Evidence map›Paper›PMID 30913359›Full record

ReviewAngewandte Chemie (International ed. in English)2019

High-Throughput Approaches in Carbohydrate-Active Enzymology: Glycosidase and Glycosyl Transferase Inhibitors, Evolution, and Discovery.

Lemeng Chao, Seino Jongkees

Open access · hybridAbstract readReview
In one paragraph

Review in Angewandte Chemie (International ed. in English), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 22 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Lemeng ChaoDepartment of Chemical Biology and Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Universiteitsweg 99, 3581AG, Utrecht, The Netherlands.
Seino JongkeesDepartment of Chemical Biology and Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Universiteitsweg 99, 3581AG, Utrecht, The Netherlands.ORCID 0000-0002-4796-0557
Utrecht University · NL

Funding

H2020 Marie Skłodowska-Curie Actions 746631
6 · The paper itself

Abstract

Carbohydrates are attached and removed in living systems through the action of carbohydrate-active enzymes such as glycosyl transferases and glycoside hydrolases. The molecules resulting from these enzymes have many important roles in organisms, such as cellular communication, structural support, and energy metabolism. In general, each carbohydrate transformation requires a separate catalyst, and so these enzyme families are extremely diverse. To make this diversity manageable, high-throughput approaches look at many enzymes at once. Similarly, high-throughput approaches can be a powerful way of finding inhibitors that can be used to tune the reactivity of these enzymes, either in an industrial, a laboratory, or a medicinal setting. In this review, we provide an overview of how these enzymes and inhibitors can be sought using techniques such as high-throughput natural product and combinatorial library screening, phage and mRNA display of (glyco)peptides, fluorescence-activated cell sorting, and metagenomics.

Indexed as

AnimalsCarbohydrate MetabolismDirected Molecular EvolutionDrug DiscoveryEnzyme InhibitorsGlycoside HydrolasesHigh-Throughput Screening AssaysHumansMetagenomicsEnzyme InhibitorsGlycoside Hydrolasescarbohydratesdirected evolutionenzymeshigh-throughput screeningphage display

Identifiers

PMID30913359
PMCPMC6771893
OpenAlexW2922559503

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.