SAFEEC

SAFEEC predicts folding free energy changes caused by missense mutations in proteins to quantify effects on protein stability.

Key Features:

• SAAFEC method: Implements the Single Amino Acid Folding free Energy Changes (SAAFEC) approach for per-residue folding free energy prediction.
• Knowledge-modified MM/PBSA: Incorporates a molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) component that accounts for molecular mechanics energies and solvation effects.
• Knowledge-based terms: Integrates terms derived from statistical analysis of biophysical characteristics of proteins.
• Multiple linear regression: Combines computed and knowledge-based features in a multiple linear regression model with weighted coefficients optimized against experimental data.
• Validation performance: Reported correlation coefficient of 0.65 on 983 cases from 42 proteins in the ProTherm database.

Scientific Applications:

• Protein Stability Analysis: Predicts how single amino acid substitutions alter protein folding free energy to assess stability changes.
• Disease Association Studies: Assesses mutation-induced stability changes that can be associated with disease-related phenotypes.
• Drug Design and Development: Provides stability-impact insights useful for designing therapeutics that target or modulate protein conformations.

Methodology:

Combines the SAAFEC knowledge-modified MM/PBSA approach with knowledge-based terms derived from statistical analysis, integrated via a multiple linear regression model whose weighted coefficients were optimized against experimental data and validated on 983 cases from 42 proteins in the ProTherm database (correlation = 0.65).