Evidence map›Paper›PMID 38768245›Full record

ArticleMolecular biology and evolution2024

Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes.

Alejandro Gil-Gomez, Joshua S Rest

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Alejandro Gil-GomezDepartment of Ecology and Evolution, Laufer Center for Physical and Quantitative Biology, Stony Brook University, 650 Life Sciences, Stony Brook, NY 11794-4254, USA.
Joshua S RestDepartment of Ecology and Evolution, Laufer Center for Physical and Quantitative Biology, Stony Brook University, 650 Life Sciences, Stony Brook, NY 11794-4254, USA.ORCID 0000-0002-9582-1041

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.

Indexed as

PhylogenyBiological EvolutionDrug InteractionsEvolution, MolecularGram-Negative BacteriaMetabolic Networks and PathwaysProtein Interaction Mapsbiological network evolutiondrug–drug interactionsgram-negative bacteriaphylogenetic comparative methods

Identifiers

PMID38768245
PMCPMC11136681

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