# GreedyPlus: An Algorithm for the Alignment of Interface Interaction Networks

**Authors:** Brian Law, Gary D. Bader

PMC · DOI: 10.1038/srep12074 · Scientific Reports · 2015-07-13

## TL;DR

This paper introduces a new algorithm called GreedyPlus to align interface interaction networks, helping compare protein interactions across species.

## Contribution

GreedyPlus is a novel greedy algorithm specifically designed for aligning interface interaction networks, which current methods fail to handle effectively.

## Key findings

- GreedyPlus successfully aligns interface interaction networks using diverse data sources.
- The algorithm generates biologically meaningful alignments for worm and yeast interface data.
- GreedyPlus is computationally efficient and customizable for different alignment needs.

## Abstract

The increasing ease and accuracy of protein-protein interaction detection has resulted in the ability to map the interactomes of multiple species. We now have an opportunity to compare species to better understand how interactomes evolve. As DNA and protein sequence alignment algorithms were required for comparative genomics, network alignment algorithms are required for comparative interactomics. A number of network alignment methods have been developed for protein-protein interaction networks, where proteins are represented as vertices linked by edges if they interact. Recently, protein interactions have been mapped at the level of amino acid positions, which can be represented as an interface-interaction network (IIN), where vertices represent binding sites, such as protein domains and short sequence motifs. However, current algorithms are not designed to align these networks and generally fail to do so in practice. We present a greedy algorithm, GreedyPlus, for IIN alignment, combining data from diverse sources, including network, protein and binding site properties, to identify putative orthologous relationships between interfaces in available worm and yeast data. GreedyPlus is fast and simple, allowing for easy customization of behaviour, yet still capable of generating biologically meaningful network alignments.

## Full-text entities

- **Genes:** LAS17 (actin-binding protein LAS17) [NCBI Gene 854353] {aka BEE1}, ACT1 (actin) [NCBI Gene 850504] {aka ABY1, END7}, BZZ1 (Bzz1p) [NCBI Gene 856514] {aka LSB7}, IQG1 (Iqg1p) [NCBI Gene 855834] {aka CYK1}, BNI1 (formin BNI1) [NCBI Gene 855450] {aka PPF3, SHE5}
- **Diseases:** OVP (MESH:D006261), RPO (MESH:D011488)
- **Chemicals:** proline (MESH:D011392)
- **Species:** Caenorhabditis elegans (species) [taxon 6239], Homo sapiens (human, species) [taxon 9606], Saccharomyces cerevisiae (baker's yeast, species) [taxon 4932], Saccharomyces bayanus (species) [taxon 4931], C. elegans [taxon 328850], Saccharomyces mikatae (species) [taxon 114525]

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/PMC4499810/full.md

## References

51 references — full list in the complete paper: https://tomesphere.com/paper/PMC4499810/full.md

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Source: https://tomesphere.com/paper/PMC4499810