Interactome refers to all sets of molecular interactions inside a cell. Although an interactome usually used for protein-protein interactions, they may also refer to metabolic networks or gene regulatory networks.
Role of Interactome in Medicine
Proteins rarely act in isolation in diseases. Usually a diseased state is associated with increased cohort of signaling proteins, metabolic factors, and gene expression. Thus, analyzing the interactome of protein-protein interactions using disease can reveal all the interactions that are upregulated or downregulated during a disease. This can provide clues or help in identifying which molecules or sets of molecules need to be targeted to control or cure the disease.
Cross-Species Interactome Mapping Reveals Network Evolution Principles from Yeasts to Human
Identifying Disease Genes Using Interactome
Analyzing the interactome of protein-protein interactions during a disease can help uncover expression of which genes are increased. Although high-throughput gene profiling techniques are also currently available, network-based approaches can highlight disease-related processes which can further identify disease-related genes. Study of such networks has led to discovery of novel disease-related genes.
Characterization of Unknown Protein
The interactome has also been used to characterise the functions of unknown proteins. Usually proteins which interact together are also likely involved in similar or same biological processes. Thus, finding the interacting partners of an unknown protein or metabolite can give indication as to its function. Several algorithms are being used to infer the protein functions, including direct and indirect methods. Direct methods include neighborhood counting, integrating information from different interacting partners to characterise function of a protein. In direct methods, topological properties of a network are identified to recognize module of proteins whose interactions can be attributed to specific processes.
Predicting Domain-Domain Interactions
Proteins usually consist of two or more domains. In prokaryotes, two-thirds of protein contain multidomains, while in eukaryotes, four-fifths of proteins contain multiple domains. Interactions between two proteins consists of interactions between two specific domains. The identification of these domains is critical to understanding protein-protein interactions. One of the methods of scoring each domain pair is by calculating the ratio of number of occurrences of a domain pair to number of independent occurrences of those domains. This score determines the probability of interaction between two domains.
Identifying Network Motiffs
Interactome networks can have specific sizes and connectivities. However, different networks can show similarities in their local or global structure. It was recently shown that different networks display a much higher frequency of patterns in their organisation that what would be expected from randomly organised network. Certain motifs were found to recur at a greater frequency. The identification of such motifs can help in inferring key information processing signals.
Comparison Between Model Organisms and Humans
Recently, a study compared different protein interactomes between humans and yeast, worm, fly. Such comparisons of interactomes can determine the degree of similarity or dissimilarity between the networks of different species which contribute to health and diseases. The study looked at >70,000 interactions and found that one 42 of them were common between human, worm and fly. Sixteen of such interaction were common to all four data sets.
Determining Sub-Cellular Localisation of a Protein
Determining where a protein localizes can be key to understand how it functions. Currently, microscopy-based methods are used most widely to determine where a protein localizes. However, two proteins which interact together also have a tendency to have same or similar sub-cellular locations. Thus, interactome and inferring the protein-protein interactions can also be used to determine location of a protein. Different algorithms have been developed for a network-based approach to predict the location of a protein using its protein-protein interaction network.
Identifying Off-Targets of a Drug
Drugs interact with different molecular targets to exert their effect. Although they mainly interact with specific targets, they also often bind to non-specific proteins which are called ‘off-targets’. Using a chemical-protein interactome, the off-targets of a drug can be predicted. This understanding is critical to analyse the pharmacology of a drug and to reduce its side-effects.