Engineering defensins: Heterologous expression strategies from genetic engineering to synthetic biology

Defensins are a structurally diverse class of host defense peptides with broad-spectrum antimicrobial and immunomodulatory activities. Their broader applications in biomedicine and biotechnology, however, remain constrained by limited natural availability and difficulties associated with heterologous production, including low yields, host toxicity, inefficient folding, and loss of biological activity. In this review, we examine defensin production from an integrated engineering perspective, emphasizing the interplay between expression regulation, host physiology, and molecular design. We establish a multidimensional engineering framework that integrates genetic engineering, synthetic biology, and AI-driven design strategies to improve defensin production and functional optimization. In this context, synthetic biology provides a framework for programmable regulation of gene expression and host metabolism. Recent advances in artificial intelligence further enable data-driven prediction and redesign of defensin sequences and structures, extending optimization beyond naturally occurring sequence space. By integrating these complementary approaches, defensin engineering can progressively shift from empirical optimization toward rational and quantitatively informed design. This framework provides a conceptual basis for improving the production, functional stability, and manufacturability of defensins and for guiding the development of scalable production strategies.