Characterization and Classification In Silico of Peptides with Dual Activity (Antimicrobial and Wound Healing)

dc.contributor.authorTrejos, María
dc.contributor.authorAristizabal, Yesid
dc.contributor.authorAragón Muriel, Alberto
dc.contributor.authorOñate Garzón, José
dc.contributor.authorLiscano, Yamil
dc.date.accessioned2025-04-04T16:58:42Z
dc.date.available2025-04-04T16:58:42Z
dc.date.issued2023-09
dc.description.abstractThe growing challenge of chronic wounds and antibiotic resistance has spotlighted the potential of dual-function peptides (antimicrobial and wound healing) as novel therapeutic strategies. The investigation aimed to characterize and correlate in silico the physicochemical attributes of these peptides with their biological activity. We sourced a dataset of 207 such peptides from various peptide databases, followed by a detailed analysis of their physicochemical properties using bioinformatic tools. Utilizing statistical tools like clustering, correlation, and principal component analysis (PCA), patterns and relationships were discerned among these properties. Furthermore, we analyzed the peptides’ functional domains for insights into their potential mechanisms of action. Our findings spotlight peptides in Cluster 2 as efficacious in wound healing, whereas Cluster 1 peptides exhibited pronounced antimicrobial potential. In our study, we identified specific amino acid patterns and peptide families associated with their biological activities, such as the cecropin antimicrobial domain. Additionally, we found the presence of polar amino acids like arginine, cysteine, and lysine, as well as apolar amino acids like glycine, isoleucine, and leucine. These characteristics are crucial for interactions with bacterial membranes and receptors involved in migration, proliferation, angiogenesis, and immunomodulation. While this study provides a groundwork for therapeutic development, translating these findings into practical applications necessitates additional experimental and clinical research.
dc.identifier.citationTrejos, M., Aristizabal, Y., Aragón-Muriel, A., Oñate-Garzón, J., & Liscano, Y. (2023). Characterization and Classification In Silico of Peptides with Dual Activity (Antimicrobial and Wound Healing). International Journal of Molecular Sciences, 24(17). https://doi.org/10.3390/ijms241713091
dc.identifier.issn16616596
dc.identifier.urihttps://repositorio.usc.edu.co/handle/20.500.12421/6290
dc.language.isoen
dc.subjectantimicrobial peptides
dc.subjectwound healing
dc.subjectclustering analysis
dc.subjectbioactivity prediction
dc.subjectpeptide in silico
dc.titleCharacterization and Classification In Silico of Peptides with Dual Activity (Antimicrobial and Wound Healing)
dc.typeArticle

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