The expressive amount of nucleotide sequences from diverse plant species in databanks enables the use of computational approaches to discovery still unidentified genes and to infer about their function, structure and role in some biological processes. Of special interest are the antimicrobial peptides (AMP), whose functionalities have a very important role in defense against microbial infection in multicellular eukaryotes, being considered less susceptible to bacterial resistance than traditional antibiotics, with potential to develop a new class of therapeutic agents. Recent computational developments have provided various algorithms and resources to profit from the overwhelming information in data banks for biomining such peptides. This review focuses on the computational and bioinformatic approaches so far used for the identification of antimicrobial peptides in plant systems, highlighting alternative means of mining the entire plant peptide space that has recently become available.
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