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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A...
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PhyloSystemX: Enhancing the Analysis of Interaction Networks.

Hugo Bonnefous1, Yu Zhang1, Philippe Lopez1

  • 1Department of Computational, Quantitative and Synthetic Biology (CQSB), UMR7238, Sorbonne Université, CNRS, IBPS, 75005, Paris, France.

Methods in Molecular Biology (Clifton, N.J.)
|April 29, 2026
PubMed
Summary
This summary is machine-generated.

PhyloSystemX reconstructs ancestral biological networks using phylogenetic data and interaction information. This tool helps uncover evolutionary conserved modules and lineage-specific innovations in biological systems.

Keywords:
Ancestral network reconstructionEvolutionary biologyInteraction networksNetwork evolutionPhylogeneticsSystems biology

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Evolutionary Biology

Background:

  • Biological networks are crucial for understanding complex interactions.
  • Current network analysis lacks evolutionary historical context.
  • Reconstructing ancestral networks is essential for evolutionary insights.

Purpose of the Study:

  • To develop PhyloSystemX, a computational tool for reconstructing ancestral biological interaction networks.
  • To integrate phylogenetic species trees with modern interaction data for evolutionary analysis.
  • To provide a method for inferring evolutionary history of biological systems.

Main Methods:

  • Implementation of parsimony-based algorithms (Dollo and Sankoff adjusted).
  • Inference of ancestral vertices (homology groups) and their interactions.
  • Analysis of diverse network types labeled with homology identifiers.

Main Results:

  • PhyloSystemX enables reconstruction of ancestral networks across evolutionary time.
  • The tool can analyze protein-protein interactions, gene co-expression networks, and metabolic regulation systems.
  • Identified conserved functional modules and lineage-specific innovations.

Conclusions:

  • PhyloSystemX bridges the gap between network analysis and evolutionary history.
  • The tool facilitates the exploration of biological system adaptation over time.
  • Future versions aim to address limitations like horizontal gene transfer.