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<p><i>Candida albicans</i> biofilm formation remains a serious clinical challenge due to its intrinsic tolerance to antifungal therapies and its ability to colonize host tissues and indwelling medical devices, resulting in persistent and difficult-to-treat infections. Therefore, the development of alternative biofilm-targeted strategies remains necessary. Growing evidence suggests that natural products derived from <i>Streptomyces</i> represent a rich source of bioactive compounds with potential antibiofilm relevance. However, systematic approaches that connect <i>Streptomyces</i> biosynthetic potential with biofilm-associated molecular networks in <i>C. albicans</i> remain limited. In this study, a genome-guided and network-based bioinformatics framework was employed to prioritize <i>Streptomyces</i>-derived secondary metabolites with potential multi-target relevance to <i>C. albicans</i> biofilm regulation. Genome assembly and annotation indicated draft genomes with large sizes, high G + C content, and substantial biosynthetic capacity. Phylogenomic analysis positioned GMR22, SHP22-7, and BSE7F within distinct <i>Streptomyces</i> lineages, supporting their genetic divergence and suitability for comparative biosynthetic exploration. Subsequent antiSMASH and BiG-FAM profiling revealed extensive and largely non-overlapping biosynthetic gene cluster (BGC) repertoires with pronounced strain-specific heterogeneity, generating a diverse pool of predicted secondary metabolites, including polyketides, nonribosomal peptides, RiPPs, terpenoids, and hybrid scaffolds. STRING-based protein–protein interaction analysis using the GO term “biofilm formation” (GO:0042710) identified a densely connected <i>C. albicans</i> biofilm-associated network, from which ALS3, FGR27, and TEC1 were prioritized as network-derived hub nodes rather than experimentally validated essential targets. Molecular docking predicted Sch-47,554, sanglifehrin A, and resistoflavine as representative <i>Streptomyces</i>-derived candidates with favorable multi-target interaction profiles against the prioritized biofilm-associated proteins. Remarkably, these compounds demonstrated substantially superior binding affinities compared to nystatin, although this evidence remains confined to in silico analysis. Furthermore, dynamics-based flexibility and normal mode analyses support conformational compatibility of ligand–protein complexes within adaptable protein regions. Overall, this study establishes an integrative genome-to-network in silico framework linking <i>Streptomyces</i> biosynthetic diversity to <i>C. albicans</i> biofilm network architecture, enabling multi-target candidate prioritization. However, experimental validation and pharmacological characterization remain essential to confirm biological activity and translational potential.</p> Graphical Abstract <p></p>

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Genome-Guided Mining and Integrated in Silico Approach Uncover Potential of Streptomyces Secondary Metabolites as Multi-Target Agents Against Candida albicans Biofilm Formation

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Ismail Ismail,
  • Sylvia Utami Tunjung Pratiwi,
  • Ema Damayanti,
  • Jaka Widada,
  • Ysrafil Ysrafil,
  • Syamsu Nur,
  • Abdul Halim Umar,
  • Ira Handayani,
  • Shanti Ratnakomala

摘要

Candida albicans biofilm formation remains a serious clinical challenge due to its intrinsic tolerance to antifungal therapies and its ability to colonize host tissues and indwelling medical devices, resulting in persistent and difficult-to-treat infections. Therefore, the development of alternative biofilm-targeted strategies remains necessary. Growing evidence suggests that natural products derived from Streptomyces represent a rich source of bioactive compounds with potential antibiofilm relevance. However, systematic approaches that connect Streptomyces biosynthetic potential with biofilm-associated molecular networks in C. albicans remain limited. In this study, a genome-guided and network-based bioinformatics framework was employed to prioritize Streptomyces-derived secondary metabolites with potential multi-target relevance to C. albicans biofilm regulation. Genome assembly and annotation indicated draft genomes with large sizes, high G + C content, and substantial biosynthetic capacity. Phylogenomic analysis positioned GMR22, SHP22-7, and BSE7F within distinct Streptomyces lineages, supporting their genetic divergence and suitability for comparative biosynthetic exploration. Subsequent antiSMASH and BiG-FAM profiling revealed extensive and largely non-overlapping biosynthetic gene cluster (BGC) repertoires with pronounced strain-specific heterogeneity, generating a diverse pool of predicted secondary metabolites, including polyketides, nonribosomal peptides, RiPPs, terpenoids, and hybrid scaffolds. STRING-based protein–protein interaction analysis using the GO term “biofilm formation” (GO:0042710) identified a densely connected C. albicans biofilm-associated network, from which ALS3, FGR27, and TEC1 were prioritized as network-derived hub nodes rather than experimentally validated essential targets. Molecular docking predicted Sch-47,554, sanglifehrin A, and resistoflavine as representative Streptomyces-derived candidates with favorable multi-target interaction profiles against the prioritized biofilm-associated proteins. Remarkably, these compounds demonstrated substantially superior binding affinities compared to nystatin, although this evidence remains confined to in silico analysis. Furthermore, dynamics-based flexibility and normal mode analyses support conformational compatibility of ligand–protein complexes within adaptable protein regions. Overall, this study establishes an integrative genome-to-network in silico framework linking Streptomyces biosynthetic diversity to C. albicans biofilm network architecture, enabling multi-target candidate prioritization. However, experimental validation and pharmacological characterization remain essential to confirm biological activity and translational potential.

Graphical Abstract