A data-driven sequencer that unveils latent "codons" in synthetic copolymers.
Journal
Chemical science
ISSN: 2041-6520
Titre abrégé: Chem Sci
Pays: England
ID NLM: 101545951
Informations de publication
Date de publication:
31 May 2023
31 May 2023
Historique:
received:
20
12
2022
accepted:
19
03
2023
medline:
2
6
2023
pubmed:
2
6
2023
entrez:
2
6
2023
Statut:
epublish
Résumé
The recent emergence of sequence engineering in synthetic copolymers has been innovating polymer materials, where short sequences, hereinafter called "codons" using an analogy from nucleotide triads, play key roles in expressing functions. However, the codon compositions cannot be experimentally determined owing to the lack of efficient sequencing methods, hindering the integration of experiments and theories. Herein, we propose a polymer sequencer based on mass spectrometry of pyrolyzed oligomeric fragments. Despite the random fragmentation along copolymer main-chains, the characteristic fragment patterns of the codons are identified and quantified
Identifiants
pubmed: 37265724
doi: 10.1039/d2sc06974a
pii: d2sc06974a
pmc: PMC10231333
doi:
Types de publication
Journal Article
Langues
eng
Pagination
5619-5626Informations de copyright
This journal is © The Royal Society of Chemistry.
Déclaration de conflit d'intérêts
Y. H. and M. N. are the owners of patent applications on RQMS and RQMS sequencing.
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