The prospects of Monte Carlo antibody loop modelling on a fault-tolerant quantum computer
Open accessAbstract
Quantum computing for the biological sciences is an area of rapidly growing interest, but specific industrial applications remain elusive. Quantum Markov chain Monte Carlo has been proposed as a method for accelerating a broad class of computational problems, including problems of pharmaceutical interest. Here we investigate the prospects of quantum advantage via this approach, by applying it to the problem of modelling antibody structure, a crucial task in drug development. To minimize the resources required while maintaining pharmaceutical-level accuracy, we propose a specific encoding of molecular dihedral angles into registers of qubits and a method for implementing, in quantum superposition, a Markov chain Monte Carlo update step based on a classical all-atom force field. We give the first detailed analysis of the resources required to solve a problem of industrial size and relevance and find that, though the time and space requirements of using a quantum computer in this way are considerable, continued technological improvements could bring the required resources within reach in the future.
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Fault-tolerant qubits would also increase the time requested for each elementary operation.
“one should also consider the increased time requested for each elementary operation [53, 54]”
From Quantum computing algorithms: getting closer to critical problems in computational biology (2022) · cites this paper as [54]
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- Authors
- Allcock, J., Vangone, A., Meyder, A., Adaszewski, S., Strahm, M., Hsieh, C.-Y., & Zhang, S.
- Affiliations
- Tencent (China) (CN)
- Roche Pharma AG (Germany) (DE)
- F. Hoffmann-La Roche AG (CH)
- Corresponding author
- Allcock, Jonathan
- Vangone, Anna
- Zhang, Shengyu
- Venue
- Frontiers in Drug Discovery
- Publisher
- Frontiers Media SA
- Published
- 2022-07-08
- Volume
- 2
- ISSN
- 2674-0338 (ISSN-L)
- OpenAlex
- W4284879541
- Cited by
- 12
- References
- 61
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 4 · 2023: 3 · 2022: 1
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Drug Discovery (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- quantum advantage, fault-tolerant quantum computing, all-atom force field, quantum resource estimation, antibody structure prediction, drug development
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