Evidence map›Paper›PMID 29745651›Full record

ReviewBioconjugate chemistry2018

Biofabricating Functional Soft Matter Using Protein Engineering to Enable Enzymatic Assembly.

Yi Liu, Hsuan-Chen Wu, Narendranath Bhokisham, Jinyang Li, Kai-Lin Hong, David N Quan, Chen-Yu Tsao, William E Bentley, Gregory F Payne

Abstract readReview
In one paragraph

Review in Bioconjugate chemistry, 2018. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  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

9 authors.

Yi Liu
Hsuan-Chen WuDepartment of Biochemical Science and Technology , National Taiwan University , Taipei City , Taiwan.
Narendranath Bhokisham
Jinyang Li
Kai-Lin HongDepartment of Biochemical Science and Technology , National Taiwan University , Taipei City , Taiwan.
David N Quan
Chen-Yu Tsao
William E Bentley

Funding

Accessing molecular communication via synthetic biology and microelectronics – gut on a chip modelR21EB024102 · NIBIB · UNIV OF MARYLAND, COLLEGE PARK · PI BENTLEY, WILLIAM E. · 2017 to 2018
$412k
NIBIB NIH HHS R21 EB024102
6 · The paper itself

Abstract

Biology often provides the inspiration for functional soft matter, but biology can do more: it can provide the raw materials and mechanisms for hierarchical assembly. Biology uses polymers to perform various functions, and biologically derived polymers can serve as sustainable, self-assembling, and high-performance materials platforms for life-science applications. Biology employs enzymes for site-specific reactions that are used to both disassemble and assemble biopolymers both to and from component parts. By exploiting protein engineering methodologies, proteins can be modified to make them more susceptible to biology's native enzymatic activities. They can be engineered with fusion tags that provide (short sequences of amino acids at the C- and/or N- termini) that provide the accessible residues for the assembling enzymes to recognize and react with. This "biobased" fabrication not only allows biology's nanoscale components (i.e., proteins) to be engineered, but also provides the means to organize these components into the hierarchical structures that are prevalent in life.

Indexed as

Amino AcidsAnimalsBacteriaBacterial ProteinsBiocatalysisBiocompatible MaterialsBioengineeringHumansModels, MolecularMonophenol MonooxygenaseProtein EngineeringProteinsQuorum SensingTransglutaminasesAmino AcidsBacterial ProteinsBiocompatible MaterialsMonophenol MonooxygenaseProteinsTransglutaminases

Identifiers

PMID29745651
PMCPMC7045599

What OpenQuestion holds

Textmetadata
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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.