Screening the γ-core Motif Peptides of Ascomycetous Antifungal Proteins for Antifungal Activity and Potential Therapeutic Applicability

The incidence of fungal infections has increased markedly in recent years, driven by increasing resistance to conventional antifungal agents. To address this challenge, the World Health Organization has highlighted the urgent need for novel antifungal molecules, particularly those that can enhance the efficacy of existing drugs. Synthetic peptides (γAFPs), derived from conserved γ-core motifs (GXC-X_{3 - 9}-C) of antifungal proteins, represent a potential source of such combination partners. Here, we systematically screened 19 γAFPs of various fungal origins and physicochemical properties to assess their activity and interaction with conventional agents. The intrinsic antifungal activity of these peptides was primarily governed by their net positive charge and hydrophilicity, with the charge-to-hydropathy ratio emerging as a strong predictor of efficacy. From this panel, two peptides (γAFP^B6GXZ8 from Penicillium rubens and γAFP^A0A2J5HZT4 from Aspergillus taichungensis) were identified as the leading candidates with potent antifungal activity mediated by the disruption of the plasma membrane. Although their standalone antifungal potency was modest, both peptides exhibited robust synergistic interactions with clinically used antifungal agents in vitro: γAFP^B6GXZ8 enhanced terbinafine efficacy against Candida albicans, while γAFP^A0A2J5HZT4 potentiated fluconazole activity against Aspergillus fumigatus. In a Galleria mellonella infection model, neither the peptides nor their combinations with conventional antifungal agents caused host toxicity, and effectively prevented C. albicans infection and prolonged the survival of larvae infected with A. fumigatus. These findings confirm that the synergistic effects observed in vitro can be maintained in vivo. Collectively, our findings identify two γ-core-derived peptides as well-tolerated synergistic co-therapeutics that augment antifungal drug efficacy and constitute promising templates for directed optimization.