ENDURE

ENDURE analyzes per-residue and multi-mutant interaction energies to quantify energetic contributions of amino acid mutations and guide protein design and stability optimization using Rosetta energy calculations and machine learning.

Key Features:

• Per-Residue Energy Analysis: Per-residue energy analysis using the Rosetta energy function to quantify energetic contributions of specific amino acid mutations within protein structures.
• Sum of Interaction Energies Calculations: Calculation of the sum of interaction energies for single and multi-mutant designs to assess cumulative energetic effects of multiple mutations.
• Residue Depth Analysis: Residue depth analysis to evaluate how mutations at different spatial layers within a protein structure influence energetic stability.
• Machine Learning–Guided Mutant Prioritization: Application of machine learning to streamline selection and prioritization of promising mutants for experimental validation.

Scientific Applications:

• PET-degrading Enzyme Optimization: Identification of mutations that enhance the thermodynamic stability of a designed polyethylene terephthalate (PET)-degrading enzyme.
• Protein Stability Engineering: Prioritization of favorable combinations of amino acid interactions and mutants for experimental characterization in protein design projects.

Methodology:

Per-residue energy analysis using the Rosetta energy function; calculation of sum of interaction energies for single and multi-mutant designs; residue depth analysis; and application of machine learning for mutant selection.