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Updated: Jun 30, 2025

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Purification and Aggregation of the Amyloid Precursor Protein Intracellular Domain
Published on: August 28, 2012
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Insights into amyloid precursor protein target through PPI network analysis.
Annu Grewal1, Deepak Sheokand1, Raveena Chauhan1
1Toxicology and Computational Biology Group, Centre for Bioinformatics, Maharshi Dayanand University, Rohtak, Haryana, India, 124001.
Bioinformation
|March 18, 2024
Summary
Alzheimer's disease (AD) research identified key proteins involved in its development. The Amyloid precursor protein (APP) emerged as a significant hub, suggesting its potential for future AD therapies.
Area of Science:
- Neuroscience
- Biochemistry
- Computational Biology
Background:
- Alzheimer's disease (AD) is a leading cause of dementia with limited effective treatments.
- Beta-amyloid (Aβ) accumulation is implicated in AD, but targeting it has yielded limited success, indicating other factors are crucial.
- Identifying novel therapeutic targets requires understanding complex protein interactions in AD pathogenesis.
Purpose of the Study:
- To identify key hub proteins involved in Alzheimer's disease etiology using a network-based approach.
- To explore the potential of these hub proteins as targets for AD drug design.
- To analyze protein-protein interaction networks associated with AD.
Main Methods:
- Literature mining to identify AD-implicated proteins.
- Retrieval of protein-protein interactions (PPIs) from the STRING database.
- Network construction and analysis using Cytoscape 3.10.1 and CytoHubba for hub protein prediction.
Main Results:
- Six major proteins (APP, BACE1, PSEN1, MAPT, APOE4, TREM2) were identified as central to AD pathogenesis.
- The merged PPI network comprised 51 nodes and 211 edges.
- Amyloid precursor protein (APP) was identified as the highest-scoring hub protein based on multiple centrality measures.
Conclusions:
- The study highlights the critical role of specific proteins, particularly APP, in Alzheimer's disease.
- APP presents a promising target for further investigation and potential therapeutic development for AD.
- Network-based approaches are valuable for identifying novel therapeutic targets in complex diseases like AD.
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