Evidence map›Paper›PMID 32629938›Full record

ReviewMolecules (Basel, Switzerland)2020

Artificial Metalloenzymes: From Selective Chemical Transformations to Biochemical Applications.

Tomoki Himiyama, Yasunori Okamoto

Open access · goldAbstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 32% 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

6 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Classifying metal-binding sites with neural networks.Protein science : a publication of the Protein Society · 2023
    Article
  4. Review
  5. Article
  6. Review
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 2 institutions in 1 country.

Tomoki HimiyamaNational Institute of Advanced Industrial Science and Technology, Ikeda, Osaka 563-8577, Japan.ORCID 0000-0001-5252-1834
Yasunori OkamotoFrontier Research Institute for Interdisciplinary Sciences, Tohoku University, 6-3 Aramaki aza Aoba, Aoba-ku, Sendai 980-8578, Japan.ORCID 0000-0002-2442-6079
National Institute of Advanced Industrial Science and Technology · JPTohoku University · JP

Funding

Japan Science and Technology Agency JPMJAX1913Japan Society for the Promotion of Science 20K15403
6 · The paper itself

Abstract

Artificial metalloenzymes (ArMs) comprise a synthetic metal complex in a protein scaffold. ArMs display performances combining those of both homogeneous catalysts and biocatalysts. Specifically, ArMs selectively catalyze non-natural reactions and reactions inspired by nature in water under mild conditions. In the past few years, the construction of ArMs that possess a genetically incorporated unnatural amino acid and the directed evolution of ArMs have become of great interest in the field. Additionally, biochemical applications of ArMs have steadily increased, owing to the fact that compartmentalization within a protein scaffold allows the synthetic metal complex to remain functional in a sea of inactivating biomolecules. In this review, we present updates on: 1) the newly reported ArMs, according to their type of reaction, and 2) the unique biochemical applications of ArMs, including chemoenzymatic cascades and intracellular/

Indexed as

Protein EngineeringCatalysisChemistry Techniques, SyntheticCoordination ComplexesMetalloproteinsCoordination ComplexesMetalloproteinsartificial metalloenzymechemoenzymatic cascadedirected evolutionintracellular catalysisorganometallic catalysisprotein engineeringselective chemical transformation

Identifiers

PMID32629938
PMCPMC7411666
OpenAlexW3040574802

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.