Evidence map›Paper›PMID 24513641›Full record

ReviewCurrent opinion in chemical biology2014

Metalloenzyme design and engineering through strategic modifications of native protein scaffolds.

Igor D Petrik, Jing Liu, Yi Lu

Abstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Synzymes: The Future of Modern Enzyme Engineering.Applied biochemistry and biotechnology · 2025
    Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Machine Learning Approaches for Metalloproteins.Molecules (Basel, Switzerland) · 2022
    Review
  9. From Data Mining ofMicroorganisms · 2021
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Artificial Heme Enzymes for the Construction of Gold-Based Biomaterials.International journal of molecular sciences · 2018
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

3 authors.

Igor D PetrikDepartment of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
Jing LiuDepartment of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States.
Yi LuDepartment of Chemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States. Electronic address: yi-lu@illinois.edu.

Funding

DESIGNING HETERONUCLEAR METALLOENZYMESR01GM062211 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI LU, YI · 2001 to 2021
$5.1M
NIGMS NIH HHS GM062211NIGMS NIH HHS R01 GM062211
6 · The paper itself

Abstract

Metalloenzymes are among the major targets of protein design and engineering efforts aimed at attaining novel and efficient catalysis for biochemical transformation and biomedical applications, due to the diversity of functions imparted by the metallo-cofactors along with the versatility of the protein environment. Naturally evolved protein scaffolds can often serve as robust foundations for sustaining artificial active sites constructed by rational design, directed evolution, or a combination of the two strategies. Accumulated knowledge of structure-function relationship and advancement of tools such as computational algorithms and unnatural amino acids incorporation all contribute to the design of better metalloenzymes with catalytic properties approaching the needs of practical applications.

Indexed as

Amino AcidsEnzyme StabilityHumansMetalloproteinsProtein EngineeringSubstrate SpecificityAmino AcidsMetalloproteins

Identifiers

PMID24513641
PMCPMC4008701

What OpenQuestion holds

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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.