Styles Matthew J, Pixley Joshua A, Wei Tongyao, Basile Christopher, Lu Shannon S, Dickinson Bryan C
Department of Chemistry, University of Chicago, 5735 S. Ellis Ave., Chicago, IL 60637.
Chan Zuckerberg Biohub, Chicago, IL 60642.
bioRxiv. 2025 Jan 17:2025.01.06.631531. doi: 10.1101/2025.01.06.631531.
Proteins that selectively bind to a target of interest are foundational components of research pipelines, diagnostics, and therapeutics. Current immunization-based, display-based, and computational approaches for discovering binders are laborious and time-consuming - taking months or more, suffer from high false positives - necessitating extensive secondary screening, and have a high failure rate, especially for disordered proteins and other challenging target classes. Here we establish Phage-Assisted Non-Continuous Selection of Protein Binders (PANCS-binders), an selection platform that links the life cycle of M13 phage to target protein binding though customized proximity-dependent split RNA polymerase biosensors, allowing for complete and comprehensive high-throughput screening of billion-plus member protein variant libraries with high signal-to-noise. We showcase the utility of PANCS-Binders by screening multiple protein libraries each against a panel of 95 separate therapeutically relevant targets, thereby individually assessing over 10 protein-protein interaction pairs, completed in two days. These selections yielded large, high-quality datasets and hundreds of novel binders, which we showed can be affinity matured or directly used in mammalian cells to inhibit or degrade targets. PANCS-Binders dramatically accelerates and simplifies the binder discovery process, the democratization of which will help unlock new creative potential in proteome-targeting with engineered binder-based biotechnologies.
能够选择性结合目标物的蛋白质是研究流程、诊断和治疗的基础组成部分。目前用于发现结合物的基于免疫、展示和计算的方法既费力又耗时(需要数月甚至更长时间),假阳性率高(需要大量的二次筛选),且失败率高,尤其是对于无序蛋白质和其他具有挑战性的目标类别。在此,我们建立了噬菌体辅助的蛋白质结合物非连续筛选(PANCS-结合物),这是一种筛选平台,它通过定制的依赖于邻近性的分裂RNA聚合酶生物传感器将M13噬菌体的生命周期与目标蛋白质结合联系起来,从而能够对数十亿成员的蛋白质变体文库进行完整且全面的高通量筛选,且具有高信噪比。我们通过针对95个不同的治疗相关靶点的面板筛选多个蛋白质文库,展示了PANCS-结合物的实用性,从而在两天内单独评估了超过10个蛋白质-蛋白质相互作用对。这些筛选产生了大量高质量的数据集和数百种新型结合物,我们表明这些结合物可以进行亲和力成熟或直接用于哺乳动物细胞中以抑制或降解靶点。PANCS-结合物极大地加速并简化了结合物发现过程,其普及将有助于利用基于工程化结合物的生物技术释放蛋白质组靶向方面的新创造潜力。