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Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes
Alejandro Gil-Gomez1, Joshua S Rest1
1Department of Ecology and Evolution, Laufer Center for Physical and Quantitative Biology, Stony Brook University, 650 Life Sciences, Stony Brook, NY 11794-4254, USA.
Molecular Biology and Evolution
|May 20, 2024
Summary
Drug-drug interactions (DDIs) rapidly change across species, offering a novel way to estimate molecular network evolution. Synergistic DDIs involve closely connected targets that evolve faster, providing insights into evolutionary rates.
Area of Science:
- Evolutionary biology
- Systems biology
- Bioinformatics
Background:
- Molecular networks, including protein-protein interaction (PPI) and metabolic networks, change as species diverge.
- Studying network evolution across species is challenging due to limited data and model organism biases.
- Drug-drug interactions (DDIs) can serve as a proxy for molecular network topology variation.
Purpose of the Study:
- To propose and evaluate the rate of DDI change across species as an estimate for molecular network evolution.
- To investigate the relationship between synergistic DDIs and the evolutionary rates of their molecular targets.
- To explore the utility of drug combination (DC) data for large-scale network evolution studies.
Main Methods:
- Computed evolutionary rates of DDIs using high-throughput data from gram-negative bacteria.
- Applied phylogenetic comparative methods to analyze DDI divergence over evolutionary time.
- Mapped drug targets in PPI and co-functional networks to analyze synergistic DDIs and their evolutionary rates.
Main Results:
- DDIs exhibit rapid divergence over short evolutionary periods, with saturation over longer timescales.
- Synergistic DDIs involve molecular targets that are evolutionarily closer in networks.
- Nodes closer in molecular networks demonstrate faster evolutionary rates.
Conclusions:
- The rate of DDI evolution can effectively estimate the rate of underlying molecular network changes.
- Synergistic drug interactions highlight rapidly evolving molecular targets.
- Drug combination data offers a scalable approach for studying network evolution across diverse species.
Keywords:
biological network evolutiondrug–drug interactionsgram-negative bacteriaphylogenetic comparative methodsMore Related Videos
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