Evidence map›Paper›PMID 33517151›Full record

ReviewCurrent opinion in structural biology2021

De novo proteins from random sequences through in vitro evolution.

Cher Ling Tong, Kun-Hwa Lee, Burckhard Seelig

Abstract readReview
In one paragraph

Review in Current opinion in structural biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Descent from a common ancestor restricts exploration of protein sequence space.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Evolution and synthetic biology.Current opinion in microbiology · 2023
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. 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.

Cher Ling TongDepartment of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN, USA; BioTechnology Institute, University of Minnesota, St. Paul, MN, USA.
Kun-Hwa LeeDepartment of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN, USA; BioTechnology Institute, University of Minnesota, St. Paul, MN, USA.
Burckhard SeeligDepartment of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN, USA; BioTechnology Institute, University of Minnesota, St. Paul, MN, USA. Electronic address: seelig@umn.edu.

Funding

Developing a synthetic evolution approach to create de novo enzymesR01GM108703 · NIGMS · UNIVERSITY OF MINNESOTA · PI SEELIG, BURCKHARD · 2014 to 2017
$1.1M
NIGMS NIH HHS R01 GM108703Shared Services Center NASA 80NSSC18K1277
6 · The paper itself

Abstract

Natural proteins are the result of billions of years of evolution. The earliest predecessors of today's proteins are believed to have emerged from random polypeptides. While we have no means to determine how this process exactly happened, there is great interest in understanding how it reasonably could have happened. We are reviewing how researchers have utilized in vitro selection and molecular evolution methods to investigate plausible scenarios for the emergence of early functional proteins. The studies range from analyzing general properties and structural features of unevolved random polypeptides to isolating de novo proteins with specific functions from synthetic randomized sequence libraries or generating novel proteins by combining evolution with rational design. While the results are exciting, more work is needed to fully unravel the mechanisms that seeded protein-dominated biology.

Indexed as

PeptidesProteinsEvolution, MolecularPeptidesProteins

Identifiers

PMID33517151
PMCPMC8222087

What OpenQuestion holds

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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.