PyTorch Frustratometer: An Ultra-fast, Parallelized Tool for Proteome-Scale Local Energetic Frustration Analysis

PyTorch Frustratometer accelerates proteome-scale local energetic frustration analysis by 70–13,000× on a single GPU while matching the original FrustratometeR results on CATH v4.4 S40.

• Why it matters: Local energetic frustration is linked to protein stability and function, but exhaustive frustration calculations are computationally expensive, limiting large-scale scanning across many proteins and mutations.
• What they did: The authors reimplemented FrustratometeR in PyTorch, classifying residue or contact energetics as minimally, highly, or neutral versus decoys, and benchmarked against the original on CATH v4.4 S40.
• The result: Across all three frustration modes and mutational scanning, the PyTorch version produces near-identical outputs to the original algorithm, enabling much faster proteome-scale local frustration mapping.

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