Enzyme property prediction using artificial intelligence

Journal Article · Mon Dec 22 00:00:00 EST 2025 · Current Opinion in Chemical Engineering

DOI:https://doi.org/10.1016/j.coche.2025.101208· OSTI ID:3028996

Yuan, Le ^[1]; Shafaei, Saman ^[1]; Zhao, Huimin ^[1]

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1. University of Illinois at Urbana-Champaign, IL (United States)

Artificial intelligence (AI)-driven enzyme property prediction enables rapid discovery and engineering of enzymes for a wide range of biotechnological and therapeutic applications. Here, we first introduce the key components in AI model development, including enzyme datasets, protein representation methods, and model architectures. We then highlight a variety of AI tools developed for the prediction of enzyme properties and functional annotations, including enzyme structure, kinetic parameters, substrate specificity, thermostability, solubility, Enzyme Commission number, and Gene Ontology term. Moreover, we describe representative downstream applications enabled by these AI tools. Finally, we discuss some challenges and opportunities as well as future prospects.

• Research Organization: University of Illinois at Urbana-Champaign, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Grant/Contract Number: SC0018420
• OSTI ID: 3028996
• Journal Information: Current Opinion in Chemical Engineering, Journal Name: Current Opinion in Chemical Engineering Vol. 51; ISSN 2211-3398
• Publisher: Elsevier
• Country of Publication: United States
• Language: English