Livestock plays a vital role in the economy of most Latin American and European countries. However, infections resulting in bovine mastitis can harm
this sector. Treatment relies on antibiotics, but their improper use may lead to microbial resistance and/or residues in animals and their by-products. In
this context, antimicrobial peptides inspired by natural innate immune systems emerge as an alternative for combating bovine mastitis, as these
molecules exhibit activity against various pathogens. Studies conducted under real-world conditions with the antimicrobial peptide cathelicidins have
demonstrated its effectiveness in treating bovine mastitis, showing low cytotoxicity and microbial resistance. Optimizing the antimicrobial peptide
cathelicidins through advanced artificial intelligence techniques, such as deep learning with convolutional neural networks and reinforcement learning,
is crucial for more effective, targeted, and sustainable treatments for bovine mastitis. This approach not only enhances the therapeutic potential of
cathelicidins but also supports the development of a scalable biotechnological product line, addressing a pressing challenge in animal health and
contributing to the sustainability of the livestock industry. An expert international collaborative team will identify and synthesize an estimated 50 novel
peptides per target and will refine and validate the interactions with pathogen targets using surface plasmon resonance. Subsequently, advanced in
vitro analytic techniques for structure evaluation will be followed by small-scale in vitro and in vivo experiments to produce therapeutic formulations for
commercialization. In this way, this project aims to strengthen secure food production through a bioeconomy approach, promoting the sustainable use
of biological resources to drive innovation in animal health.
