• Corpus ID: 246430642

Gate-based Quantum Computing for Protein Design

@inproceedings{Khatami2022GatebasedQC,
  title={Gate-based Quantum Computing for Protein Design},
  author={Mohammad Hassan Khatami and Udson C. Mendes and Nathan Wiebe and Philip M. Kim},
  year={2022}
}
Protein design is a technique to engineer proteins by modifying their sequence to obtain novel functionalities. In this method, amino acids in the sequence are permutated to find the low energy states satisfying the configuration. However, exploring all possible combinations of amino acids is generally impossible to achieve on conventional computers due to the exponential growth of possibilities with the number of designable sites. Thus, sampling methods are currently used as a conventional… 
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References

SHOWING 1-10 OF 54 REFERENCES

Designing Peptides on a Quantum Computer

This work presents 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, using a large side-chain rotamer library and the full Rosetta energy function.

Resource-efficient quantum algorithm for protein folding

A model Hamiltonian with O ( N 4 ) scaling and a corresponding quantum variational algorithm for the folding of a polymer chain with N monomers on a lattice is presented, reflecting many physico-chemical properties of the protein, reducing the gap between coarse-grained representations and mere lattice models.

A quantum alternating operator ansatz with hard and soft constraints for lattice protein folding

A novel approach for solving the lattice protein folding problem on universal gate-based quantum computing architectures as a quantum alternating operator ansatz, a member of the wider class of variational quantum/classical hybrid algorithms.

Coarse-grained lattice protein folding on a quantum annealer

This work sets a new record for lattice protein folding on a quantum annealer by folding Chignolin on a planar lattice and Trp-Cage on a cubic lattice.

Finding low-energy conformations of lattice protein models by quantum annealing

This report presents a benchmark implementation of quantum annealing for lattice protein folding problems (six different experiments up to 81 superconducting quantum bits) and paves the way towards studying optimization problems in biophysics and statistical mechanics using quantum devices.

Experimental one-way quantum computing

The implementation of Grover's search algorithm demonstrates that one-way quantum computation is ideally suited for such tasks.

Validating quantum computers using randomized model circuits

A single-number metric, quantum volume, that can be measured using a concrete protocol on near-term quantum computers of modest size, and measured on several state-of-the-art transmon devices, finding values as high as 16.5%.

On the need for large Quantum depth

The results show that relative to oracles, doubling the quantum circuit depth indeed gives the hybrid model more power, and this cannot be traded by classical computation.

A fast quantum mechanical algorithm for database search

In early 1994, it was demonstrated that a quantum mechanical computer could efficiently solve a well-known problem for which there was no known efficient algorithm using classical computers, i.e. testing whether or not a given integer, N, is prime, in a time which is a finite power of o (logN) .

Quantum Error Correction Protects Quantum Search Algorithms Against Decoherence

This contribution investigates the effect of quantum noise on the performance of QSAs, in terms of their success probability as a function of the database size to be searched, when decoherence is modelled by depolarizing channels’ deleterious effects imposed on the quantum gates.
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