Interactomics is a discipline at the intersection of bioinformatics and biology that deals with studying both the interactions and the results of those interactions between and among proteins, and other molecules within a cell. Interactomics aims to compare such networks of interactions between and within species in order to find how the traits of such networks are either preserved or varied.
The word “interactome” was originally coined in 1999 by a group of French scientists headed by Bernard Jacq. Mathematically, interactomes are generally displayed as graphs. Though interactomes may be described as biological networks, they should not be confused with other networks such as neural networks or food webs.
Interactomics is an example of “top-down” systems biology, which takes an overhead, as well as overall, view of a ecosystem or organism. Large sets of genome-wide and proteomic data are collected, and correlations between different molecules are inferred.
Molecular interactions can occur between molecules belonging to different biochemical families or within a given family, such as proteins, nucleic acids, lipids, and carbohydrates. Interactomes may be described as biological networks, and most commonly, interactome refers to protein-protein interaction (PPI) network and protein-DNA interaction networks (also called gene regulatory networks), or subsets thereof. Therefore, a typical interactome includes transcription factors, chromatin regulatory proteins, and their target genes. Interactomics aims to compare such networks of interactions between and within species in order to discover patterns of network preservation and/or variation. Interactomic methods are currently being used to predict the function of proteins with no known function, especially in the field of drug discovery.
Interactome mapping, in which signaling networks are modeled on the basis of physical protein-protein interactions, is not hindered by compensatory mechanisms that may mask roles of pathway members/modifiers in functional assays. Early interactome studies relied on genome-wide yeast two-hybrid (Y2H) assays using known signaling pathway proteins as baits.
The study of interactomes is called interactomics. The basic unit of a protein network is the protein–protein interaction (PPI). While there are many methods to study PPIs, there are relatively few that have been used on a large scale to map whole interactions.
The yeast two hybrid system (Y2H) is suited to explore the binary interactions among two proteins at a time. Affinity purification and subsequent mass spectrometry is suited to identify a protein complex. Both methods can be used in a high-throughput (HTP) fashion. Yeast two hybrid screens allow false positive interactions between proteins that are never expressed in the same time and place; affinity capture mass spectrometry does not have this drawback, and is the current gold standard. Yeast two-hybrid data better indicates non-specific tendencies towards sticky interactions rather while affinity capture mass spectrometry better indicates functional in vivo protein–protein interactions.
Once an interactome has been created, there are numerous ways to analyze its properties. However, there are two important goals of such analyses. First, scientists try to elucidate the systems properties of interactomes, e.g. the topology of its interactions. Second, studies may focus on individual proteins and their role in the network.