蛋白元件的智能挖掘、改造和从头设计  

Intelligent mining,engineering,and de novo design of proteins

作　　者：刘翠 史振坤 马红武[1,2] 廖小平 LIU Cui;SHI Zhenkun;MA Hongwu;LIAO Xiaoping(Biodesign Center,Tianjin Institute of Industrial Biotechnology,Chinese Academy of Sciences,Tianjin 300308,China;National Center of Technology Innovation for Synthetic Biology,Tianjin 300308,China)

机构地区：[1]中国科学院天津工业生物技术研究所,天津300308 [2]国家合成生物技术创新中心,天津300308

出　　处：《生物工程学报》2025年第3期993-1010,共18页Chinese Journal of Biotechnology

基　　金：中国科学院战略性先导科技专项(XDC0110203);国家自然科学基金(12326611)。

摘　　要：天然元件服务于细胞长期进化获得的生存本能,难以满足工程细胞在工业等特殊环境下高效执行生物功能的需求。酶作为生物催化剂,在生物合成途径中发挥着关键作用,它们能够显著提高生化反应的速率和选择性。然而,天然酶的催化效率、稳定性、底物特异性和耐受性等方面往往不能满足工业生产的需求。因此,挖掘、设计和改造酶以适应特定的生物制造过程至关重要。近年来,人工智能(artificial intelligence,AI)技术在蛋白的挖掘、评估、改造和从头设计中发挥着越来越重要的作用。AI技术可以通过机器学习和深度学习算法,分析大量的生物信息学数据,预测蛋白的功能和特性,从而加速蛋白的发现和优化过程。此外,AI还可以辅助科研人员从头设计新的蛋白结构,通过模拟和预测其在不同条件下的性能,为蛋白的设计提供指导。本文综述了面向生物制造的蛋白元件挖掘、评估、改造以及从头设计的最新研究进展,探讨了该领域的热点问题、难点以及新兴技术方法,旨在为相关领域的科研工作提供指导。Natural components serve the survival instincts of cells that are obtained through long-term evolution,while they often fail to meet the demands of engineered cells for efficiently performing biological functions in special industrial environments.Enzymes,as biological catalysts,play a key role in biosynthetic pathways,significantly enhancing the rate and selectivity of biochemical reactions.However,the catalytic efficiency,stability,substrate specificity,and tolerance of natural enzymes often fall short of industrial production requirements.Therefore,exploring and modifying enzymes to suit specific biomanufacturing processes has become crucial.In recent years,artificial intelligence(AI)has played an increasingly important role in the discovery,evaluation,engineering,and de novo design of proteins.AI can accelerate the discovery and optimization of proteins by analyzing large amounts of bioinformatics data and predicting protein functions and characteristics by machine learning and deep learning algorithms.Moreover,AI can assist researchers in designing new protein structures by simulating and predicting their performance under different conditions,providing guidance for protein design.This paper reviews the latest research advances in protein discovery,evaluation,engineering,and de novo design for biomanufacturing and explores the hot topics,challenges,and emerging technical methods in this field,aiming to provide guidance and inspiration for researchers in related fields.

关 键 词：生物制造 酶挖掘 评估 蛋白改造 从头设计 

分 类 号：Q81[生物学—生物工程]