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How to solve the complex biological mysteries of cells through protein interaction maps?
In molecular biology, the "interactome" refers to the entire collection of all molecular interactions within a specific cell. Among them, protein-protein interactions (PPIs) are not only at the core of this research, but may also reveal how these interactions shape biological processes in cells. As early as 1999, French scientist Bernard Jacq and his team first proposed this term, creating a new way to explore biological complexity. When the interactions between these molecules are recorded, the data are displayed in the form of graphics, which helps us understand the biological significance behind them.
"Interactive bodies are not only biological networks, they also make the complex relationships between various molecules more visible, providing a basis for in-depth research."
Basics of molecular interaction networks
Molecular interactions occur in all living organisms, whether they belong to different biochemical families (such as proteins, nucleic acids, lipids, etc.) or to the same family. These interactions form molecular interaction networks, and these networks are often classified based on the nature of the compounds involved. The most common interactor is the protein-protein interaction network (PIN). For example, the Sirt-1 protein interactome involves proteins with which Sirt-1 directly interacts, revealing the important role of these proteins in cellular function.
Biological significance of interactive body size
The interactors of different species vary in size, which is significantly correlated with their biological complexity. Taking yeast as an example, its interactome is estimated to have 10,000 to 30,000 protein-protein interactions, and this number may even change as research methods improve. This means that understanding an organism's complexity may require deeper analysis than just considering its genome.
The value of gene interaction networks
Interactions between genes affect each other's function, and one mutation may be harmless without the other mutations, but may be lethal in combination with another mutation. The network formed by these genes not only helps to explore the functional map of cellular processes, but is also critical for the identification of drug targets. In 2010, researchers used 5.4 million two-gene comparisons to create one of the most complete gene interactors, covering about 75% of yeast genes. This model improved our understanding of gene function.
"Gene interaction networks can help us reveal the concept of gene conservation and provide a more reliable basis for predicting gene functions."
Exploring experimental and computational methods of interactive bodies
The scientific field that explores interactive objects is called interactomics. This science uses a variety of experimental and computational methods to characterize the structure and properties of interactive networks. The yeast two-hybrid system (Y2H) is an important method that allows us to examine specific interactions between two proteins. The affinity purification method accompanied by mass spectrometry technology can more comprehensively identify protein complexes, greatly reducing the error rate.
“The interactive network visualization enabled by these technologies not only consolidates the understanding of intracellular processes, but also facilitates applications in drug discovery.”
Analysis and prediction of experimental data
Once the interactive body is established, scientists can use the data for analysis to understand the characteristics and functions of the system. This includes an assessment of the coverage of interactions; past research has shown that Y2H screening typically detects only about 25% of interactions. However, scientists can further improve the reliability of their results by filtering out incorrect and correct data by comparing it to benchmarks of well-known interactions.
Future challenges and prospects
As interactology continues to develop, scientists face many challenges, including technical errors and the complexity of test results. Although current technology does not fully understand all protein interactions, future studies that can further improve methods may reveal deeper biological mechanisms and the potential for drug development.
By examining interacting bodies, can we effectively unlock the complex secrets of how cells work?
