Mining databases for protein aggregation: a review

Area of Science:

• Biochemistry and Molecular Biology
• Computational Biology
• Disease Pathogenesis Research

Background:

• Protein aggregation is a key indicator of protein instability and linked to numerous diseases.
• Understanding protein aggregation mechanisms is vital for disease etiology and pathogenesis research.
• Computational biology advances have led to a proliferation of protein aggregation data across diverse repositories.

Purpose of the Study:

• To review and analyze existing protein aggregation data resources.
• To map and visualize the associations between aggregation databases and other bioinformatics tools.
• To highlight the need for a unified platform for protein aggregation data.

Main Methods:

• Systematic review of protein aggregation data repositories.
• Categorization of repositories into protein-based, fragment-based, and disease-based.
• Network mapping and visualization of database interconnections and community annotation roles.

Main Results:

• Identified and categorized various scattered protein aggregation data resources.
• Visualized the landscape of current aggregation databases and their links to other tools.
• Demonstrated the value of community annotation in aggregating biological knowledge.

Conclusions:

• Existing protein aggregation data is fragmented across numerous sources.
• A comprehensive network map aids in understanding the current data landscape.
• Unification of aggregation databases into a common platform is necessary for efficient research.