Antimicrobial resistance is one of the emerging health issues in the world today, which has led to the necessity of finding new and effective antimicrobial agents. The medicinal plant Moringa oleifera Lam. was used to determine possible antimicrobial peptides (AMPs) by computational (in silico) techniques. The protein sequences of M. oleifera were retrieved from the National Center for Biotechnology Information (NCBI) and explored through a series of bioinformatics software to predict the peptide regions that have antimicrobial potential. The expected peptide was also characterised in terms of its physicochemical characteristics and structure. Molecular docking of the designed peptide was done to test its interaction with Staphylococcus aureus. This research shows that the in silico method is applicable in the rapid and low-cost screening of bioactive peptides before laboratory testing. The findings showed that the peptide from M. oleifera may be used as a good source of natural AMPs. However, it is advisable to further verify the antimicrobial activity of these peptides experimentally to determine their efficacy and test their application against multidrug-resistant pathogens.
