实体肿瘤微环境中有利于pH依赖性结合的抗体突变:来自大规模结构计算的见解

Wanlei Wei, Christopher R. Corbeil, Francis Gaudreault, Christophe Deprez, E. Purisima, T. Sulea
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引用次数: 3

摘要

近年来,基于抗体的治疗方法在治疗各种肿瘤方面发展迅速。不幸的是,由于非肿瘤效应和细胞毒性,安全性问题仍然是治疗标准的一个重要问题。迫切需要改进以确保抗肿瘤药物的靶向递送。我们之前证明,在酸性条件下,在抗HER2抗体中加入组氨酸pH开关诱导选择性抗原结合(mab 2020;12:1682866)。由于癌蛋白在酸性实体肿瘤微环境中的优先靶向,这导致了安全性的提高。在这次成功之后,我们将这种方法扩展到一组400多种抗体结构,这些抗体结构与100多种不同的与实体瘤相关的人类癌蛋白结合在一起。计算表明,在酸性条件下,某些残基类型(即Trp、Arg和Tyr)的His突变可能更成功地诱导pH依赖性结合。此外,互补性决定区域内的10个位置也预计会取得更大的成功。结合起来,这两个可访问的指标可以作为基于序列的pH选择性结合工程的基础。这种方法可以应用于大多数缺乏详细结构表征的抗癌抗体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Antibody mutations favoring pH‐dependent binding in solid tumor microenvironments: Insights from large‐scale structure‐based calculations
Antibody‐based therapeutics for treatment of various tumors have grown rapidly in recent years. Unfortunately, safety issues, attributed to off‐tumor effects and cytotoxicity, are still a significant concern with the standard of care. Improvements to ensure targeted delivery of antitumor pharmaceuticals are desperately needed. We previously demonstrated that incorporating histidyl pH‐switches in an anti‐HER2 antibody induced selective antigen binding under acidic pH conditions (MAbs 2020;12:1682866). This led to an improved safety profile due to preferential targeting of the oncoprotein in the acidic solid tumor microenvironment. Following this success, we expanded this approach to a set of over 400 antibody structures complexed with over 100 different human oncoproteins, associated with solid tumors. Calculations suggested that mutations to His of certain residue types, namely Trp, Arg, and Tyr, could be significantly more successful for inducing pH‐dependent binding under acidic conditions. Furthermore, 10 positions within the complementarity‐determining region were also predicted to exhibit greater successes. Combined, these two accessible metrics could serve as the basis for a sequence‐based engineering of pH‐selective binding. This approach could be applied to most anticancer antibodies, which lack detailed structural characterization.
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