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Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions

Lignin is one of the most abundant biopolymers in nature and has great potential to be transformed into high-value chemicals. However, the limited availability of molecular structure data hinders its potential industrial applications. Herein, we present the Lignin Structural (LGS) Dataset that inclu...

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Autores principales: Eswaran, Sudha cheranma devi, Subramaniam, Senthil, Sanyal, Udishnu, Rallo, Robert, Zhang, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9588021/
https://www.ncbi.nlm.nih.gov/pubmed/36273011
http://dx.doi.org/10.1038/s41597-022-01709-4
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author Eswaran, Sudha cheranma devi
Subramaniam, Senthil
Sanyal, Udishnu
Rallo, Robert
Zhang, Xiao
author_facet Eswaran, Sudha cheranma devi
Subramaniam, Senthil
Sanyal, Udishnu
Rallo, Robert
Zhang, Xiao
author_sort Eswaran, Sudha cheranma devi
collection PubMed
description Lignin is one of the most abundant biopolymers in nature and has great potential to be transformed into high-value chemicals. However, the limited availability of molecular structure data hinders its potential industrial applications. Herein, we present the Lignin Structural (LGS) Dataset that includes the molecular structure of milled wood lignin focusing on two major monomeric units (coniferyl and syringyl), and the six most common interunit linkages (phenylpropane β-aryl ether, resinol, phenylcoumaran, biphenyl, dibenzodioxocin, and diaryl ether). The dataset constitutes a unique resource that covers a part of lignin’s chemical space characterized by polymer chains with lengths in the range of 3 to 25 monomer units. Structural data were generated using a sequence-controlled polymer generation approach that was calibrated to match experimental lignin properties. The LGS dataset includes 60 K newly generated lignin structures that match with high accuracy (~90%) the experimentally determined structural compositions available in the literature. The LGS dataset is a valuable resource to advance lignin chemistry research, including computational simulation approaches and predictive modelling.
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spelling pubmed-95880212022-10-24 Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions Eswaran, Sudha cheranma devi Subramaniam, Senthil Sanyal, Udishnu Rallo, Robert Zhang, Xiao Sci Data Data Descriptor Lignin is one of the most abundant biopolymers in nature and has great potential to be transformed into high-value chemicals. However, the limited availability of molecular structure data hinders its potential industrial applications. Herein, we present the Lignin Structural (LGS) Dataset that includes the molecular structure of milled wood lignin focusing on two major monomeric units (coniferyl and syringyl), and the six most common interunit linkages (phenylpropane β-aryl ether, resinol, phenylcoumaran, biphenyl, dibenzodioxocin, and diaryl ether). The dataset constitutes a unique resource that covers a part of lignin’s chemical space characterized by polymer chains with lengths in the range of 3 to 25 monomer units. Structural data were generated using a sequence-controlled polymer generation approach that was calibrated to match experimental lignin properties. The LGS dataset includes 60 K newly generated lignin structures that match with high accuracy (~90%) the experimentally determined structural compositions available in the literature. The LGS dataset is a valuable resource to advance lignin chemistry research, including computational simulation approaches and predictive modelling. Nature Publishing Group UK 2022-10-22 /pmc/articles/PMC9588021/ /pubmed/36273011 http://dx.doi.org/10.1038/s41597-022-01709-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Eswaran, Sudha cheranma devi
Subramaniam, Senthil
Sanyal, Udishnu
Rallo, Robert
Zhang, Xiao
Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions
title Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions
title_full Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions
title_fullStr Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions
title_full_unstemmed Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions
title_short Molecular structural dataset of lignin macromolecule elucidating experimental structural compositions
title_sort molecular structural dataset of lignin macromolecule elucidating experimental structural compositions
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9588021/
https://www.ncbi.nlm.nih.gov/pubmed/36273011
http://dx.doi.org/10.1038/s41597-022-01709-4
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