CCSOL

ccSOL omics predicts protein solubility at proteome scale using physicochemical properties of amino acid sequences.

Key Features:

• Proteome-wide predictions: Provides solubility predictions across entire proteomes for large-scale analyses.
• Identification of soluble fragments: Detects soluble fragments within protein sequences to inform construct design and engineering.
• Exhaustive single-point mutation analysis: Evaluates the impact of individual point mutations on predicted protein solubility.
• Physicochemical-property-based prediction: Bases predictions on analysis of coil/disorder propensities, hydrophobicity/hydrophilicity, and β-sheet and α-helix propensities.

Scientific Applications:

• Proteome-scale solubility profiling: Assess solubility properties across whole proteomes for structural biology and proteomics studies.
• Protein engineering and construct design: Guide design of protein constructs and variants with improved solubility.
• Mutation impact analysis: Investigate how single-point mutations affect protein solubility and stability.

Methodology:

Predictive model built on analysis of physicochemical properties (coil/disorder propensities; hydrophobicity/hydrophilicity; β-sheet and α-helix propensities); trained on 36,990 Target Track entries (reported 79% accuracy) and validated on three independent datasets totaling 31,760 proteins with <30% sequence similarity (reported 74% accuracy).