Artificial intelligence tools for enzyme engineering and metabolic engineering
Abstract
Enzyme engineering and metabolic engineering drive innovation in energy biotechnology. In recent years, artificial intelligence (AI) has supported successful applications in designing effective enzymes and productive microbial cell factories. This review summarizes recent advances in enzyme redesign using protein language models, de novo enzyme design with generative models, and AI tools for engineering metabolism and related cellular phenotypes. Across these areas, AI models are shifting from single modality inputs to integrated representations of protein function, metabolic pathways, and cell states. We emphasize that unifying the diverse data representations across scales will be necessary for advancements in energy biotechnology.
Fields of Study & Subjects
Microbial Metabolic Engineering and Bioproduction
Machine Learning in Bioinformatics
Genomics and Phylogenetic Studies
Publication details
- Journal / source
- Current Opinion in Biotechnology
- Publisher
- Elsevier BV
- Volume
- 100
- Pages
- 103522–103522
- Publication date
- 3 June 2026
- Language
- EN