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A unified model for de novo design of elastin-like polypeptides with tunable inverse transition temperatures

机译:具有可调反向转化温度的弹性蛋白样多肽从头设计的统一模型

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摘要

Elastin-like polypeptides (ELPs) are stimulus responsive peptide polymers that exhibit inverse temperature phase transition behavior, causing an ELP to aggregate above its inverse transition temperature (Tt). Although this property has been exploited in a variety of biotechnological applications, de novo design of ELPs that display a specific Tt is not trivial because the Tt of an ELP is a complex function of several variables, including its sequence, chain length, polypeptide concentration, and the type and concentration of cosolutes in solution. This paper provides a quantitative model that predicts the Tt of a family of ELPs (Val-Pro-Gly-Xaa-Gly, where Xaa = Ala and/or Val) from their composition, chain length, and concentration in phosphate buffered saline. This model will enable de novo prediction of the amino acid sequence and chain length of ELPs that will display a predetermined Tt in physiological buffer within a specified concentration regime, thereby greatly facilitating the design of new ELPs for applications in medicine and biotechnology.
机译:弹性蛋白样多肽(ELPs)是刺激反应性肽聚合物,表现出逆温度相变行为,导致ELP聚集在逆温度(Tt)以上。尽管此属性已在多种生物技术应用中得到开发,但从头设计显示特定Tt的ELP并非易事,因为ELP的Tt是多个变量的复杂函数,包括其序列,链长,多肽浓度,以及溶液中溶质的类型和浓度。本文提供了一种定量模型,可根据其组成,链长和磷酸盐缓冲液中的浓度预测ELP(Val-Pro-Gly-Xaa-Gly,其中Xaa = Ala和/或Val)家族的Tt。该模型将能够从头预测ELP的氨基酸序列和链长,这些氨基酸和链长将在指定浓度范围内在生理缓冲液中显示出预定的Tt,从而大大简化了用于医学和生物技术领域的新ELP的设计。

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