Evidence map›Paper›PMID 29722450›Full record

ArticleProtein science : a publication of the Protein Society2018

Crius: A novel fragment-based algorithm of de novo substrate prediction for enzymes.

Zhiqiang Yao, Shuiqin Jiang, Lujia Zhang, Bei Gao, Xiao He, John Z H Zhang, Dongzhi Wei

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Protein science : a publication of the Protein Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 96% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 2 institutions in 1 country.

Zhiqiang YaoState Key Laboratory of Bioreactor Engineering, East China university of Science and Technology, Meilong Road 130th, Shanghai, People's Republic of China.
Shuiqin JiangState Key Laboratory of Bioreactor Engineering, East China university of Science and Technology, Meilong Road 130th, Shanghai, People's Republic of China.
Lujia ZhangState Key Laboratory of Bioreactor Engineering, East China university of Science and Technology, Meilong Road 130th, Shanghai, People's Republic of China.
Bei GaoState Key Laboratory of Bioreactor Engineering, East China university of Science and Technology, Meilong Road 130th, Shanghai, People's Republic of China.
Xiao HeShanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Department of Chemistry, School of Molecular Engineering, East China Normal University, Shanghai, 200062, China.
John Z H ZhangShanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Department of Chemistry, School of Molecular Engineering, East China Normal University, Shanghai, 200062, China.
Dongzhi WeiState Key Laboratory of Bioreactor Engineering, East China university of Science and Technology, Meilong Road 130th, Shanghai, People's Republic of China.
East China University of Science and Technology · CNNew York University Shanghai · CN

Funding

Innovation Program of Shanghai Municipal Education Commission 201701070005E00020National Key R&D Program of China 2016YFA0501701National Key R&D Program of China 31571786National Key R&D Program of China 31772007Natural Science Foundation of Shanghai 16ZR1449500
6 · The paper itself

Abstract

The study of enzyme substrate specificity is vital for developing potential applications of enzymes. However, the routine experimental procedures require lot of resources in the discovery of novel substrates. This article reports an in silico structure-based algorithm called Crius, which predicts substrates for enzyme. The results of this fragment-based algorithm show good agreements between the simulated and experimental substrate specificities, using a lipase from Candida antarctica (CALB), a nitrilase from Cyanobacterium syechocystis sp. PCC6803 (Nit6803), and an aldo-keto reductase from Gluconobacter oxydans (Gox0644). This opens new prospects of developing computer algorithms that can effectively predict substrates for an enzyme.

Indexed as

AlgorithmsSoftwareComputational BiologyComputer SimulationEnzymesModels, MolecularSubstrate SpecificityEnzymesenzyme selectivityfragment-based algorithmsubstrate predictionsubstrate specificity

Identifiers

PMID29722450
PMCPMC6153407
OpenAlexW2802833050

What OpenQuestion holds

Textmetadata
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.