<p>Artificial intelligence (AI) has revolutionized the protein engineering process from multiple aspects, including representing protein information, generating protein designs, and evaluating protein properties. This review aims to introduce the recent progress of AI in protein research. We first introduce how AI models represent protein sequences, structures, and other properties. Further, the applications of generative models in protein design are introduced. The use of predictive models and smart agents in the evaluation process is then discussed, including high-precision protein property simulation and wet lab experimental design. Additionally, we discuss the future development of AI in protein research and the potential challenges it may encounter.</p>

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AI4Protein: transforming the future of protein design

  • Dequan Wang,
  • Zheling Tan,
  • Jin Gao,
  • Shaoting Zhang,
  • Jiaqi Shen,
  • Yuming Lu

摘要

Artificial intelligence (AI) has revolutionized the protein engineering process from multiple aspects, including representing protein information, generating protein designs, and evaluating protein properties. This review aims to introduce the recent progress of AI in protein research. We first introduce how AI models represent protein sequences, structures, and other properties. Further, the applications of generative models in protein design are introduced. The use of predictive models and smart agents in the evaluation process is then discussed, including high-precision protein property simulation and wet lab experimental design. Additionally, we discuss the future development of AI in protein research and the potential challenges it may encounter.