Evidence map›Paper›PMID 32248317›Full record

ReviewTopics in current chemistry (Cham)2020

DNA-Scaffolded Proximity Assembly and Confinement of Multienzyme Reactions.

Jinglin Fu, Zhicheng Wang, Xiao Hua Liang, Sung Won Oh, Ezry St Iago-McRae, Ting Zhang

Abstract readReview
In one paragraph

Review in Topics in current chemistry (Cham), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

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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

6 authors.

Jinglin FuDepartment of Chemistry, Rutgers University-Camden, Camden, NJ, 08102, USA. jinglin.fu@rutgers.edu.ORCID http://orcid.org/0000-0002-0814-0089
Zhicheng WangDepartment of Chemistry, Rutgers University-Camden, Camden, NJ, 08102, USA.
Xiao Hua LiangDepartment of Chemistry, Rutgers University-Camden, Camden, NJ, 08102, USA.
Sung Won OhCenter for Computational and Integrative Biology, Rutgers University-Camden, Camden, NJ, 08102, USA.
Ezry St Iago-McRaeCenter for Computational and Integrative Biology, Rutgers University-Camden, Camden, NJ, 08102, USA.
Ting ZhangDepartment of Chemistry, Rutgers University-Camden, Camden, NJ, 08102, USA.

Funding

Army Research Office W911NF1910240U.S. Department of Defense W911NF-16-1-0220
6 · The paper itself

Abstract

Cellular functions rely on a series of organized and regulated multienzyme cascade reactions. The catalytic efficiencies of these cascades depend on the precise spatial organization of the constituent enzymes, which is optimized to facilitate substrate transport and regulate activities. Mimicry of this organization in a non-living, artificial system would be very useful in a broad range of applications-with impacts on both the scientific community and society at large. Self-assembled DNA nanostructures are promising applications to organize biomolecular components into prescribed, multidimensional patterns. In this review, we focus on recent progress in the field of DNA-scaffolded assembly and confinement of multienzyme reactions. DNA self-assembly is exploited to build spatially organized multienzyme cascades with control over their relative distance, substrate diffusion paths, compartmentalization and activity actuation. The combination of addressable DNA assembly and multienzyme cascades can deliver breakthroughs toward the engineering of novel synthetic and biomimetic reactors.

Indexed as

DNAEnzymesProtein EngineeringDNAEnzymesBiomimetic systemsDNA nanotechnologyDNA scaffolded assemblyEnzyme encapsulationEnzyme immobilizationEnzyme regulationMultienzyme cascadeSynthetic reactors

Identifiers

PMID32248317
PMCPMC7127875

What OpenQuestion holds

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Registered trials

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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.