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In this report, we explore the use of a quantum optimization algorithm forobtaining low energy conformations of protein models. We discuss mappingsbetween protein models and optimization variables, which are in turn mapped toa system of coupled quantum bits. General strategies are given for constructingHamiltonians to be used to solve optimization problems ofphysical/chemical/biological interest via quantum computation by adiabaticevolution. As an example, we implement the Hamiltonian corresponding to theHydrophobic-Polar (HP) model for protein folding. Furthermore, we present anapproach to reduce the resulting Hamiltonian to two-body terms gearing towardsan experimental realization.

physical review. a, atomic, molecular, and optical physics/physical review, a, atomic, molecular, and optical physics

On the construction of model Hamiltonians for adiabatic quantum  computation and its application to finding low energy conformations of  lattice protein models