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Perspective on the Current State-of-the-Art of Quantum Computing for Drug Discovery Applications
[Image: see text] Computational chemistry is an essential tool in the pharmaceutical industry. Quantum computing is a fast evolving technology that promises to completely shift the computational capabilities in many areas of chemical research by bringing into reach currently impossible calculations....
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753588/ https://www.ncbi.nlm.nih.gov/pubmed/36355616 http://dx.doi.org/10.1021/acs.jctc.2c00574 |
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author | Blunt, Nick S. Camps, Joan Crawford, Ophelia Izsák, Róbert Leontica, Sebastian Mirani, Arjun Moylett, Alexandra E. Scivier, Sam A. Sünderhauf, Christoph Schopf, Patrick Taylor, Jacob M. Holzmann, Nicole |
author_facet | Blunt, Nick S. Camps, Joan Crawford, Ophelia Izsák, Róbert Leontica, Sebastian Mirani, Arjun Moylett, Alexandra E. Scivier, Sam A. Sünderhauf, Christoph Schopf, Patrick Taylor, Jacob M. Holzmann, Nicole |
author_sort | Blunt, Nick S. |
collection | PubMed |
description | [Image: see text] Computational chemistry is an essential tool in the pharmaceutical industry. Quantum computing is a fast evolving technology that promises to completely shift the computational capabilities in many areas of chemical research by bringing into reach currently impossible calculations. This perspective illustrates the near-future applicability of quantum computation of molecules to pharmaceutical problems. We briefly summarize and compare the scaling properties of state-of-the-art quantum algorithms and provide novel estimates of the quantum computational cost of simulating progressively larger embedding regions of a pharmaceutically relevant covalent protein–drug complex involving the drug Ibrutinib. Carrying out these calculations requires an error-corrected quantum architecture that we describe. Our estimates showcase that recent developments on quantum phase estimation algorithms have dramatically reduced the quantum resources needed to run fully quantum calculations in active spaces of around 50 orbitals and electrons, from estimated over 1000 years using the Trotterization approach to just a few days with sparse qubitization, painting a picture of fast and exciting progress in this nascent field. |
format | Online Article Text |
id | pubmed-9753588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-97535882022-12-16 Perspective on the Current State-of-the-Art of Quantum Computing for Drug Discovery Applications Blunt, Nick S. Camps, Joan Crawford, Ophelia Izsák, Róbert Leontica, Sebastian Mirani, Arjun Moylett, Alexandra E. Scivier, Sam A. Sünderhauf, Christoph Schopf, Patrick Taylor, Jacob M. Holzmann, Nicole J Chem Theory Comput [Image: see text] Computational chemistry is an essential tool in the pharmaceutical industry. Quantum computing is a fast evolving technology that promises to completely shift the computational capabilities in many areas of chemical research by bringing into reach currently impossible calculations. This perspective illustrates the near-future applicability of quantum computation of molecules to pharmaceutical problems. We briefly summarize and compare the scaling properties of state-of-the-art quantum algorithms and provide novel estimates of the quantum computational cost of simulating progressively larger embedding regions of a pharmaceutically relevant covalent protein–drug complex involving the drug Ibrutinib. Carrying out these calculations requires an error-corrected quantum architecture that we describe. Our estimates showcase that recent developments on quantum phase estimation algorithms have dramatically reduced the quantum resources needed to run fully quantum calculations in active spaces of around 50 orbitals and electrons, from estimated over 1000 years using the Trotterization approach to just a few days with sparse qubitization, painting a picture of fast and exciting progress in this nascent field. American Chemical Society 2022-11-10 2022-12-13 /pmc/articles/PMC9753588/ /pubmed/36355616 http://dx.doi.org/10.1021/acs.jctc.2c00574 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Blunt, Nick S. Camps, Joan Crawford, Ophelia Izsák, Róbert Leontica, Sebastian Mirani, Arjun Moylett, Alexandra E. Scivier, Sam A. Sünderhauf, Christoph Schopf, Patrick Taylor, Jacob M. Holzmann, Nicole Perspective on the Current State-of-the-Art of Quantum Computing for Drug Discovery Applications |
title | Perspective on
the Current State-of-the-Art of Quantum
Computing for Drug Discovery Applications |
title_full | Perspective on
the Current State-of-the-Art of Quantum
Computing for Drug Discovery Applications |
title_fullStr | Perspective on
the Current State-of-the-Art of Quantum
Computing for Drug Discovery Applications |
title_full_unstemmed | Perspective on
the Current State-of-the-Art of Quantum
Computing for Drug Discovery Applications |
title_short | Perspective on
the Current State-of-the-Art of Quantum
Computing for Drug Discovery Applications |
title_sort | perspective on
the current state-of-the-art of quantum
computing for drug discovery applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753588/ https://www.ncbi.nlm.nih.gov/pubmed/36355616 http://dx.doi.org/10.1021/acs.jctc.2c00574 |
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