Center for Synthetic Biology, Technical University of Darmstadt, 64287, Darmstadt, Germany.
Department of Biology, Technical University of Darmstadt, 64287, Darmstadt, Germany.
Adv Sci (Weinh). 2023 Oct;10(28):e2303496. doi: 10.1002/advs.202303496. Epub 2023 Aug 10.
Domain insertion engineering is a promising approach to recombine the functions of evolutionarily unrelated proteins. Insertion of light-switchable receptor domains into a selected effector protein, for instance, can yield allosteric effectors with light-dependent activity. However, the parameters that determine domain insertion tolerance and allostery are poorly understood. Here, an unbiased screen is used to systematically assess the domain insertion permissibility of several evolutionary unrelated proteins. Training machine learning models on the resulting data allow to dissect features informative for domain insertion tolerance and revealed sequence conservation statistics as the strongest indicators of suitable insertion sites. Finally, extending the experimental pipeline toward the identification of switchable hybrids results in opto-chemogenetic derivatives of the transcription factor AraC that function as single-protein Boolean logic gates. The study reveals determinants of domain insertion tolerance and yielded multimodally switchable proteins with unique functional properties.
结构域插入工程是一种很有前途的方法，可以将进化上无关的蛋白质的功能重新组合在一起。例如，将光控受体结构域插入到选定的效应蛋白中，可以得到具有光依赖性活性的变构效应物。然而，决定结构域插入容忍度和变构的参数还了解甚少。在这里，我们采用一种无偏的筛选方法，系统地评估了几种进化上无关的蛋白质的结构域插入允许性。对所得数据进行机器学习模型训练，可以解析出与结构域插入容忍度相关的特征，并揭示序列保守性统计数据是合适插入位点的最强指标。最后，将实验管道扩展到可切换杂交体的鉴定，得到转录因子 AraC 的光化学遗传衍生物，它们可以作为单蛋白布尔逻辑门。该研究揭示了结构域插入容忍度的决定因素，并产生了具有独特功能特性的多模态可切换蛋白。
