  Protein folding processes are a vital aspect of molecular biology that is
hard to simulate with conventional computers. Quantum algorithms have been
proven superior for certain problems and may help tackle this complex life
science challenge. We analyze the resource requirements for simulating protein
folding on a quantum computer, assessing this problem's feasibility in the
current and near-future technological landscape. We calculate the minimum
number of qubits, interactions, and two-qubit gates necessary to build a
heuristic quantum algorithm with the specific information of a folding problem.
Particularly, we focus on the resources needed to build quantum operations
based on the Hamiltonian linked to the protein folding models for a given amino
acid count. Such operations are a fundamental component of these quantum
algorithms, guiding the evolution of the quantum state for efficient
computations. Specifically, we study course-grained folding models on the
lattice and the fixed backbone side-chain conformation model and assess their
compatibility with the constraints of existing quantum hardware given different
bit-encodings. We conclude that the number of qubits required falls within
current technological capabilities. However, the limiting factor is the high
number of interactions in the Hamiltonian, resulting in a quantum gate count
unavailable today.
