SODA

SODA predicts changes in protein solubility by integrating intrinsic disorder, aggregation propensity, hydrophobicity, and secondary-structure preferences to assess the impact of sequence variants and mutations.

Key Features:

• Predictive capability: Analyzes physico-chemical properties including aggregation propensity, intrinsic disorder, hydrophobicity, and secondary-structure preferences to predict solubility changes.
• Performance: Trained and benchmarked on two independent datasets and reported to excel at predicting mutations that decrease solubility.
• Speed: Returns predictions for single amino-acid substitutions within seconds.
• Mutation repertoire mapping: Estimates the effects of the full repertoire of mutations in a human germline antibody and identifies solubility hotspots on the protein surface.

Scientific Applications:

• Protein engineering: Identification of mutations that affect solubility to guide design of proteins with altered stability or solubility.
• Structural biology: Assessment of solubility changes to inform studies of folding, misfolding, and aggregation-related disease mechanisms.
• Biotechnology: Prediction of solubility effects to support development and production of stable recombinant proteins.

Methodology:

Analyzes aggregation propensity, intrinsic disorder, hydrophobicity, and secondary-structure preferences and was trained and benchmarked on two datasets.