Next-Generation Food Enzymology: From Metagenomic Discovery to AI-Driven Biocatalyst Design
Food enzymology is entering a new era driven by the convergence of metagenomics, artificial intelligence, and synthetic biology. While traditional food processes rely on a limited repertoire of established biocatalysts, metagenomic and multiomics approaches now provide access to vast reservoirs of unexplored enzymatic diversity. Simultaneously, advances in protein structure prediction, functional modeling, and de novo protein design are transforming enzyme discovery from a largely empirical process to a predictive discipline. In this Perspective, we discuss how these technologies will enable the development of tailored biocatalysts for sustainable, precise, and next-generation food processing applications.
Authors
- Mathieu Schwartz (ORCID: https://orcid.org/0000-0002-2670-5274)
- Fabrice Neiers (ORCID: https://orcid.org/0000-0002-8965-4929)
- Camille Loupiac (ORCID: https://orcid.org/0000-0003-2343-0313)
- Adrien Nicolaı̈ (ORCID: https://orcid.org/0000-0001-7779-4652)
- Didier Hocquet (ORCID: https://orcid.org/0000-0002-4192-7238)
- Ruben Ladeira (ORCID: https://orcid.org/0009-0006-9113-1381)
Institutions
- Institut National de la Recherche Agronomique (MA)
- Laboratoire Interdisciplinaire Carnot de Bourgogne (FR)
- Université Bourgogne Europe (FR)
- Université Marie et Louis Pasteur (FR)
- Université de Franche-Comté (FR)
Publication Details
- Journal
- Journal of Agricultural and Food Chemistry
- Published
- 2026-07-16
- DOI
- https://doi.org/10.1021/acs.jafc.6c04349
- Primary Topic
- Enzyme Catalysis and Immobilization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- Agence Nationale de la Recherche
- Conseil régional de Bourgogne-Franche-Comté