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Investigating the potential for a limited quantum speedup on protein lattice problems

Abstract:
Protein folding, the determination of the lowest-energy configuration of a protein, is an unsolved computational problem. If protein folding could be solved, it would lead to significant advances in molecular biology, and technological development in areas such as drug discovery and catalyst design. As a hard combinatorial optimisation problem, protein folding has been studied as a potential target problem for adiabatic quantum computing. Although several experimental implementations have been discussed in the literature, the computational scaling of these approaches has not been elucidated. In this article, we present a numerical study of the (stoquastic) adiabatic quantum algorithm applied to protein lattice folding. Using exact numerical modelling of small systems, we find that the time-to-solution metric scales exponentially with peptide length, even for small peptides. However, comparison with classical heuristics for optimisation indicates a potential limited quantum speedup. Overall, our results suggest that quantum algorithms may well offer improvements for problems in the protein folding and structure prediction realm.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1088/1367-2630/ac29ff

Authors

More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
More by this author
Institution:
University of Oxford
Department:
STATISTICS
Sub department:
Statistics
Role:
Author
ORCID:
0000-0003-1731-8405
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
ORCID:
0000-0002-7766-5348


Publisher:
IOP Science
Journal:
New Journal of Physics More from this journal
Volume:
23
Article number:
103030
Publication date:
2021-09-24
Acceptance date:
2021-09-24
DOI:
EISSN:
1367-2630


Language:
English
Keywords:
Pubs id:
1099846
Local pid:
pubs:1099846
Deposit date:
2020-10-30
ARK identifier:

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