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自动化蛋白质设计的最新进展及其未来的挑战。

Recent advances in automated protein design and its future challenges.

机构信息

a Department of Computational Medicine and Bioinformatics , University of Michigan , Ann Arbor , MI , USA.

b Radiation Biology Branch , Center for Cancer Research, National Cancer Institute - NIH , Bethesda , MD , USA.

出版信息

Expert Opin Drug Discov. 2018 Jul;13(7):587-604. doi: 10.1080/17460441.2018.1465922. Epub 2018 Apr 25.

DOI:10.1080/17460441.2018.1465922
PMID:29695210
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6002944/
Abstract

Protein function is determined by protein structure which is in turn determined by the corresponding protein sequence. If the rules that cause a protein to adopt a particular structure are understood, it should be possible to refine or even redefine the function of a protein by working backwards from the desired structure to the sequence. Automated protein design attempts to calculate the effects of mutations computationally with the goal of more radical or complex transformations than are accessible by experimental techniques. Areas covered: The authors give a brief overview of the recent methodological advances in computer-aided protein design, showing how methodological choices affect final design and how automated protein design can be used to address problems considered beyond traditional protein engineering, including the creation of novel protein scaffolds for drug development. Also, the authors address specifically the future challenges in the development of automated protein design. Expert opinion: Automated protein design holds potential as a protein engineering technique, particularly in cases where screening by combinatorial mutagenesis is problematic. Considering solubility and immunogenicity issues, automated protein design is initially more likely to make an impact as a research tool for exploring basic biology in drug discovery than in the design of protein biologics.

摘要

蛋白质的功能取决于其结构,而结构又取决于相应的蛋白质序列。如果能够理解导致蛋白质形成特定结构的规则,那么就有可能通过从所需结构回溯到序列来改进甚至重新定义蛋白质的功能。自动化蛋白质设计试图通过计算来计算突变的影响,目的是实现比实验技术更激进或更复杂的转变。涵盖领域:作者简要概述了计算机辅助蛋白质设计的最新方法学进展,展示了方法学选择如何影响最终设计,以及自动化蛋白质设计如何用于解决被认为超出传统蛋白质工程范围的问题,包括为药物开发创建新的蛋白质支架。此外,作者还特别针对自动化蛋白质设计的未来挑战进行了探讨。专家意见:自动化蛋白质设计作为一种蛋白质工程技术具有潜力,特别是在组合诱变筛选有问题的情况下。考虑到溶解度和免疫原性问题,自动化蛋白质设计最初更有可能作为一种研究工具,用于在药物发现中探索基础生物学,而不是用于设计蛋白质生物制剂。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/35abf7a0830a/nihms967871f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/47b77ff646df/nihms967871f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/1f2771f55819/nihms967871f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/6168303e2ff3/nihms967871f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/35abf7a0830a/nihms967871f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/47b77ff646df/nihms967871f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/1f2771f55819/nihms967871f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/6168303e2ff3/nihms967871f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/683a/6002944/35abf7a0830a/nihms967871f4.jpg

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2
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Nature. 2017 Oct 5;550(7674):74-79. doi: 10.1038/nature23912. Epub 2017 Sep 27.
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