Evidence map›Paper›PMID 38300270›Full record

ArticleAnalytical chemistry2024

Harnessing Peptide Nucleic Acids and the Eukaryotic Resolvase MOC1 for Programmable, Precise Generation of Double-Strand DNA Breaks.

Gundra Sivakrishna Rao, Ahmed H Saleh, Firdaws Melliti, Syed Muntjeeb, Magdy Mahfouz

Open access · hybridAbstract read
In one paragraph

Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 1 institution in 1 country.

Gundra Sivakrishna RaoLaboratory for Genome Engineering and Synthetic Biology, Division of Biological Sciences, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
Ahmed H SalehLaboratory for Genome Engineering and Synthetic Biology, Division of Biological Sciences, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
Firdaws MellitiLaboratory for Genome Engineering and Synthetic Biology, Division of Biological Sciences, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
Syed MuntjeebLaboratory for Genome Engineering and Synthetic Biology, Division of Biological Sciences, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.
Magdy MahfouzLaboratory for Genome Engineering and Synthetic Biology, Division of Biological Sciences, 4700 King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia.ORCID 0000-0002-0616-6365
King Abdullah University of Science and Technology · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Programmable site-specific nucleases (SSNs) hold extraordinary promise to unlock myriad gene editing applications in medicine and agriculture. However, developing small and specific SSNs is needed to overcome the delivery and specificity translational challenges of current genome engineering technologies. Structure-guided nucleases have been harnessed to generate double-strand DNA breaks but with limited success and translational potential. Here, we harnessed the power of peptide nucleic acids (PNAs) for site-specific DNA invasion and the generation of localized DNA structures that are recognized and cleaved by the eukaryotic resolvase AtMOC1 from

Indexed as

Peptide Nucleic AcidsDNADNA Breaks, Double-StrandedGene EditingTemperatureDNAPeptide Nucleic Acids

Identifiers

PMID38300270
PMCPMC10867802
OpenAlexW4391431473

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.