Comprehensive Characterization of Protein-Protein Interactions Perturbed by Disease Mutations
The comprehensive characterization of protein-protein interactions perturbed by disease mutations is crucial for understanding disease pathogenesis, identifying potential therapeutic targets, and developing new treatments. Protein-protein interactions are fundamental to the biological functions in organisms, with nearly all life processes depending on the complex and precise interactions between proteins. However, mutations in genes, especially those associated with diseases, often disrupt these interactions, leading to abnormal protein functions, which in turn trigger various diseases. The comprehensive characterization of protein-protein interactions perturbed by disease mutations aims to thoroughly analyze and identify how these mutations disrupt the interaction networks between proteins. Abnormal protein-protein interactions caused by disease mutations directly affect important biological processes, such as cell signaling, metabolism, and gene expression. Therefore, the comprehensive characterization of protein-protein interactions perturbed by disease mutations not only helps to uncover the causes of diseases but also provides guidance for personalized medicine. For example, in cancer research, identifying the pathways where key protein-protein interactions are disturbed by mutations can reveal the mechanisms of tumorigenesis and guide the development of targeted therapies. Moreover, neurodegenerative diseases, cardiovascular diseases, and immune diseases are also closely related to alterations in specific protein-protein interaction networks.
Specific Characterization Methods and Processes
1. Identification of Disease-Related Mutations
(1) Data Collection: Disease-related gene mutation information is collected from multiple sources, such as public databases (e.g., ClinVar, OMIM), published research literature, and large-scale genomic sequencing project data. These data provide known mutation sites and types related to specific diseases.
(2) Screening and Verification: The collected mutations are screened, with priority given to those that frequently appear in disease patients and are predicted to have significant functional impacts. Targeted gene sequencing (e.g., Sanger sequencing, next-generation sequencing) is performed on patient samples to verify the presence of these mutations and determine their distribution within the disease population.
2. Protein Expression and Purification
(1) Constructing Expression Vectors: Expression vectors are constructed for proteins containing disease mutation sites and the corresponding wild-type genes. Bacterial (e.g., Escherichia coli), yeast, insect cells, or mammalian cells (e.g., HEK293 cells) are commonly selected as expression systems based on the protein's characteristics and subsequent experimental requirements.
(2) Protein Expression and Purification: The constructed expression vectors are introduced into the host cells for protein expression. Following expression, affinity chromatography (e.g., His-tag purification), ion exchange chromatography, and gel filtration chromatography are used to purify the proteins, obtaining high-purity wild-type and mutant protein samples for subsequent interaction studies.
3. Detection of Protein-Protein Interactions
(1) In Vitro Interaction Detection
①Surface Plasmon Resonance (SPR): SPR enables real-time monitoring of protein-protein interactions by detecting the binding and dissociation of protein molecules on the sensor surface, providing parameters such as the affinity constant (KD). One protein is immobilized on the sensor chip, and the other protein solution is injected to observe signal changes and analyze interactions.
②Isothermal Titration Calorimetry (ITC): ITC directly measures the heat changes during protein-protein interactions, determining thermodynamic parameters such as binding enthalpy and entropy. One protein solution is titrated into a sample cell containing the other protein, and the heat changes are recorded and analyzed.
③Fluorescence Resonance Energy Transfer (FRET): FRET occurs when two fluorescently labeled proteins come into close proximity, leading to energy transfer. Changes in fluorescence signals can determine the presence and intensity of protein-protein interactions.
(2) In Vivo Interaction Detection
①Co-Immunoprecipitation (Co-IP): Co-IP uses antibodies specific to the target protein to precipitate other interacting proteins. These interactions are detected using methods like Western blotting. Tagged proteins are expressed in cells, and antibodies against the tag are used for immunoprecipitation to analyze the protein composition in the precipitate.
②Yeast Two-Hybrid System: The two proteins of interest are fused with the DNA-binding domain and activation domain of a transcription factor. If these proteins interact, the transcription factor is reactivated, leading to expression of a reporter gene, and the interaction is assessed by monitoring the reporter gene expression.
4. Structural Biology Analysis
(1) X-ray Crystallography: Protein complexes (wild-type and mutant) are crystallized, and their three-dimensional structure is determined using X-ray diffraction. The impact of mutations on the protein interaction interface, such as changes in amino acid residues, hydrogen bonds, and hydrophobic interactions, can be directly observed.
(2) Nuclear Magnetic Resonance (NMR): NMR is used to study smaller proteins or protein fragments' structure and dynamic changes. It provides structural information in solution and helps analyze the dynamic impact of mutations on protein conformation and interaction regions.
(3) Cryo-Electron Microscopy (Cryo-EM): For difficult-to-crystallize protein complexes, Cryo-EM can resolve high-resolution structures in near-native states, revealing subtle structural changes caused by mutations and how these changes impact protein-protein interactions.
5. Functional Analysis
(1) Cellular Functional Assays: Wild-type and mutant proteins are introduced into cells to observe changes in cellular phenotypes, such as proliferation, apoptosis, migration, and differentiation. For example, the interaction of mutation-related proteins in cancer is studied to assess their impact on tumor cell growth and metastatic potential.
(2) Signal Pathway Analysis: The activation or inhibition of signal pathways related to protein-protein interactions is assessed. Changes in phosphorylation levels of key proteins in the pathway, or alterations in protein expression levels, are analyzed using Western blotting to understand how mutations interfere with signaling and contribute to disease progression.
6. Bioinformatics Analysis
(1) Protein Structure Prediction: Computational algorithms are used to predict the three-dimensional structure of proteins, particularly for those whose structures are difficult to determine experimentally. By analyzing the location of mutation sites within the protein structure, their potential impact on protein-protein interactions can be predicted.
(2) Interaction Network Analysis: Existing protein interaction data are integrated to construct protein interaction networks, analyzing the position and role of mutated proteins within the network. Network analysis helps identify other key proteins interacting with the mutated protein and the effects these interactions have on the entire biological network.
The comprehensive characterization of protein-protein interactions perturbed by disease mutations allows for the analysis of numerous mutations and interactions within a short timeframe, significantly enhancing efficiency. MtoZ Biolabs provides protein interaction analysis services, which are highly regarded by numerous research institutions for their precision, comprehensiveness, and efficiency. MtoZ Biolabs offers cutting-edge instrumentation and technology to provide high-quality services. For more details about our services, feel free to contact us and explore the endless possibilities for collaboration.
MtoZ Biolabs, an integrated chromatography and mass spectrometry (MS) services provider.
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