Evidence map›Paper›PMID 36793302›Full record

ArticleRSC advances2023

Design of highly active substrates using molecular docking for microbial transglutaminase detection.

Longhao Zou, Xu Geng, Zhengqiang Li, Tao Li

Open access · goldAbstract read
In one paragraph

Article in RSC advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
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

4 authors at 1 institution in 1 country.

Longhao ZouKey Laboratory for Molecular Enzymology & Engineering, The Ministry of Education, School of Life Sciences, Jilin University Changchun China taoli@jlu.edu.cn.
Xu GengKey Laboratory for Molecular Enzymology & Engineering, The Ministry of Education, School of Life Sciences, Jilin University Changchun China taoli@jlu.edu.cn.
Zhengqiang LiKey Laboratory for Molecular Enzymology & Engineering, The Ministry of Education, School of Life Sciences, Jilin University Changchun China taoli@jlu.edu.cn.ORCID https://orcid.org/0000-0003-4025-2117
Tao LiKey Laboratory for Molecular Enzymology & Engineering, The Ministry of Education, School of Life Sciences, Jilin University Changchun China taoli@jlu.edu.cn.ORCID https://orcid.org/0000-0002-4184-2373
Jilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transglutaminase (TGase) family catalyzes a transamidation reaction between glutamine (Gln) and lysine (Lys) residues on protein substrates. Highly active substrates are important for cross-linking and modifying proteins of TGase. In the present work, high-activity substrates have been designed based on the principles of enzyme-substrate interaction, using microbial transglutaminase (mTGase) as a research model of the TGase family. Substrates with high activity were screened using a combination of molecular docking and traditional experiments. Twenty-four sets of peptide substrates all produced good catalytic activity with mTGase. FFKKAYAV as the acyl acceptor and VLQRAY as the acyl donor group had the best reaction efficiency with highly sensitive detection of 26 nM mTGase. In addition, the substrate grouping, KAYAV and AFQSAY, detected 130 nM mTGase under physiological conditions (37 °C, pH 7.4), producing 20-fold higher activity than the natural substrate, collagen. The experimental results confirmed the potential for design of high-activity substrates by a combination of molecular docking and traditional experiments under physiological conditions.

Identifiers

PMID36793302
PMCPMC9923216
OpenAlexW4320500598

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.