I would expect that without any further insights into protein folding, a quantum method would look fairly similar to existing methods, but might have a bit more capability of exploring multiple states at the same time (without multitasking).

Here's the approach used by Rosetta, which is used in both the Rosetta@home distributed computing project, and the foldit distributed gaming project:

Rosetta's strategy for finding low energy shapes looks like this:

 

1. Start with a fully unfolded chain (like a metal chain with its ends pulled).
2. Move a part of the chain to create a new shape.
3. Calculate the energy of the new shape.
4. Accept or reject the move depending on the change in energy.
5. Repeat 2 through 4 until every part of the chain has been moved a lot of times.

 

We call this a trajectory. The end result of a trajectory is a predicted structure.

I would expect that without any further insights into protein folding, a quantum method would look fairly similar to existing methods, but might have a bit more capability of exploring multiple states at the same time (without multitasking).

Here's the approach used by Rosetta, which is used in both the Rosetta@home distributed computing project, and the foldit distributed gaming project:

Rosetta's strategy for finding low energy shapes looks like this:

1. Start with a fully unfolded chain (like a metal chain with its ends pulled).
2. Move a part of the chain to create a new shape.
3. Calculate the energy of the new shape.
4. Accept or reject the move depending on the change in energy.
5. Repeat 2 through 4 until every part of the chain has been moved a lot of times.

We call this a trajectory. The end result of a trajectory is a predicted structure.