Abstract
The emergence of bacterial resistance has reduced the efficacy of conventional antibiotics. As promising therapeutic candidates to treat infections, antimicrobial peptides (AMPs) emerge as an alternative for the control of microorganisms. AMPs have been found in several sources, including animals, plants and fungi, constituting early host defense against pathogens. As a very diverse group, these peptides represent a myriad of structures, which could lead to different mechanisms of action. However, currently, only approximately 2% of known AMP sequences have experimentally solved structures. Therefore, computational structure prediction is essential to improve our understanding of AMP structural diversity, origins and interactions with their targets. Hence, this chapter will focus on computational strategies that have been applied to predict AMP three-dimensional structure and how they have helped to expand our knowledge of the AMP structural universe, structure–function relationships and the development of more potent AMPs.
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