Week 3 - L2 - Methods and Applications for Characterizing Protein-Protein Interactions and Biomolecule Interactions

Understanding how a protein or other biomolecule interacts with other components within a cell is critical for biological study.
Biomolecules do not exist in isolation; every biomolecule interacts with other biomolecules within its environment.
Interaction analysis is essential for gaining functional insights into molecular behavior and cellular processes.
The broader term for this field of study is biomolecule interaction analysis.

There are multiple experimental methodologies available to detect protein-protein interactions (PPI) and characterize their nature.
Biophysical techniques, such as Nuclear Magnetic Resonance (NMR), enable the collection of structural data on multiple proteins simultaneously.
Fluorescence Resonance Energy Transfer (FRET) is a fluorescence-based experiment used to detect interactions:
- When two proteins specifically tagged with fluorophores come into close proximity, energy transfer results in the emission of a signal.
- This emission provides physical evidence that the proteins are close enough to form a direct interaction.
Interaction proteomics is a specialized branch of proteomics dedicated to characterizing the networks of interactions between proteins.

STRING is a powerful bioinformatic tool used to identify likely protein-protein interactions for a specific protein of interest.
The tool does not just list proteins but provides physical and functional evidence that an interaction is taking place.
In a STRING network map, proteins are represented as nodes, and the lines connecting these nodes represent specific lines of evidence supporting the interaction.
Confidence in these interactions is quantified via a score; for example, in high-confidence networks, scores are often very close to $1$ , indicating very strong evidence for the existence of the interaction.

The TSC1 gene codes for a protein known as hamartin.
Analysis using STRING reveals that hamartin interacts with several other proteins, most notably the protein coded for by the TSC2 gene, known as tuberin.
The relationship between hamartin and tuberin is complex, as many of the proteins interacting with TSC1 also interact with one another, forming an intricate network.
Other components identified in this specific network include:
- Various kinases.
- RPTOR, which is a regulator associated with mTOR (mammalian target of rapamycin).
Functionally, the hamartin-tuberin complex (TSC1-TSC2) plays a primary role in the inhibition of mTOR.
By examining these interaction partners, it is possible to infer that hamartin (TSC1) is involved in cellular processes linked to the functions of those specific proteins.

Assessing the consequences of over-expression or under-expression of a particular gene is a vital strategy for characterizing protein function.
Model organisms, such as mice, are frequently utilized to simulate and study these variations in expression levels.
A specific case involving expression variation is the study of Beclin-1 in epithelial colon cells:
- Beclin-1 plays a major role in autophagy, the cellular process where intracellular components are degraded within the lysosome.
- In a normal state, Beclin-1 expression is localized specifically within the nuclei of epithelial cells.
- In the presence of an adenocarcinoma, the expression pattern of Beclin-1 changes significantly, showing staining in both the nuclei and the cytoplasm.
- Overexpression of Beclin-1 in epithelial cells already displaying adenocarcinoma results in increased intensity and distribution of Beclin-1 staining.
- Under-expression of Beclin-1 results in only small, limited amounts of staining observable in the nucleus.
Observations indicate that Beclin-1 overexpression serves as a biological marker for adenocarcinoma.

The consequences of genetic mutation serve as another analytical tool for characterizing protein function.
By identifying individuals with specific mutations that cause genetic diseases, researchers can determine how a mutation in a specific gene region causes dysfunction at both the protein and cellular levels.
Functional characterization is not limited to human studies; mutations can be intentionally created in model organisms:
- Point mutations can be introduced to study localized changes.
- Gene knockouts involve the complete removal or inactivation of a gene to observe the resulting biological consequences.
Hypothetically, if the knockout of a particular gene leads to the development of tumors with high frequency, it strongly suggests that the target gene is likely a tumor suppressor gene.
The ability to assess phenotypic changes following genetic manipulation in model organisms is a powerful method for understanding the role of a gene and its corresponding protein.
Collectively, there are six primary methods for characterizing a protein expressed from a gene of interest, which will be applied to the assessment of proteins such as APOE.