Investigating the potential for a limited quantum speedup on protein lattice problems

Protein folding is a central challenge in computational biology, with important applications molecular drug discovery and catalyst design. As hard combinatorial optimisation problem, it has been studied as potential target problem for quantum annealing. Although several experimental implementations have discussed the literature, scaling of these approaches not elucidated. In this article, we present numerical study annealing applied to large number small peptide problems, aiming infer useful insights near-term applications. We two conclusions: that even naïve annealing, when protein lattice folding, outperform classical approaches, careful engineering Hamiltonians schedules involved can deliver notable relative improvements problem. Overall, our results suggest algorithms may well offer problems structure prediction realm.