RT Journal Article
SR Electronic
T1 Designing Peptides on a Quantum Computer
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 752485
DO 10.1101/752485
A1 Vikram Khipple Mulligan
A1 Hans Melo
A1 Haley Irene Merritt
A1 Stewart Slocum
A1 Brian D. Weitzner
A1 Andrew M. Watkins
A1 P. Douglas Renfrew
A1 Craig Pelissier
A1 Paramjit S. Arora
A1 Richard Bonneau
YR 2020
UL http://biorxiv.org/content/early/2020/03/11/752485.abstract
AB Although a wide variety of quantum computers are currently being developed, actual computational results have been largely restricted to contrived, artificial tasks. Finding ways to apply quantum computers to useful, real-world computational tasks remains an active research area. Here we describe our mapping of the protein design problem to the D-Wave quantum annealer. We present a system whereby Rosetta, a state-of-the-art protein design software suite, interfaces with the D-Wave quantum processing unit to find amino acid side chain identities and conformations to stabilize a fixed protein backbone. Our approach, which we call the QPacker, uses a large side-chain rotamer library and the full Rosetta energy function, and in no way reduces the design task to a simpler format. We demonstrate that quantum annealer-based design can be applied to complex real-world design tasks, producing designed molecules comparable to those produced by widely adopted classical design approaches. We also show through large-scale classical folding simulations that the results produced on the quantum annealer can inform wet-lab experiments. For design tasks that scale exponentially on classical computers, the QPacker achieves nearly constant runtime performance over the range of problem sizes that could be tested. We anticipate better than classical performance scaling as quantum computers mature.