Evidence map›Paper›PMID 41018632›Full record

ReviewACS omega2025

Molecular Paleontology Meets Drug Discovery: The Case for De-extinct Antimicrobials.

Rumiana Tenchov, Qiongqiong Angela Zhou

Abstract readReview
In one paragraph

Review in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Rumiana TenchovCAS, a Division of the American Chemical Society, Columbus, Ohio 43210, United States.ORCID https://orcid.org/0000-0003-4698-6832
Qiongqiong Angela ZhouCAS, a Division of the American Chemical Society, Columbus, Ohio 43210, United States.ORCID https://orcid.org/0000-0001-6711-369X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rise of antibiotic resistance has necessitated the exploration of unconventional sources of novel antimicrobial agents. One emerging novel frontier is "de-extinct" moleculesbioactive peptides, antibiotics, and other bioactive agents reconstructed from ancient or extinct organismsan innovative convergence of paleogenomics, paleoproteomics, and synthetic biology. Recent advances in high-throughput DNA sequencing, mass spectrometry, and computational biology have enabled scientists to recover and analyze genetic and protein sequences from long-extinct species, offering unprecedented insights into evolutionary biology and potential applications in medicine, biotechnology, and conservation, including the successful regeneration of antimicrobial molecules from several extinct organisms. While paleogenomics provides the blueprint for reconstructing extinct genomes, paleoproteomics offers complementary insights into gene expression, protein function, and post-translational modifications that are often lost in DNA-based studies. These approaches can yield proteins and metabolites that have been lost to evolution, offering a new reservoir of bioactive compounds that could be used for new strategies in medicine, biotechnology, and synthetic biology. In this report we explore data from the CAS Content Collection to outline the current landscape and research progress in the emerging area of molecular de-extinction, to identify key developing concepts and challenges, and to identify successfully revived de-extinct antimicrobials. We outline the technical approaches to their revival in an effort to understand how this highly innovative strategy helps combat modern multidrug-resistant pathogens as well as the challenges and ethical considerations in deploying ancient molecules.

Identifiers

PMID41018632
PMCPMC12461407

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.