Zhang Hongkai, Xie Jia, Lerner Richard A
Department of Cell and Molecular Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
Department of Cell and Molecular Biology, The Scripps Research Institute, La Jolla, CA 92037, United States.
Biochem Biophys Res Commun. 2014 Nov 7;454(1):251-5. doi: 10.1016/j.bbrc.2014.10.085. Epub 2014 Oct 24.
Autocrine based selections from intracellular combinatorial antibody and peptide libraries have proven to be a powerful method for selection of agonists and identification of new therapeutic targets. However, success requires a case-by-case construction of a robust selection system which is a process that can be time consuming and expensive. Here we report a general system that takes advantage of the chemical rate acceleration caused by approximation of a membrane tethered ligand and its receptor. The system uses an artificial signal transduction and is, thus, agnostic to the endogenous signal transduction of the receptor-ligand system. This method allows analysis of receptor-ligand interactions and selection of molecules from large libraries that interact with receptors when they are in their natural milieu.
从细胞内组合抗体和肽库中进行基于自分泌的筛选，已被证明是一种筛选激动剂和鉴定新治疗靶点的强大方法。然而，成功需要针对具体情况构建一个强大的筛选系统，而这一过程可能既耗时又昂贵。在此，我们报告一种通用系统，该系统利用膜 tethered 配体及其受体的接近所引起的化学速率加速。该系统使用人工信号转导，因此与受体 - 配体系统的内源性信号转导无关。这种方法允许分析受体 - 配体相互作用，并从大型文库中筛选在自然环境中与受体相互作用的分子。
