Mapping the Antibiofilm Peptide Space with Similarity Networks and Curated Negative Sets
Journal
ACS Omega
ISSN
2470-1343
Publisher
American Chemical Society (ACS)
Date Issued
2025
Author(s)
Castillo-Mendieta, Kevin
Márquez, Edgar A.
García-Giménez, José Luis
Antunes, Agostinho
Agüero-Chapin, Guillermin
Type
text::journal::journal article
Abstract
Biofilm-forming microorganisms pose a growing threat in clinical and industrial settings due to their tolerance to conventional antimicrobials. Antibiofilm peptides (ABFPs) offer a promising alternative, yet their discovery is challenging due to sequence diversity and complex mechanisms of action. We present the most comprehensive curated ABFP dataset to date and systematically compare it against two negative sets: quorum sensing peptides (QSPs) and random peptides (RPs). Classical statistical analyses combined with alignment-free similarity networks─Chemical Space Networks (CSNs) and Half-Space Proximal Networks (HSPNs)─identified compositional and physicochemical features that distinguish ABFPs from negative sets. Integration of quantitative biofilm inhibition (MBIC) and eradication (MBEC) data enhanced the resolution of meaningful patterns in the antibiofilm chemical space. Network analyses revealed conserved ABFP-enriched clusters with bioactivity data, distinctive motifs absent in negative sets, and central peptides with high topological importance that may serve as scaffolds for developing potent antimicrobials. QSPs and RPs, as biologically distinct comparators, served as robust filters refining ABFP signatures and reducing false positives. Projection onto the HSPN confirmed that ABFPs occupy a unique and well-defined region of sequence space. This integrative framework─combining curated datasets, compositional profiling, and network topology─provides a practical platform to accelerate ABFP discovery by identifying key features that can be incorporated into rule-based filters for prioritizing promising candidates. © 2025 The Authors. Published by American Chemical Society.
License
Acceso Abierto
How to cite
Castillo-Mendieta, K., Marrero-Ponce, Y., Márquez, E. A., García-Giménez, J. L., Antunes, A., & Agüero-Chapin, G. (2025). Mapping the Antibiofilm Peptide Space with Similarity Networks and Curated Negative Sets. ACS Omega, 10(49), 60457–60476. https://doi.org/10.1021/acsomega.5c07679