Accelerating the discovery of industrial PET-degrading enzymes: Evolving paradigms from bioprospecting to computational discovery.

AI-assisted and structure-guided methods have advanced the discovery of PET-degrading enzymes with improved industrial relevance, surpassing traditional bioprospecting.

• Why it matters: Addressing PET waste is critical for environmental sustainability, but enzyme deployment faces challenges like substrate heterogeneity, thermal stability, and activity loss, limiting practical recycling solutions.
• What they did: The review compares discovery approaches—phenotype-driven bioprospecting, sequence mining, structure-guided searches, and AI prioritization—focusing on throughput, novelty, and industrial fitness, emphasizing hierarchical validation and standardized characterization.
• The result: Integrating these methods and establishing open data standards will enable identification of robust, application-ready enzymes, advancing efficient, circular PET recycling technologies.