The future of drug development with quantum computing.
Bonde, Bhushan, Patil, Pratik and Choubey, Bhaskar (2023) The future of drug development with quantum computing. In: High Performance Computing for Drug Discovery and Biomedicine. Methods in Molecular Biology, 2716 (2716). Humana Press, New, pp. 153-179. ISBN 9781071634486
Full text not available from this repository.Abstract
Novel medication development is a time-consuming and expensive multistage procedure. Recent technology developments have lowered timeframes, complexity, and cost dramatically. Current research projects are driven by AI and machine learning computational models. This chapter will introduce quantum computing (QC) to drug development issues and provide an in-depth discussion of how quantum computing may be used to solve various drug discovery problems. We will first discuss the fundamentals of QC, a review of known Hamiltonians, how to apply Hamiltonians to drug discovery challenges, and what the noisy intermediate-scale quantum (NISQ) era methods and their limitations are.We will further discuss how these NISQ era techniques can aid with specific drug discovery challenges, including protein folding, molecular docking, AI-/ML-based optimization, and novel modalities for small molecules and RNA secondary structures. Consequently, we will discuss the latest QC landscape's opportunities and challenges. [Abstract copyright: © 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.]
Item Type: | Book Section |
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Uncontrolled Keywords: | quantum theory, noisy intermediate-scale quantum (NISQ) era, protein folding, molecular docking simulation, computing methodologies, variational quantum eigensolver (VQE), drug discovery, drug development, quantum computing, hybrid compute |
Subjects: | Q Science > Q Science (General) T Technology > T Technology (General) |
Divisions: | Faculty of Health & Science > Department of Science & Technology |
SWORD Depositor: | Pub Router |
Depositing User: | Pub Router |
Date Deposited: | 28 Sep 2023 09:24 |
Last Modified: | 28 Sep 2023 09:24 |
URI: | https://oars.uos.ac.uk/id/eprint/3353 |