用于大分子筛选和输送的蛋白质组条形码平台。

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Ning Wang, Nicole A. Mcneer, Elliot Eton, Josh Fass and Alex Kentsis*, 
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引用次数: 0

摘要

工程大分子为治疗人类疾病中传统上无法治疗的相互作用提供了令人信服的方法。然而,它们的疗效却受到组织和细胞内输送障碍的限制。受分子条形码和进化方面最新进展的启发,我们开发了 BarcodeBabel,这是一种设计肽条形码库的通用方法,适用于高通量质谱蛋白质组学。PeptideBabel 是一种蒙特卡洛抽样算法,用于设计具有可进化理化特性和序列复杂性的多肽,结合使用 PeptideBabel,我们开发出了具有独特理化特征的细胞穿透肽(CPPs)条形码库。通过定量靶向质谱分析,我们确定了具有更好的细胞核和细胞质递送能力的 CPPS,每个人体细胞的递送量超过数亿分子,同时保持最小的膜破坏和可忽略不计的体外毒性。这些研究证明了肽条形码作为大分子筛选和递送的同质高通量方法的概念。BarcodeBabel 和 PeptideBabel 可从 https://github.com/kentsisresearchgroup/ 获取开源信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Proteomic Barcoding Platform for Macromolecular Screening and Delivery

Proteomic Barcoding Platform for Macromolecular Screening and Delivery

Proteomic Barcoding Platform for Macromolecular Screening and Delivery

Engineered macromolecules offer compelling means for the therapy of conventionally undruggable interactions in human disease. However, their efficacy is limited by barriers to tissue and intracellular delivery. Inspired by recent advances in molecular barcoding and evolution, we developed BarcodeBabel, a generalized method for the design of libraries of peptide barcodes suitable for high-throughput mass spectrometry proteomics. Combined with PeptideBabel, a Monte Carlo sampling algorithm for the design of peptides with evolvable physicochemical properties and sequence complexity, we developed a barcoded library of cell penetrating peptides (CPPs) with distinct physicochemical features. Using quantitative targeted mass spectrometry, we identified CPPS with improved nuclear and cytoplasmic delivery exceeding hundreds of millions of molecules per human cell while maintaining minimal membrane disruption and negligible toxicity in vitro. These studies provide a proof of concept for peptide barcoding as a homogeneous high-throughput method for macromolecular screening and delivery. BarcodeBabel and PeptideBabel are available open-source from https://github.com/kentsisresearchgroup/.

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来源期刊
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
期刊介绍: Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".
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