Selected examples illustrating the practical application of quantum computing in protein science have been published in the scientific literature (Table ) and covered by three excellent recent reviews . Several categories of problems have already been tackled by quantum algorithms. For instance, Variational Quantum Eigensolver Algorithms have been applied to find low-energy states of biomolecular systems -albeit for relatively small systems -which is a crucial step for molecular simulations, protein folding, or simulations of enzymatic reactions . Protein folding and molecular docking can also be formulated as a quadratic unconstrained binary optimisation (QUBO) problem on a lattice, solvable using Quantum Approximate Optimization Algorithm . Similarly, sequence similarity calculations can be reformulated as a QUBO problem using conflict graphs , showing great promise for future quantum-based BLAST-like algorithms. Graph-based approaches have also shown potential in molecular docking, for which Gaussian Boson Sampling can produce stable docking configurations .