COCIN

COCIN identifies conserved protein complexes across species by constructing interolog networks that integrate domain conservation from Ensembl and sequence similarity to improve detection from noisy protein–protein interaction (PPI) datasets.

Key Features:

• Interolog Network Construction: Constructs an interolog network (IN) by integrating Ensembl domain conservation data with sequence similarity to link proteins across species such as human and yeast.
• Domain Conservation Integration: Incorporates functional domain conservation alongside sequence similarity to reveal conservation patterns not apparent from sequence analysis alone.
• Advanced Clustering Methods: Applies state-of-the-art clustering techniques to the interolog network and maps resultant clusters back to original PPI networks to identify conserved complexes.
• Improved Recall and Accuracy: Achieves higher recall for conserved complex detection (76%) compared with direct detection from original PPI networks (54%) by filtering non-conserved interactions.
• Identification of Core Cellular Complexes: Recovers conserved complexes including the MLH1-MSH2-PMS2-PCNA mismatch-repair complex, RNA polymerase-II, EIF3, and MCM complexes.

Scientific Applications:

• Conservation Analysis: Analyzes evolutionary conservation and reorganization of protein complexes between species, revealing redistribution of proteins and functions rather than simple subset relationships.
• Implications for Synthetic Lethality Studies: Informs extrapolation of genetic relationships from model organisms (e.g., yeast) to humans, with potential application to identifying novel cancer targets.

Methodology:

Constructs an interolog network by integrating domain conservation and sequence similarity, analyzes the IN using clustering methods, maps clusters back to original PPI networks, filters non-conserved interactions, and validates predicted complexes against original PPI networks.