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Gate-based universal quantum computers form a rapidly evolving field ofquantum computing hardware technology. In previous work, we presented a quantumalgorithm for lattice protein folding on a cubic lattice, tailored for quantumannealers. In this paper, we introduce a novel approach for solving the latticeprotein folding problem on universal gate-based quantum computingarchitectures. Lattice protein models are coarse-grained representations ofproteins that have been used extensively over the past thirty years to examinethe principles of protein folding and design.These models can be used toexplore a vast number of possible protein conformations and to infer structuralproperties of more complex atomistic protein structures. We formulate theproblem as a quantum alternating operator ansatz, a member of the wider classof variational quantum/classical hybrid algorithms. To increase the probabilityof sampling the ground state, we propose splitting the optimization probleminto hard and soft constraints. This enables us to use a previouslyunder-utilised component of the variational algorithm to constrain the searchto the subspace of solutions that satisfy the hard constraints.

A quantum alternating operator ansatz with hard and soft constraints for lattice protein folding