Identifying conserved protein complexes between species by constructing interolog networks

TL;DR

This paper presents a computational approach to identify conserved protein complexes across species by constructing interolog networks, leveraging domain conservation to improve detection accuracy amidst noisy data.

Contribution

It introduces a novel method that integrates domain conservation information into interolog network construction to better identify conserved protein complexes between species.

Findings

Identified conserved complexes missed by previous methods.

Demonstrated the importance of domain conservation in complex identification.

Improved detection of conserved complexes across human and yeast.

Abstract

Protein complexes conserved across species indicate processes that are core to cellular machinery (e.g. cell-cycle or DNA damage-repair complexes conserved across human and yeast). While numerous computational methods have been devised to identify complexes from the protein interaction (PPI) networks of individual species, these are severely limited by noise and errors (false positives) in currently available datasets. Our analysis using human and yeast PPI networks revealed that these methods missed several important complexes including those conserved between the two species (e.g. the MLH1-MSH2-PMS2-PCNA mismatch-repair complex). Here, we note that much of the functionalities of yeast complexes have been conserved in human complexes not only through sequence conservation of proteins but also of critical functional domains. Therefore, integrating information of domain conservation might throw further light on conservation patterns between yeast and human complexes.