Protein-Protein Interactions (PPI)
Protein-Protein Interactions (PPIs) play a vital role in maintaining biological systems. Strong interactions ensure structural integrity and function, while weaker interactions provide flexibility, allowing cells to adapt to changing conditions. Understanding PPIs is fundamental to advancing research in cell biology and drug development.
Explore Biolayer Interferometry for PPIExplore 표면 플라스몬 공명 for PPI
The protein-protein interaction assays can be broadly classified into three main categories:
In Vitro - This method involves conducting the entire procedure outside the cell in a controlled laboratory environment. Techniques include affinity chromatography, protein fragment complementation, X-ray crystallography, NMR, phage display, spectroscopy, protein assays, and biomolecular interaction analysis.
In Vivo - These techniques are applied directly to living cells or organisms, allowing for the observation and analysis of biological processes in their natural context.
인실리코 - These techniques are performed using computer simulations and computational models. They encompass sequence and structure-based approaches, in-silico two-hybrid approaches, gene expression-based methods, chromosome proximity and gene fusion techniques, phylogenetic profiling, or tree-building techniques.
PPIs are classified based on factors such as stability, duration, and the types of proteins involved.
Protein-protein interactions can be classified in several ways:
Based on affinity, they can be classified as obligate (in case one or more of the proteins is unstable in vivo unless interacting and forming a specific protein complex) and non-obligate interactions (in case the proteins can exist independently).
Non-obligate interactions can be classified based on the stability of the complex they form, as permanent or transient, and transient interactions as weak or strong.
As most obligate interactions are permanent, and most non-obligate interactions are transient, obligate and permanent are sometimes used interchangeably in the literature.
The majority of cellular processes are regulated by transient PPI, and thus a large part of the research on PPI concentrates on this type of interaction.
Dynamic processes like signal transduction and metabolism rely on weaker, transient interactions regulated by conditions like 인산화 or conformational changes. These weak interactions help assemble multi-enzyme complexes or shape cellular morphology and motility.
In contrast, strong PPIs lead to stable, multi-subunit complexes, with dissociation constants typically in the nanomolar range or lower. RNA polymerase is a well-studied complex with strong interactions between its multiple subunits. Another example is the interaction between the anti-apoptotic protein Bcl-2 and the pro-apoptotic protein Bax, which balances cell survival and death. Disruption of this balance is a key factor in cancer development.
Many drugs target PPIs to either disrupt or enhance specific interactions, providing therapeutic benefits in diseases like cancer. Small molecules, peptides, and monoclonal antibodies (mAbs) are examples of interaction modulators developed through various 선별 and optimization techniques.
For example, monoclonal antibodies targeting the PD-1/PD-L1 pathway have revolutionized cancer immunotherapy by blocking this 면역관문, boosting anti-tumor responses. Similarly, Nutlin-3 inhibits the interaction between MDM2 and p53, preventing p53 degradation and allowing its tumor-suppressive functions to operate. This small molecule is undergoing clinical testing and shows promise in cancer treatment.
There are end-point and real-time methods for analyzing PPIs. End-point assays provide information about a single timepoint and are ideal for detecting an interaction. However, for capturing dynamic interactions and detailed kinetics, real-time methods provide the most complete picture of the PPI.
The choice of method depends on factors like target size, sample usage, and throughput requirements. It is also crucial to consider the interaction type, as weak or transient interactions may be lost in certain protocols. In some applications, an ELISA provides sufficient yes/no information about the interaction of interest. However, for a deeper understanding of dynamic interactions, label-free, real-time data is often needed.
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PPIs occur when two or more proteins physically interact, driving nearly all biological processes. Examples include enzyme-substrate interactions, receptor-ligand signaling cascades, cell cycle regulation, and structural assemblies like the cytoskeleton.
Yes, proteins interact with other proteins. These interactions are crucial for many biological processes, including signal transduction, cellular structure, and metabolic pathways.
Breaking protein-protein interactions can be achieved through several methods:
These methods are often used in research and drug development to study protein functions and develop therapeutic interventions.
Testing for PPIs involves several steps and can be achieved using various techniques.
First, choose the appropriate method based on the nature of the proteins, the type of interaction, and the information needed, such as binding affinity, kinetics, or structural details.
Next, prepare protein samples. If required, label the proteins with fluorescent or other suitable tags to facilitate detection, especially for techniques like FRET or MST.
After conducting the experiment depending on the chosen method, analyze the data. Finally, validate the results by confirming findings using complementary techniques or repeating experiments to ensure reliability and reproducibility.
Common techniques used to study protein-protein interactions (PPI) include:
Biolayer Interferometry (BLI) is a technique used to study protein-protein interactions. It measures binding events in real-time by detecting changes in the interference pattern of light reflected from a biosensor surface. One protein is immobilized on the sensor, and the other is in solution. BLI provides information on binding kinetics, affinity, and specificity without the need for labeling, making it a valuable tool for analyzing protein interactions.
The BLI technology allows a fluidic-free design. Unlike other techniques that require complex microfluidic systems, BLI uses a simple dip-and-read format eliminating the risk of clogging and cross-contamination and simplifying the experimental setup.
Additionally, BLI is capable of measuring interactions in crude samples, such as cell lysates or unpurified protein mixtures. This capability is particularly beneficial for early-stage research and high-throughput 선별.
For Biolayer Interferometry (BLI) experiments, the amount of protein required can vary depending on the specific assay and the proteins involved. BLI utilizes a plate-based format, which allows for non-destructive measurement. This means that the sample plate can be reused for further experiments after the initial BLI analysis. This feature not only conserves valuable samples but also enables subsequent analyses or assays, enhancing the efficiency and versatility of the experimental workflow. It's important to optimize the concentration and amount based on preliminary experiments to ensure reliable and reproducible results.
Generally, for the experiment you need:
표면 플라스몬 공명 (SPR) is a technique used to study protein-protein interactions. It allows researchers to measure the binding affinity, kinetics, and specificity of interactions between proteins in real-time without the need for labeling. In SPR, one protein is immobilized on a sensor chip, and the other protein is flowed over the surface. Changes in the refractive index near the surface are measured, which occur when the proteins interact. This provides valuable data on how proteins interact, including the strength and duration of the interaction.
The amount of protein required for 표면 플라스몬 공명 (SPR) experiments can vary depending on the specific setup and the proteins involved. Generally, you need:
It's important to optimize the concentration and amount based on preliminary experiments to ensure reliable and reproducible results.
Acuner Ozbabacan, S. E., Engin, H. B., Gursoy, A., & Keskin, O. (2011). Transient protein–protein interactions. Protein Engineering, Design and Selection, 24 (9), 635–648. https://doi.org/10.1093/protein/gzr025
Berggård, T., Linse, S., & James, P. (2007). Methods for the detection and analysis of protein-protein interactions. Proteomics, 7(16), 2833–2842. https://doi.org/10.1002/pmic.200700131
Goncearenco, A., Li, M., Simonetti, F. L., Shoemaker, B. A., & Panchenko, A. R. (2017). Exploring Protein-Protein Interactions as Drug Targets for Anti-cancer Therapy with 인실리코 Workflows. Methods in molecular biology (Clifton, N.J.), 1647, 221–236. https://doi.org/10.1007/978-1-4939-7201-2_15
Lu, H., Zhou, Q., He, J., Jiang, Z., Peng, C., Tong, R., & Shi, J. (2020). Recent advances in the development of protein-protein interactions modulators: mechanisms and clinical trials. Signal transduction and targeted therapy, 5(1), 213. https://doi.org/10.1038/s41392-020-00315-3
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