D-Wave goes public with 81-qubit protein modeling
All together now: ‘It’s quantum, innit?’
D-Wave – whose claims to have a working quantum computer have been met with skepticism and major contracts in equal measure – has published a paper in Nature in which it demonstrates the application of quantum annealing to protein folding analysis.
Protein folding is a difficult problem in the classical world, because of the vast number of possible solutions. As D-Wave’s authors put it in their paper (online in full here): “Finding low-energy threedimensional structures is an intractable problem even in the simplest model, the Hydrophobic-Polar (HP) model.”
In nature, proteins should normally fold themselves to a “ground state” – the lowest possible energy configuration for that particular combination of amino acids – because the low-energy state is the most stable. When folding goes wrong in humans, it can result in a range of diseases like Alzheimer’s, Huntington’s and Parkinsons.
However, predicting the “correct” folding for any given protein on a computer is difficult and time-consuming – so much so that scientists have found that crowd-sourcing using the game FoldIt can get results where supercomputers don’t.
D-Wave’s paper claims to demonstrate the first application of quantum principles to solving protein folding. It’s only been performed on a small scale – using 81 qubits – and is intended as a benchmark.
Moreover, the authors state that the scale of the problem they’ve demonstrated would still be solvable using a classical computer. “Even though the cases presented here still can be solved on a classical computer by exact enumeration (the six-amino-acid problem has only 40 possible configurations), it is remarkable that the device anneals to the ground state of a search space of 281 possible computational outcomes. This study provides a proof-of-principle that optimization of biophysical problems such as protein folding can be studied using quantum mechanical devices,” the authors write.
The Register will watch with interest to see how well the D-Wave paper stands up to scrutiny. ®
Sponsored: Benefits from the lessons learned in HPC