Yeah but not really "It worked, but not particularly well. According to the researchers, 10,000 measurements using an 81-qubit version of the experiment gave the correct answer just 13 times. This was owing, in part, to the limitations of the machine itself, and in part to thermal noise that disrupted the computation. It’s also worth pointing that conventional computers could already solve these particular protein folding problems."

This paper provides an approach for a simplified representation of a problem, so called lattice protein folding, for a very small protein.

In particular, they find a 2D lattice fold of a 6-amino acid sequence (PSVKMA). 2D lattice fold means that every amino acid must occupy discrete Euclidean coordinates (i.e. (0,2) or (2,1)), which allows you to convert the search into optimization problem.

Couple of years later (using more tricks and newer D-Wave machine), we pushed the limit to 10 amino acids on the planar grid, and generalized the approach to 3D grids as well (where we were able to obtain a lattice fold of 8 amino acid sequence) [1]. This is actually still well below what your laptop can search with some effort.

On the other hand, AlphaFold2 predicts coordinates of the C-alpha atoms in the continuous space, so the predicted structure would actually be an potential direct substitute for experimental structure (similar to, i.e. a structure obtained using homology modelling).

[1] https://arxiv.org/abs/1811.00713

To be fair, "solves protein folding problem" is a lot narrower than "solves protein folding".

E.g. "Multivac solves physics problem" vs. "Multivac solves physics"