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随机杂多聚物可保持蛋白质在异质环境中的功能。

Random heteropolymers preserve protein function in foreign environments.

机构信息

Department of Materials Science and Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.

Department of Materials Science and Engineering, Northwestern University, Evanston, IL 60208, USA.

出版信息

Science. 2018 Mar 16;359(6381):1239-1243. doi: 10.1126/science.aao0335.

Abstract

The successful incorporation of active proteins into synthetic polymers could lead to a new class of materials with functions found only in living systems. However, proteins rarely function under the conditions suitable for polymer processing. On the basis of an analysis of trends in protein sequences and characteristic chemical patterns on protein surfaces, we designed four-monomer random heteropolymers to mimic intrinsically disordered proteins for protein solubilization and stabilization in non-native environments. The heteropolymers, with optimized composition and statistical monomer distribution, enable cell-free synthesis of membrane proteins with proper protein folding for transport and enzyme-containing plastics for toxin bioremediation. Controlling the statistical monomer distribution in a heteropolymer, rather than the specific monomer sequence, affords a new strategy to interface with biological systems for protein-based biomaterials.

摘要

成功地将活性蛋白质纳入合成聚合物中,可以开发出一类具有仅在生命系统中才发现的功能的新材料。然而,蛋白质在适合聚合物加工的条件下很少发挥作用。基于对蛋白质序列趋势和蛋白质表面特征化学模式的分析,我们设计了四单体随机杂聚物,以模拟天然无序蛋白质,从而在非天然环境中实现蛋白质的溶解和稳定。这些杂聚物通过优化组成和统计单体分布,使膜蛋白在无细胞合成中实现正确的蛋白质折叠,用于运输,以及含有酶的塑料用于毒素生物修复。通过控制杂聚物中的统计单体分布,而不是特定的单体序列,为基于蛋白质的生物材料与生物系统进行接口提供了一种新策略。

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