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Protein folding processes are a vital aspect of molecular biology that ishard to simulate with conventional computers. Quantum algorithms have beenproven superior for certain problems and may help tackle this complex lifescience challenge. We analyze the resource requirements for simulating proteinfolding on a quantum computer, assessing this problem's feasibility in thecurrent and near-future technological landscape. We calculate the minimumnumber of qubits, interactions, and two-qubit gates necessary to build aheuristic quantum algorithm with the specific information of a folding problem.Particularly, we focus on the resources needed to build quantum operationsbased on the Hamiltonian linked to the protein folding models for a given aminoacid count. Such operations are a fundamental component of these quantumalgorithms, guiding the evolution of the quantum state for efficientcomputations. Specifically, we study course-grained folding models on thelattice and the fixed backbone side-chain conformation model and assess theircompatibility with the constraints of existing quantum hardware given differentbit-encodings. We conclude that the number of qubits required falls withincurrent technological capabilities. However, the limiting factor is the highnumber of interactions in the Hamiltonian, resulting in a quantum gate countunavailable today.

Resource analysis of quantum algorithms for coarse-grained protein folding models