A3DyDB: exploring structural aggregation propensities in the yeast proteome

Area of Science:

• Biochemistry
• Structural Biology
• Computational Biology

Background:

• Saccharomyces cerevisiae is a key model organism for eukaryotic cellular processes.
• Limited structural data hinders understanding of yeast protein aggregation and function.
• Protein aggregation is implicated in various cellular mechanisms and diseases.

Purpose of the Study:

• To create a comprehensive database of aggregation propensity predictions for the Saccharomyces cerevisiae proteome.
• To provide a tool for exploring structure-based aggregation properties of yeast proteins.
• To enable the analysis of mutation effects on protein stability and solubility.

Main Methods:

• Utilized Aggrescan 3D (A3D) algorithm for predicting intrinsic protein aggregation propensities.
• Employed AlphaFold2 (AF2) to generate 3D structural models for the S. cerevisiae proteome.
• Compiled predictions for 6039 yeast proteins into the A3D yeast database (A3DyDB).

Main Results:

• The A3D yeast database (A3DyDB) provides structure-based aggregation propensity predictions for 6039 S. cerevisiae proteins.
• A user-friendly interface allows querying, browsing, and visualization of aggregation data.
• The database facilitates evaluation of mutation impacts on protein stability and solubility.

Conclusions:

• A3DyDB fills a critical gap in yeast research resources.
• Enables exploration of correlations between structural aggregation propensity and protein properties.
• Expected to become a valuable tool for modeling protein aggregation in budding yeast.