| Summary: | <i>Fusarium oxysporum</i> remains one of the leading causes of economic losses and poor crop yields; its detection is strained due to its presentation in various morphological and physiological forms. This research work sought to identify novel biomarkers for the detection of <i>Fusarium oxysporum</i> using in silico approaches. Experimentally validated anti-<i>Fusarium oxysporum</i> antimicrobial peptides (AMPs) were used to construct a profile against <i>Fusarium oxysporum</i>. The performance and physicochemical parameters of these peptides were predicted. The gene for the <i>Fusarium oxysporum</i> receptor protein PR-1-like Protein, Fpr1, was identified and translated. The resulting protein model from the translation was then validated. The anti-<i>Fusarium oxysporum</i> AMPs and <i>Fusarium oxysporum</i> receptor protein 3-D structures were characterized, and their docking interaction analyses were carried out. The HMMER in silico tool identified novel anti-<i>Fusarium oxysporum</i> antimicrobial peptides with good performance in terms of accuracy, sensitivity, and specificity. These AMPs also displayed good physicochemical properties and bound with greater affinity to <i>Fusarium oxysporum</i> protein receptor PR-1-like Protein. The tendency of these AMPs to precisely detect <i>Fusarium oxysporum</i> PR-1-like Protein, Fpr1, would justify their use for the identification of the fungus. This study would enhance and facilitate the identification of <i>Fusarium oxysporum</i> to reduce problems associated with poor crop yield, economic losses, and decreased nutritional values of plants to keep up with the growing population.
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