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Photo of Anders Irbäck

Anders Irbäck

Professor

Photo of Anders Irbäck

Folding lattice proteins with quantum annealing

Author

  • Anders Irbäck
  • Lucas Knuthson
  • Sandipan Mohanty
  • Carsten Peterson

Summary, in English

Quantum annealing is a promising approach for obtaining good approximate solutions to difficult optimization problems. Folding a protein sequence into its minimum-energy structure represents such a problem. For testing new algorithms and technologies for this task, the minimal lattice-based [hydrophobic (H) or polar (P) beads] HP model is well suited, as it represents a considerable challenge despite its simplicity. The HP model has favorable interactions between adjacent, not directly bound hydrophobic residues. Here, we develop a novel spin representation for lattice protein folding tailored for quantum annealing. With a distributed encoding onto the lattice, it differs from earlier attempts to fold lattice proteins on quantum annealers, which were based upon chain growth techniques. With our encoding, the Hamiltonian by design has the quadratic structure required for calculations on an Ising-type annealer, without having to introduce any auxiliary spin variables. This property greatly facilitates the study of long chains. The approach is robust to changes in the parameters required to constrain the spin system to chainlike configurations, and performs very well in terms of solution quality. The results are evaluated against existing exact results for HP chains with up to N=30 beads with 100% hit rate, thereby also outperforming classical simulated annealing. In addition, the method allows us to recover the lowest known energies for N=48 and N=64 HP chains, with similar hit rates. These results are obtained by the commonly used hybrid quantum-classical approach. For pure quantum annealing, our method successfully folds an N=14 HP chain. The calculations were performed on a D-Wave Advantage quantum annealer.

Department/s

  • Computational Science for Health and Environment
  • eSSENCE: The e-Science Collaboration
  • Computational Biology and Biological Physics - Undergoing reorganization

Publishing year

2022-10

Language

English

Publication/Series

Physical Review Research

Volume

4

Issue

4

Document type

Journal article

Publisher

American Physical Society

Topic

  • Structural Biology
  • Other Physics Topics
  • Other Computer and Information Science

Status

Published

Research group

  • Computational Science for Health and Environment

ISBN/ISSN/Other

  • ISSN: 2643-1564