ArticleCommunications chemistry2024
Exploring the sequence-function space of microbial fucosidases.
Article in Communications chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- The butyrate-producing Gram-positive human gut bacterium, Hoskinsella mucinilytica, selectively targets host mucin N-acetylhexosamines.The Journal of biological chemistry · 2026Article
- The Discovery of Endo-Fucanases in the GH141 Family: A Novel Functional Activity Within the Family.International journal of molecular sciences · 2025Article
- Recombinant Production and Characterization of a Novel α-L-Fucosidase fromInternational journal of molecular sciences · 2025Article
- Fluorogenic, Subsingle-Turnover Monitoring of Enzymatic Reactions Involving NAD(P)H Provides a Generalized Platform for Directed Ultrahigh-Throughput Evolution of Biocatalysts in Microdroplets.Journal of the American Chemical Society · 2025Article
- Structural elucidation and characterization of GH29A α-l-fucosidases and the effect of pH on their transglycosylation.The FEBS journal · 2025Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Microbial α-L-fucosidases catalyse the hydrolysis of terminal α-L-fucosidic linkages and can perform transglycosylation reactions. Based on sequence identity, α-L-fucosidases are classified in glycoside hydrolases (GHs) families of the carbohydrate-active enzyme database. Here we explored the sequence-function space of GH29 fucosidases. Based on sequence similarity network (SSN) analyses, 15 GH29 α-L-fucosidases were selected for functional characterisation. HPAEC-PAD and LC-FD-MS/MS analyses revealed substrate and linkage specificities for α1,2, α1,3, α1,4 and α1,6 linked fucosylated oligosaccharides and glycoconjugates, consistent with their SSN clustering. The structural basis for the substrate specificity of GH29 fucosidase from Bifidobacterium asteroides towards α1,6 linkages and FA2G2 N-glycan was determined by X-ray crystallography and STD NMR. The capacity of GH29 fucosidases to carry out transfucosylation reactions with GlcNAc and 3FN as acceptors was evaluated by TLC combined with ESI-MS and NMR. These experimental data supported the use of SSN to further explore the GH29 sequence-function space through machine-learning models. Our lightweight protein language models could accurately allocate test sequences in their respective SSN clusters and assign 34,258 non-redundant GH29 sequences into SSN clusters. It is expected that the combination of these computational approaches will be used in the future for the identification of novel GHs with desired specificities.
Identifiers
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Registered trials
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