Drug repositioning pipeline integrating community analysis in drug-drug similarity networks and automated ATC community labeling to foster molecular docking analysis
Our integrated pipeline effectively integrates network-based community analysis and automated ATC labeling with literature and docking analysis, narrowing the search space for <i>in silico</i> and experimental follow-up. The chloramphenicol example illustrates its utility for uncovering non-obvious repositioning opportunities. Future work will extend similarity definitions (e.g., to higher-order network motifs) and incorporate wet-lab validation of top candidates.
Authors
- Fedora Grande (ORCID: https://orcid.org/0000-0002-6154-4330)
- Vlad Groza (ORCID: https://orcid.org/0000-0003-2704-8541)
- Maria Antonietta Occhiuzzi (ORCID: https://orcid.org/0000-0003-0098-0347)
- Lucreția Udrescu (ORCID: https://orcid.org/0000-0002-3084-6301)
- Mihai Udrescu (ORCID: https://orcid.org/0000-0002-7607-9240)
- Daiana Colibăşanu (ORCID: https://orcid.org/0009-0003-2449-3452)
Institutions
- Polytechnic University of Timişoara (RO)
- Victor Babeș University of Medicine and Pharmacy Timișoara (RO)
- University of Calabria (IT)
Publication Details
- Journal
- Frontiers in Bioinformatics
- Published
- 2025-10-23
- DOI
- https://doi.org/10.3389/fbinf.2025.1666716
- Citations
- 1
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.50