Intelligent mining, engineering, and <i>de novo</i> design of proteins.

Cui LIU; Zhenkun SHI; Hongwu MA; Xiaoping LIAO

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Intelligent mining, engineering, and de novo design of proteins.

Author: Cui LIU ¹ ; Zhenkun SHI ¹ ; Hongwu MA ¹ ; Xiaoping LIAO ¹
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1. Biodesign Center, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.
Publication Type:English Abstract
Keywords: biomanufacturing; de novo design; enzyme mining; evaluation; protein engineering
MeSH: Protein Engineering/methods*; Artificial Intelligence; Proteins/genetics*; Computational Biology; Machine Learning; Data Mining; Algorithms; Deep Learning
From: Chinese Journal of Biotechnology 2025;41(3):993-1010
CountryChina
Language:Chinese
Abstract: 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.