Topological Complementarity Predicts Synergistic Drug Pairs in Branched Metabolic Networks.
- 1Birla Institute of Technology and Science-Pilani, Hyderabad, India
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.
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BibTeX
@misc{pandey2026topological,
title = {{Topological Complementarity Predicts Synergistic Drug Pairs in Branched Metabolic Networks.}},
author = {D. Pandey and P. Sikdar and A. Chattaraj and S. Chowdhury},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.24.761489},
url = {https://www.biorxiv.org/content/10.64898/2026.10.24.761489v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Topological Complementarity Predicts Synergistic Drug Pairs in Branched Metabolic Networks.
AU - D. Pandey
AU - P. Sikdar
AU - A. Chattaraj
AU - S. Chowdhury
PY - 2026
DA - 2026/10/24
PB - bioRxiv
DO - 10.64898/2026.10.24.761489
UR - https://www.biorxiv.org/content/10.64898/2026.10.24.761489v1
AB - 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.
ER -