Aggrescan3D standalone package for structure-based prediction of protein aggregation properties

Area of Science:

• Computational Biology
• Protein Engineering
• Biophysics

Background:

• Protein aggregation is implicated in various diseases and affects protein stability.
• Predicting and controlling protein aggregation and solubility is crucial for protein design and biotechnology.
• Existing tools may lack flexibility or comprehensive analysis for protein aggregation properties.

Purpose of the Study:

• To introduce Aggrescan3D (A3D) standalone, a Python package for structure-based prediction of protein aggregation.
• To enable rational design of protein solubility by integrating aggregation propensity and stability predictions.
• To provide a flexible computational framework for analyzing protein aggregation, including conformational fluctuations and mutations.

Main Methods:

• Utilizes a structure-based approach for predicting protein aggregation properties.
• Combines predictions of structural aggregation propensity and protein stability.
• Analyzes the impact of protein conformational fluctuations and multiple mutations on aggregation.

Main Results:

• A3D standalone offers enhanced capabilities over its web server predecessor.
• Demonstrates successful re-design of protein solubility through combined predictions, validated experimentally.
• Provides customizable options and automated analysis for multiple mutations.

Conclusions:

• A3D standalone is a versatile tool for predicting protein aggregation and designing soluble proteins.
• The package facilitates the integration of computational tools for advanced protein engineering.
• A3D standalone is freely available under the MIT license for academic and non-profit use.