Classical and Quantum Design of Binding Peptides Targeting Superoxide Dismutase 1 for Amyotrophic Lateral Sclerosis Treatment

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease affecting nerve cells in the brain and spinal cord, leading to paralysis and death. Existing treatments only moderately slow progression, so new therapies targeting the underlying molecular processes are needed. De novo design is a rapidly advancing tool permitting creation of novel proteins. However, designing synthetic peptides with non-natural amino acids is still a difficult optimization problem for classical computers due to its combinatorial complexity. Recent advances show promise in mapping such problems to quantum computers, which can more efficiently explore vast search spaces. This project applies classical and quantum computing to design a therapeutic peptide that binds a biologically relevant target: superoxide dismutase 1 (SOD1), a protein that causes a subset of ALS cases. In SOD1-associated ALS, the SOD1 dimer falls apart, leading to harmful protein misfolding and aggregation. A peptide that holds this pair together could prevent aggregation. With the Rosetta and Masala software suites, we have designed and validated peptides targeting SOD1 using both classical and quantum computers. This represents a novel approach toward treatment of a currently incurable neurodegenerative disease.