<i>De novo</i> protein design in the age of artificial intelligence.

Nan LIU; Xiaocheng JIN; Chongzhou YANG; Ziyang WANG; Xiaoping MIN; Shengxiang GE

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De novo protein design in the age of artificial intelligence.

Author: Nan LIU ¹ ; Xiaocheng JIN ¹ ; Chongzhou YANG ² ; Ziyang WANG ² ; Xiaoping MIN ² ; Shengxiang GE ¹
Author Information

1. State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361005, Fujian, China.
2. Institute of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen 361005, Fujian, China.
Publication Type:English Abstract
Keywords: artificial intelligence; de novo protein design; deep learning; diffusion model
MeSH: Artificial Intelligence; Proteins/chemistry*; Algorithms; Protein Engineering/methods*; Deep Learning
From: Chinese Journal of Biotechnology 2024;40(11):3912-3929
CountryChina
Language:Chinese
Abstract: Proteins with specific functions and characteristics play a crucial role in biomedicine and nanotechnology. De novo protein design enables the customization of sequences to produce proteins with desired structures that do not exist in the nature. In recent years, with the rapid development of artificial intelligence (AI), deep learning-based generative models have increasingly become powerful tools, enabling the design of functional proteins with atomic-level precision. This article provides an overview of the evolution of de novo protein design, with focus on the latest algorithmic models, and then analyzes existing challenges such as low design success rates, insufficient accuracy, and dependence on experimental validation. Furthermore, this article discusses the future trends in protein design, aiming to provide insights for researchers and practitioners in this field.