DEEP LEARNING IN THE DISCOVERY OF NOVEL ANTIMICROBIAL PEPTIDES (AMPS) (Ustozlar uchun, 2026)
The rise of multi-drug resistant "superbugs" has necessitated a shift away from traditional small-molecule antibiotics toward Antimicrobial Peptides (AMPs)—nature’s ancient defense system. However, the chemical space for these peptides is vast, with trillions of potential combinations. This review evaluates the 2024–2026 revolution in "Digital Mining," where Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) have moved from experimental curiosities to essential tools. By scanning massive genomic databases and "resurrecting" molecules from extinct species, these models are predicting potent antimicrobial candidates with high accuracy before a single drop of liquid is touched in a lab.