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Finding the K best synthesis plans
In synthesis planning, the goal is to synthesize a target molecule from available starting materials, possibly optimizing costs such as price or environmental impact of the process. Current algorithmic approaches to synthesis planning are usually based on selecting a bond set and finding a single go...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5887019/ https://www.ncbi.nlm.nih.gov/pubmed/29623440 http://dx.doi.org/10.1186/s13321-018-0273-z |
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author | Fagerberg, Rolf Flamm, Christoph Kianian, Rojin Merkle, Daniel Stadler, Peter F. |
author_facet | Fagerberg, Rolf Flamm, Christoph Kianian, Rojin Merkle, Daniel Stadler, Peter F. |
author_sort | Fagerberg, Rolf |
collection | PubMed |
description | In synthesis planning, the goal is to synthesize a target molecule from available starting materials, possibly optimizing costs such as price or environmental impact of the process. Current algorithmic approaches to synthesis planning are usually based on selecting a bond set and finding a single good plan among those induced by it. We demonstrate that synthesis planning can be phrased as a combinatorial optimization problem on hypergraphs by modeling individual synthesis plans as directed hyperpaths embedded in a hypergraph of reactions (HoR) representing the chemistry of interest. As a consequence, a polynomial time algorithm to find the K shortest hyperpaths can be used to compute the K best synthesis plans for a given target molecule. Having K good plans to choose from has many benefits: it makes the synthesis planning process much more robust when in later stages adding further chemical detail, it allows one to combine several notions of cost, and it provides a way to deal with imprecise yield estimates. A bond set gives rise to a HoR in a natural way. However, our modeling is not restricted to bond set based approaches—any set of known reactions and starting materials can be used to define a HoR. We also discuss classical quality measures for synthesis plans, such as overall yield and convergency, and demonstrate that convergency has a built-in inconsistency which could render its use in synthesis planning questionable. Decalin is used as an illustrative example of the use and implications of our results. [Image: see text] |
format | Online Article Text |
id | pubmed-5887019 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-58870192018-04-12 Finding the K best synthesis plans Fagerberg, Rolf Flamm, Christoph Kianian, Rojin Merkle, Daniel Stadler, Peter F. J Cheminform Research In synthesis planning, the goal is to synthesize a target molecule from available starting materials, possibly optimizing costs such as price or environmental impact of the process. Current algorithmic approaches to synthesis planning are usually based on selecting a bond set and finding a single good plan among those induced by it. We demonstrate that synthesis planning can be phrased as a combinatorial optimization problem on hypergraphs by modeling individual synthesis plans as directed hyperpaths embedded in a hypergraph of reactions (HoR) representing the chemistry of interest. As a consequence, a polynomial time algorithm to find the K shortest hyperpaths can be used to compute the K best synthesis plans for a given target molecule. Having K good plans to choose from has many benefits: it makes the synthesis planning process much more robust when in later stages adding further chemical detail, it allows one to combine several notions of cost, and it provides a way to deal with imprecise yield estimates. A bond set gives rise to a HoR in a natural way. However, our modeling is not restricted to bond set based approaches—any set of known reactions and starting materials can be used to define a HoR. We also discuss classical quality measures for synthesis plans, such as overall yield and convergency, and demonstrate that convergency has a built-in inconsistency which could render its use in synthesis planning questionable. Decalin is used as an illustrative example of the use and implications of our results. [Image: see text] Springer International Publishing 2018-04-05 /pmc/articles/PMC5887019/ /pubmed/29623440 http://dx.doi.org/10.1186/s13321-018-0273-z Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Fagerberg, Rolf Flamm, Christoph Kianian, Rojin Merkle, Daniel Stadler, Peter F. Finding the K best synthesis plans |
title | Finding the K best synthesis plans |
title_full | Finding the K best synthesis plans |
title_fullStr | Finding the K best synthesis plans |
title_full_unstemmed | Finding the K best synthesis plans |
title_short | Finding the K best synthesis plans |
title_sort | finding the k best synthesis plans |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5887019/ https://www.ncbi.nlm.nih.gov/pubmed/29623440 http://dx.doi.org/10.1186/s13321-018-0273-z |
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