Mesh : Membrane Proteins / metabolism Receptor, IGF Type 2 / metabolism Lysosomes / metabolism Protein Transport Cations / metabolism

来  源:   DOI:10.1021/jacs.3c07687

Abstract:
Membrane proteins are a crucial class of therapeutic targets that remain challenging to modulate using traditional occupancy-driven inhibition strategies or current proteolysis-targeting degradation approaches. Here, we report that the inherent endolysosomal sorting machinery can be harnessed for the targeted degradation of membrane proteins. A new degradation technique, termed signal-mediated lysosome-targeting chimeras (SignalTACs), was developed by genetically fusing the signaling motif from the cation-independent mannose-6-phosphate receptor (CI-M6PR) to a membrane protein binder. Antibody-based SignalTACs were constructed with the CI-M6PR signal peptides fused to the C-terminus of both heavy and light chains of IgG. We demonstrated the scope of this platform technology by degrading five pathogenesis-related membrane proteins, including HER2, EGFR, PD-L1, CD20, and CD71. Furthermore, two simplified constructs of SignalTACs, nanobody-based and peptide-based SignalTACs, were created and shown to promote the lysosomal degradation of target membrane proteins. Compared to the parent antibodies, SignalTACs exhibited significantly higher efficiency in inhibiting tumor cell growth both in vitro and in vivo. This work provides a simple, general, and robust strategy for degrading membrane proteins with molecular precision and may represent a powerful platform with broad research and therapeutic applications.
摘要:
膜蛋白是一类关键的治疗靶标,使用传统的占用驱动的抑制策略或当前的蛋白水解靶向降解方法进行调节仍然具有挑战性。这里,我们报告说,固有的内溶酶体分选机制可以用于膜蛋白的靶向降解。一种新的降解技术,称为信号介导的溶酶体靶向嵌合体(SignalTACs),是通过将非阳离子依赖性甘露糖-6-磷酸受体(CI-M6PR)的信号基序与膜蛋白结合剂进行遗传融合而开发的。基于抗体的SignalTAC用与IgG的重链和轻链两者的C末端融合的CI-M6PR信号肽构建。我们通过降解五种发病机制相关的膜蛋白来证明该平台技术的范围,包括HER2,EGFR,PD-L1、CD20和CD71。此外,SignalTAC的两个简化结构,基于纳米抗体和基于肽的SignalTACs,被创建并显示出促进目标膜蛋白的溶酶体降解。与亲本抗体相比,SignalTAC在体外和体内抑制肿瘤细胞生长方面均表现出显着更高的效率。这项工作提供了一个简单的,一般,以及以分子精度降解膜蛋白的强大策略,可能代表具有广泛研究和治疗应用的强大平台。
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