Demonstrates high prediction accuracy for enzymatic degradation of plastics utilizing language models, suggesting a novel approach for efficient protein design.
Plastic pollution poses a significant environmental threat, with PET comprising 12% of global solid waste. Enzymatic degradation provides a sustainable recycling method, yet optimizing enzymes for industrial use remains difficult. This study utilizes protein and polymer language models to predict plastic degradation from protein sequences and polymer SMILES. The approach demonstrates high prediction accuracy with key structural features revealed by language models, enabling efficient in silico screening for protein design.
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Xu et al. (2026) studied this question.
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