Antimicrobial peptides in malaria and tuberculosis management: a systematic review of emerging evidence

AMPs (Antimicrobial peptides) are small molecules that are crucial components of biological activities, viz wound healing, angiogenesis, antimicrobial activity, immune regulation, and exhibit anticancer properties. This systematic review summarizes the origin, sequence, efficacy, and structure-activity mechanisms of AMPs against tuberculosis and malaria, the world's leading killer infectious diseases, employing the AMP database (APD3) (till June 2025) and PubMed search (January 1965 to June 2025). The comprehension is well addressed by covering the inhibitory activity, SAR (structure-activity relationships), and action mechanisms of AMPs (natural and synthetic) against Mycobacterium tuberculosis and Plasmodium spp., as both pathogens exhibit multidrug resistance. The review also illustrates how these specific motifs, along with their properties such as hydrophobicity, charge, or amphipathicity, influence the AMPs activity against the pathogens. Moreover, challenges in the AMPs use and the way forward, including the recent breakthroughs employing nanocarriers, inhalable formulations for TB, and targeted erythrocyte delivery for malaria, are also highlighted. AMPs have illustrated promising anti-TB and antimalarial efficacy owing to their unique structure and novel mode of action, despite exhibiting varying extents of toxicity. Anti-malarial AMPs are grouped in defensins and cecropins, while the majority of natural anti-TB AMPs are classified as bacteriocins, defensins, and cathelicidins. Synthetic AMPs, in contrast, are designed to enhance activity and selectivity while reducing toxicity and the development of resistance. AMPs have α-helical, β-sheet, or random-coil structures and are cationic, amphipathic, and highly hydrophobic, attributes that contribute to observed anti-TB and anti-malarial potential. A comprehensive understanding of AMP's structure and function, along with the use of artificial intelligence (AI) and machine learning, can provide impetus for AMP therapy as an alternative to tackle tuberculosis and malaria.