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LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes
BACKGROUND: The increasing amount of chemical reaction data makes traditional ways to navigate its corpus less effective, while the demand for novel approaches and instruments is rising. Recent data science and machine learning techniques support the development of new ways to extract value from the...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067316/ https://www.ncbi.nlm.nih.gov/pubmed/37005691 http://dx.doi.org/10.1186/s13321-023-00714-y |
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author | Pasquini, Marta Stenta, Marco |
author_facet | Pasquini, Marta Stenta, Marco |
author_sort | Pasquini, Marta |
collection | PubMed |
description | BACKGROUND: The increasing amount of chemical reaction data makes traditional ways to navigate its corpus less effective, while the demand for novel approaches and instruments is rising. Recent data science and machine learning techniques support the development of new ways to extract value from the available reaction data. On the one side, Computer-Aided Synthesis Planning tools can predict synthetic routes in a model-driven approach; on the other side, experimental routes can be extracted from the Network of Organic Chemistry, in which reaction data are linked in a network. In this context, the need to combine, compare and analyze synthetic routes generated by different sources arises naturally. RESULTS: Here we present LinChemIn, a python toolkit that allows chemoinformatics operations on synthetic routes and reaction networks. Wrapping some third-party packages for handling graph arithmetic and chemoinformatics and implementing new data models and functionalities, LinChemIn allows the interconversion between data formats and data models and enables route-level analysis and operations, including route comparison and descriptors calculation. Object-Oriented Design principles inspire the software architecture, and the modules are structured to maximize code reusability and support code testing and refactoring. The code structure should facilitate external contributions, thus encouraging open and collaborative software development. CONCLUSIONS: The current version of LinChemIn allows users to combine synthetic routes generated from various tools and analyze them, and constitutes an open and extensible framework capable of incorporating contributions from the community and fostering scientific discussion. Our roadmap envisages the development of sophisticated metrics for routes evaluation, a multi-parameter scoring system, and the implementation of an entire “ecosystem” of functionalities operating on synthetic routes. LinChemIn is freely available at https://github.com/syngenta/linchemin. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13321-023-00714-y. |
format | Online Article Text |
id | pubmed-10067316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-100673162023-04-03 LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes Pasquini, Marta Stenta, Marco J Cheminform Software BACKGROUND: The increasing amount of chemical reaction data makes traditional ways to navigate its corpus less effective, while the demand for novel approaches and instruments is rising. Recent data science and machine learning techniques support the development of new ways to extract value from the available reaction data. On the one side, Computer-Aided Synthesis Planning tools can predict synthetic routes in a model-driven approach; on the other side, experimental routes can be extracted from the Network of Organic Chemistry, in which reaction data are linked in a network. In this context, the need to combine, compare and analyze synthetic routes generated by different sources arises naturally. RESULTS: Here we present LinChemIn, a python toolkit that allows chemoinformatics operations on synthetic routes and reaction networks. Wrapping some third-party packages for handling graph arithmetic and chemoinformatics and implementing new data models and functionalities, LinChemIn allows the interconversion between data formats and data models and enables route-level analysis and operations, including route comparison and descriptors calculation. Object-Oriented Design principles inspire the software architecture, and the modules are structured to maximize code reusability and support code testing and refactoring. The code structure should facilitate external contributions, thus encouraging open and collaborative software development. CONCLUSIONS: The current version of LinChemIn allows users to combine synthetic routes generated from various tools and analyze them, and constitutes an open and extensible framework capable of incorporating contributions from the community and fostering scientific discussion. Our roadmap envisages the development of sophisticated metrics for routes evaluation, a multi-parameter scoring system, and the implementation of an entire “ecosystem” of functionalities operating on synthetic routes. LinChemIn is freely available at https://github.com/syngenta/linchemin. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13321-023-00714-y. Springer International Publishing 2023-04-01 /pmc/articles/PMC10067316/ /pubmed/37005691 http://dx.doi.org/10.1186/s13321-023-00714-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Pasquini, Marta Stenta, Marco LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes |
title | LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes |
title_full | LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes |
title_fullStr | LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes |
title_full_unstemmed | LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes |
title_short | LinChemIn: SynGraph—a data model and a toolkit to analyze and compare synthetic routes |
title_sort | linchemin: syngraph—a data model and a toolkit to analyze and compare synthetic routes |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067316/ https://www.ncbi.nlm.nih.gov/pubmed/37005691 http://dx.doi.org/10.1186/s13321-023-00714-y |
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