Evidence map›Paper›PMID 39762573›Full record

ArticleNature chemistry2025

Intellectual frameworks to understand complex biochemical systems at the origin of life.

Burckhard Seelig, Irene A Chen

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Article in Nature chemistry, 2025. 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. Review
  2. Emergent Chemical Reactivity and Complexity of RNA Condensates.Angewandte Chemie (International ed. in English) · 2025
    Article
  3. Article
  4. Review
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

2 authors.

Burckhard SeeligDepartment of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis, MN, USA. seelig@umn.edu.ORCID 0000-0001-8598-0586
Irene A ChenDepartment of Chemical and Biomolecular Engineering, University of California, Los Angeles, Los Angeles, CA, USA. ireneachen@ucla.edu.ORCID 0000-0001-6040-7927

Funding

Developing a synthetic evolution approach to create de novo enzymesR01GM108703 · NIGMS · UNIVERSITY OF MINNESOTA · PI SEELIG, BURCKHARD · 2014 to 2017
$1.1M
Human Frontier Science Program (HFSP) RGP0041National Aeronautics and Space Administration (NASA) 80NSSC18K1277National Aeronautics and Space Administration (NASA) 80NSSC21K0595National Science Foundation (NSF) EF-1935087National Science Foundation (NSF) EF-1935372National Science Foundation (NSF) EF-1935372, EF-1935087NIGMS NIH HHS R01 GM108703Simons Foundation 290356FY18Simons Foundation 340762U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) 5R01GM108703
6 · The paper itself

Abstract

Understanding the emergence of complex biochemical systems, such as protein translation, is a great challenge. Although synthetic approaches can provide insight into the potential early stages of life, they do not address the equally important question of why the complex systems of life would have evolved. In particular, the intricacies of the mechanisms governing the transfer of information from nucleic acid sequences to proteins make it difficult to imagine how coded protein synthesis could have emerged from a prebiotic soup. Here we discuss the use of intellectual frameworks in studying the emergence of life. We discuss how one such framework, namely the RNA world theory, has spurred research, and provide an overview of its limitations. We suggest that the emergence of coded protein synthesis could be broken into experimentally tractable problems by treating it as a molecular bricolage-a complex system integrating many different parts, each of which originally evolved for uses unrelated to its modern function-to promote a concrete understanding of its origin.

Indexed as

Origin of LifeRNAProtein BiosynthesisRNA

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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.