Back

Prime editing enables high-throughput identification and characterization of selective MutSβ inhibitors

Jing, Y.; Yan, J.; Yang, D.; Chen, Y.; Senoussi, I.; Woodward, J.; Williams, K.; Kim, H.; He, K.; Daub, H.; Dahiya, V.; Thomsen, M.; Ling, J.; Ravisankar, P.; Pritykin, Y.; Balmus, G.; Cejka, P.; Hussmann, J. A.; Liu, L.; Vogt, T. F.; Finley, M.; Adamson, B.

2026-10-06 bioengineering
10.64898/2026.10.05.755959 bioRxiv
Show abstract

DNA mismatch repair (MMR) maintains genome stability but paradoxically drives expansion of pathogenic repeats responsible for trinucleotide repeat disorders. Attenuating repeat instability through targeted inhibition of MMR is therefore a therapeutic strategy of interest; however, progress is constrained by a lack of robust methods for defining and isolating MMR subpathways. We exploited features of prime editing to profile the effects of core MMR genes on thousands of programmed DNA mispairs in cells and resolved distinct MMR processes, including a noncanonical, loop-directed mechanism. Guided by these results, we built a set of scalable reporters that detect loss of separable MMR processes and screened ~72,000 small molecules for activity against MutS{beta}-directed MMR. This effort identified a novel series of MutS{beta} inhibitors that reduced (CAG)n expansion in a cell model. Altogether, this study establishes several methods for systematically interrogating MMR, with demonstrated capacity to identify inhibitors of therapeutic value.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
Nature Communications
○ 5641 papers in training set
Top 4%
27.0%
Similar papers in this journal
2
Cell Chemical Biology
○ 94 papers in training set
Top 0.1%
13.3%
Similar papers in this journal
3
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 7%
6.4%
Similar papers in this journal
4
Nucleic Acids Research
◐ 1281 papers in training set
Top 4%
4.4%
Similar papers in this journal
50% of probability mass above
5
Science
● 477 papers in training set
Top 2%
4.1%
Similar papers in this journal
6
Molecular Cell
○ 350 papers in training set
Top 2%
3.3%
7
Advanced Science
○ 286 papers in training set
Top 3%
2.7%
8
Nature Genetics
○ 286 papers in training set
Top 2%
2.5%
9
Journal of the American Chemical Society
● 217 papers in training set
Top 1%
2.2%
10
eLife
● 5828 papers in training set
Top 47%
1.9%
11
Cell Reports
○ 1498 papers in training set
Top 18%
1.9%
12
Science Advances
● 1243 papers in training set
Top 19%
1.8%
13
Nature
○ 645 papers in training set
Top 7%
1.8%
14
Nature Biotechnology
○ 172 papers in training set
Top 3%
1.5%
15
Angewandte Chemie International Edition
○ 93 papers in training set
Top 1%
1.5%
16
Nature Chemistry
○ 42 papers in training set
Top 0.6%
1.4%
17
Journal of Experimental Medicine
● 119 papers in training set
Top 2%
1.4%
18
Nature Biomedical Engineering
○ 47 papers in training set
Top 1%
1.4%
19
Molecular Therapy
○ 81 papers in training set
Top 1%
1.1%
20
Cell Genomics
○ 172 papers in training set
Top 3%
1.1%
21
Science Translational Medicine
● 127 papers in training set
Top 2%
1.1%
22
Nature Chemical Biology
○ 119 papers in training set
Top 2%
1.1%
23
ACS Chemical Biology
● 167 papers in training set
Top 2%
1.1%
24
EMBO Molecular Medicine
○ 95 papers in training set
Top 2%
1.1%
25
Cell
○ 431 papers in training set
Top 9%
1.0%
26
Cell Systems
○ 201 papers in training set
Top 5%
0.9%
27
Nature Methods
○ 385 papers in training set
Top 7%
0.6%
28
Neuron
○ 337 papers in training set
Top 5%
0.6%
29
ACS Central Science
● 71 papers in training set
Top 2%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.