MutateX

MutateX automates in-silico saturation mutagenesis of protein structures and structural ensembles to predict free energy changes (ΔΔG) associated with systematic residue substitutions.

Key Features:

• Automation and high-throughput processing: Automates input preparation, systematic mutation setup, parallel execution of FoldX, and output generation for large-scale saturation mutagenesis studies.
• Systematic mutation analysis: Systematically mutates each residue in a protein or protein complex to all other amino acids to evaluate effects on stability and interactions.
• FoldX empirical free energy calculations: Uses the FoldX empirical free energy function to estimate ΔΔG values for individual mutations.
• Support for ensembles and post-translational modifications: Performs ΔΔG calculations over protein structural ensembles and can estimate free-energy changes due to post-translational modifications.

Scientific Applications:

• Analysis of disease-associated mutations: Interprets stability and interaction changes of disease-associated mutations at the atomic level using predicted ΔΔG values.
• Rational design of protein variants: Guides rational design of protein variants and mutagenesis experiments by predicting mutation-induced ΔΔG effects.
• Optimization of enzymes and interfaces: Assists optimization of industrial enzymes and protein–protein interfaces by evaluating ΔΔG changes from substitutions.
• Studies on cancer-related proteins: Applied to cancer-related proteins to rationalize known mutations and to inform experimental follow-up.

Methodology:

MutateX implements systematic residue-by-residue mutagenesis to all amino acids, prepares inputs and runs FoldX in parallel, and relies on the FoldX empirical free energy function to compute ΔΔG values; it also supports calculations over structural ensembles and for post-translational modifications and is implemented in Python.