以扩展到超过 100,000 次交互。我们应用 MP3-seq 来表征合理设计的异二聚体家族之间的相互作用，并研究赋予卷曲螺旋相互作用特异性的元件。最后，我们使用 AlphaFold-Multimer （AF-M） 预测卷曲异二聚体结构，并根据基于物理的能量项训练线性模型以预测 MP3-seq 值。我们发现基于 AF-M 的模型对于预筛选交互作用可能很有价值，但仍然需要通过实验测量交互作用来定量地对它们的优势进行排序。