Antimicrobial Peptides and Artificial Intelligence: Promising Tools for Sustainable Agriculture Practices

The use of pesticides, fertilizers, copper compounds, and antibiotics to control microbial diseases in crops has caused adverse effects on human health and the environment, as well as the emergence of multidrug-resistant phytopathogenic bacteria and fungi. In this sense, to minimize reliance on agricultural chemicals and protect the environment, current agricultural practices are integrating life sciences technologies, such as genomics, big data, and artificial intelligence. For instance, the discovery and design of antimicrobial peptides integrate these areas. These peptides have become ideal candidates for promoting sustainable agricultural models. They are small, amphipathic, and polycationic molecules with a complex and diverse mode of action, which makes it difficult for microbes to develop resistance. In this review, we present advances in artificial intelligence and computational approaches for antimicrobial peptide design, along with a pipeline for designing antimicrobial peptides that utilize computational and artificial intelligence strategies extensively employed in our research group. Besides, we summarize advances in peptide research as a promising strategy for sustainable agricultural practices.