RosettaDDGPrediction

RosettaDDGPrediction predicts folding/unfolding ΔΔG in monomeric proteins and binding free energy changes in protein complexes upon amino acid substitutions using Rosetta-based structure modeling.

Key Features:

• Rosetta-Based ΔΔG Calculations: Integrates Rosetta protocols to compute mutation-induced changes in protein stability and protein–protein binding free energy.
• High-Throughput Mutation Screening: Implements a Python wrapper to automate large-scale ΔΔG calculations, aggregate variant data, and manage multi-mutation analyses.

Scientific Applications:

• Variant and Interaction Analysis: Evaluates structural and energetic effects of disease-associated variants, protein stability changes, protein–protein interactions, disordered motifs, and phosphomimetics.

Methodology:

RosettaDDGPrediction applies structure-based Rosetta ΔΔG protocols to modeled or experimental protein structures, performs energy minimization and mutation modeling, and computes free energy differences between wild-type and variant forms within an automated high-throughput framework.