Mapping the Antibiofilm Peptide Space with Similarity Networks and Curated Negative Sets.

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 (MBE

SUBMITTER: Castillo-Mendieta K 

PROVIDER: S-EPMC12713488 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature