{
  "abstract": "Drug discovery typically ranks targets by individual sensitivity. Branched metabolic networks, in contrast, have redundant flux routes that buffer single-enzyme inhibition possibly deviating the best target from the most sensitive node. We developed a topology-driven framework for identifying optimal dual-target pairs and applied it to the E. coli folate pathway. A kinetic model of the folate pathway and its extended one-carbon pool showed that single-node inhibition is compensated by flux redistribution. Pairwise synergy scoring, a metric to measure drug-pair potency as compared to single drug, identified DHPS (folP) and DHFR (folA) as a top-ranked complementary pair. Experimental validation in E. coli MG1655 using sulfamethoxazole and trimethoprim confirmed strong dose-dependent synergy at intermediate inhibition and attenuation at saturation. Our results support topological complementarity as a key predictor of combination efficacy and provide a rationale for drug-pair design in branched biosynthetic pathways.",
  "abstract_shown": true,
  "affiliations": [
    "Birla Institute of Technology and Science-Pilani, Hyderabad, India"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "D. Pandey"
    },
    {
      "name": "P. Sikdar"
    },
    {
      "name": "A. Chattaraj"
    },
    {
      "affs": [
        0
      ],
      "name": "S. Chowdhury"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7gbex4tr9eney.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.24.761489",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.24.761489v1.full",
  "id": "7gbex4tr9eney",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.24.761489v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "systems biology"
    ],
    [
      "openalex",
      "1312|Microbial Metabolic Engineering and Bioproduction"
    ]
  ],
  "openalex": "W7223845468",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.24.761489v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7gbex4tr9eney.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:48Z",
      "native_id": "10.64898/2026.10.24.761489",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.24.761489v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:systems biology",
      "subfield": "systems-synthetic"
    }
  ],
  "title": "Topological Complementarity Predicts Synergistic Drug Pairs in Branched Metabolic Networks.",
  "title_text": "Topological Complementarity Predicts Synergistic Drug Pairs in Branched Metabolic Networks.",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:48Z",
  "url": "https://research.draconitic.com/paper/7gbex4tr9eney",
  "venue": "bioRxiv",
  "versions": []
}