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一种用于选择和进化抗聚集蛋白的体内平台。

An in vivo platform to select and evolve aggregation-resistant proteins.

机构信息

Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, LS2 9JT, UK.

School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK.

出版信息

Nat Commun. 2020 Apr 14;11(1):1816. doi: 10.1038/s41467-020-15667-1.

DOI:10.1038/s41467-020-15667-1
PMID:32286330
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7156504/
Abstract

Protein biopharmaceuticals are highly successful, but their utility is compromised by their propensity to aggregate during manufacture and storage. As aggregation can be triggered by non-native states, whose population is not necessarily related to thermodynamic stability, prediction of poorly-behaving biologics is difficult, and searching for sequences with desired properties is labour-intensive and time-consuming. Here we show that an assay in the periplasm of E. coli linking aggregation directly to antibiotic resistance acts as a sensor for the innate (un-accelerated) aggregation of antibody fragments. Using this assay as a directed evolution screen, we demonstrate the generation of aggregation resistant scFv sequences when reformatted as IgGs. This powerful tool can thus screen and evolve 'manufacturable' biopharmaceuticals early in industrial development. By comparing the mutational profiles of three different immunoglobulin scaffolds, we show the applicability of this method to investigate protein aggregation mechanisms important to both industrial manufacture and amyloid disease.

摘要

蛋白质生物制药非常成功,但它们在制造和储存过程中容易聚集,这限制了它们的用途。由于聚集可能由非天然状态触发,而这些状态的出现与热力学稳定性不一定相关,因此预测不良生物制剂的行为非常困难,而寻找具有所需特性的序列则是劳动密集型且耗时的。在这里,我们展示了一种在大肠杆菌周质中进行的测定,该测定将聚集直接与抗生素抗性联系起来,可作为抗体片段固有(非加速)聚集的传感器。使用该测定作为定向进化筛选,我们展示了当重新格式化为 IgG 时,聚集抗性 scFv 序列的生成。因此,这个强大的工具可以在工业开发的早期筛选和改进“可制造”的生物制药。通过比较三种不同免疫球蛋白支架的突变谱,我们证明了该方法适用于研究对工业制造和淀粉样变性疾病都很重要的蛋白质聚集机制。

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The Role of Protein Thermodynamics and Primary Structure in Fibrillogenesis of Variable Domains from Immunoglobulin Light Chains.蛋白质热力学和一级结构在免疫球蛋白轻链可变区纤维形成中的作用。
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AggNet: Advancing protein aggregation analysis through deep learning and protein language model.AggNet:通过深度学习和蛋白质语言模型推进蛋白质聚集分析。
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