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    Item type:Publication,
    A 2026 Update on Computational Approaches to the Discovery and Design of Antimicrobial Peptides
    (MDPI AG, 2026)
    Agüero-Chapin, Guillermin
    ;
    Antunes, Agostinho
    ;
    Antimicrobial resistance (AMR) continues to stand as a critical global healthcare challenge. Current projections suggest that AMR could become the leading cause of death by 2050, potentially surpassing cancer mortality rates [1]. The urgency for novel therapeutic agents was further underscored by the 2020 pandemic, which shifted antibiotic consumption patterns and accelerated the emergence of multidrug-resistant (MDR) “superbugs” [2]. In this precarious landscape, Antimicrobial Peptides (AMPs) represent a transformative frontier. Unlike traditional antibiotics, AMPs typically target microbial membranes, a mechanism that significantly diminishes the likelihood of resistance development [3,4]. The conventional discovery of AMPs is a laboratory-intensive process often hampered by prohibitive costs and protracted timelines. This Special Issue, “A 2026 Update on Computational Approaches to the Discovery and Design of Antimicrobial Peptides”, showcases the power of in silico methodologies to accelerate the identification and optimization of these therapeutic candidates [5]. ©The authors ©MDPI.