基于 Caspase 的融合蛋白技术:通过计算建模和仿真描述底物的可裂解性。

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL
Jakob Liu, Andreas Fischer, Monika Cserjan-Puschmann, Nico Lingg, Chris Oostenbrink
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引用次数: 0

摘要

基于 Caspase 的融合蛋白技术(CASPON)可普遍裂解相关蛋白质的融合标签,以重建原生 N-端。虽然 CASPON 酶已被优化为可对多种 N 端肽进行杂交,但对于较大的蛋白质,其裂解效率可能低得令人吃惊。我们根据内在无序 N 端肽的结构表征及其与 CASPON 酶的假定相互作用,开发出一种有效的方法来合理化和预测裂解效率。有利的 N 端相互作用构象的数量与实验观察到的裂解效率非常吻合,与构象选择模型一致。该方法依靠计算成本低廉的分子动力学模拟,有效地生成了一系列不同的 N 端构象,然后通过简单的拟合程序将其加入 CASPON 酶中。该方法可用于预先评估 CASPON 的可裂解性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Caspase-Based Fusion Protein Technology: Substrate Cleavability Described by Computational Modeling and Simulation.

Caspase-Based Fusion Protein Technology: Substrate Cleavability Described by Computational Modeling and Simulation.

The Caspase-based fusion protein technology (CASPON) allows for universal cleavage of fusion tags from proteins of interest to reconstitute the native N-terminus. While the CASPON enzyme has been optimized to be promiscuous against a diversity of N-terminal peptides, the cleavage efficacy for larger proteins can be surprisingly low. We develop an efficient means to rationalize and predict the cleavage efficiency based on a structural representation of the intrinsically disordered N-terminal peptides and their putative interactions with the CASPON enzyme. The number of favorably interacting N-terminal conformations shows a very good agreement with the experimentally observed cleavage efficiency, in agreement with a conformational selection model. The method relies on computationally cheap molecular dynamics simulations to efficiently generate a diverse collection of N-terminal conformations, followed by a simple fitting procedure into the CASPON enzyme. It can be readily used to assess the CASPON cleavability a priori.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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