Applications of foldability in intelligent enzyme engineering and design: take AlphaFold2 for example

MENG Qiaozhen; GUO Fei

doi:10.12211/2096-8280.2023-011

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Applications of foldability in intelligent enzyme engineering and design: take AlphaFold2 for example

Invited Review | 更新时间：2025-03-20

- Applications of foldability in intelligent enzyme engineering and design: take AlphaFold2 for example
- Synthetic Biology Journal Vol. 4, Issue 3, Pages: 571-589(2023)
- 作者机构：
  
  1.天津大学智能与计算学部计算机学院，天津 300350
  2.中南大学计算机学院，湖南长沙 410000
- 作者简介：
- 基金信息：
- DOI：10.12211/2096-8280.2023-011
  CLC： Q816
- Received：06 February 2023，
  
  Revised：2023-03-28，
  
  Published：30 June 2023
- 稿件说明：
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孟巧珍，郭菲. “可折叠性”在酶智能设计改造中的应用研究——以AlphaFold2为例［J］. 合成生物学， 2023， 4（3）： 571-589

MENG Qiaozhen， GUO Fei. Applications of foldability in intelligent enzyme engineering and design： take AlphaFold2 for example［J］. Synthetic Biology Journal， 2023， 4（3）： 571-589
孟巧珍，郭菲. “可折叠性”在酶智能设计改造中的应用研究——以AlphaFold2为例［J］. 合成生物学， 2023， 4（3）： 571-589 DOI： 10.12211/2096-8280.2023-011.

MENG Qiaozhen， GUO Fei. Applications of foldability in intelligent enzyme engineering and design： take AlphaFold2 for example［J］. Synthetic Biology Journal， 2023， 4（3）： 571-589 DOI： 10.12211/2096-8280.2023-011.

摘要

天然酶具有绿色环保、高效催化的优点，但由于工业环境的酸碱性、温度等条件不够适宜，天然酶在实际工业生产中往往存在错误折叠、功能受限等问题。使用人工智能技术辅助酶的改造设计，相比传统方法具有高效、快速、低成本的优势，但在这个过程中大部分工作没有考虑设计改造酶的“可折叠性”问题。同时，最近几年来，以AlphaFold2为代表的蛋白质结构预测工具借助人工智能技术取得了突破性的进展，已经具有原子级别的结构预测精度。这一工具的日益成熟，不仅有助于对蛋白结构功能机制的了解，同时可以丰富现有酶结构数据，用于后续的研究。因此，基于现有酶改造以及从头设计新酶过程中出现的错误折叠导致成功率不高、实验验证成本高的问题，我们认为结合蛋白质结构预测工具辅助酶的改造设计任务，可以增加设计可靠酶的数量，同时降低实验成本。本文首先梳理回顾人工智能技术在酶设计改造中的应用，主要从序列和结构两个角度展开。然后将现有蛋白质结构预测工具归纳成四种类型分别介绍其设计原理和预测能力。接着以AlphaFold2为代表性工作，归纳了三种在现有技术基础上利用结构预测工具进一步提高酶改造的合理性以及酶设计的“可折叠性”的方式：①结构“分析器”；②突变“筛选器”；③折叠“监督器”。最后在讨论部分总结并提出了一些现有算法的不足和缺陷。随着人工智能技术的逐渐发展以及人类对蛋白质作用机理的研究，酶的改造设计精度一定会有所提高，这将助力合成生物学的快速发展。

Abstract

Natural enzymes often have advantages of environmental friendliness

high catalytic efficiency and so on. However

due to inappropriate pH

temperature and other conditions in industrial environment

the application of natural enzymes in industrial production is unsatisfactory owing to challenges such as misfolding of proteins and limited functions. Compared with traditional methods

enzyme design and engineering with the help of artificial intelligence (AI) have advantages of high efficiency

high speed and low cost

but most work does not consider the 'foldability' in the process of enzyme engineering. A designed enzyme may fold to another state for minimum energy

so called misfolding. As we all know

protein design is regarded as an inverse folding process. Can we utilize protein folding tools to constrain the foldability of the designed enzyme? In recent years

protein structure prediction tools represented by AlphaFold2 have made breakthroughs with the help of AI for accuracy at atomic levels

which enriches existing enzyme structure data for subsequent studies to address the above question. Therefore

we discuss applying protein structural tools to fulfill the task of enzyme design and engineering

increase the proportion of reliable enzymes designed and reduce the cost of experiments. Firstly

we review the application of artificial intelligence technology in enzyme design and engineering from the perspective of sequence and structure. Then

we summarize existing protein structure prediction tools into four types and introduce their methods and prediction ability respectively. Furthermore

taking AlphaFold2 as an example

we group the applications which improve the rationality of enzyme modification and the "foldability" of design into three categories: 1) Structure 'Analyzer'

2) Mutation 'Filter' and 3) Folding 'Monitor'. Finally

we highlight drawbacks with existing algorithms for further improvements. With the rapid development of AI and understanding on protein function mechanism

the precision of enzyme modifications and designs will be increased.

关键词

Keywords

references

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