Evidence map›Paper›PMID 39940619›Full record

ArticlePolymers2025

Nano-Polymers as Cas9 Inhibitors.

Oksana Chepurna, Avradip Chatterjee, Yuanqing Li, Hong Ding, Ramachandran Murali, Keith L Black, Tao Sun

Abstract read
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Oksana ChepurnaDepartment of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Avradip ChatterjeeDepartment of Biomedical Sciences, Research Division of Immunology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.ORCID 0000-0001-8345-4339
Yuanqing LiShanghai Institute of Material Medica, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai 200231, China.
Hong DingShanghai Institute of Material Medica, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai 200231, China.ORCID 0000-0001-7923-0527
Ramachandran MuraliDepartment of Biomedical Sciences, Research Division of Immunology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.ORCID 0000-0002-8384-2793
Keith L BlackDepartment of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Tao SunDepartment of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite wide applications of CRISPR/Cas9 technology, effective approaches for CRISPR delivery with functional control are limited. In an attempt to develop a nanoscale CRSIPR/Cas9 delivery platform, we discovered that several biocompatible polymers, including polymalic acid (PMLA), polyglutamic acid (PGA), and polyaspartic acid (PLD), when conjugated with a trileucine (LLL) moiety, can effectively inhibit Cas9 nuclease function. The Cas9 inhibition by those polymers is dose-dependent, with varying efficiency to achieve 100% inhibition. Further biophysical studies revealed that PMLA-LLL directly binds the Cas9 protein, resulting in a substantial decrease in Cas9/sgRNA binding affinity. Transmission electron microscopy and molecular docking were performed to provide a possible binding mechanism for PMLA-LLL to interact with Cas9. This work identified a new class of Cas9 inhibitor in nano-polymer form. These biodegradable polymers may serve as novel Cas9 delivery vehicles with a potential to enhance the precision of Cas9-mediated gene editing.

Indexed as

CRISPR/Cas9inhibitornano-polymerpolyaspartic acidpolyglutamic acidpolymalic acidtrileucine

Identifiers

PMID39940619
PMCPMC11820846

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Registered trials

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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.