Back

Competing effects modulate the rate of poly(A) RNA deadenylation in a biomolecular condensate

Irwin, R. M.; Harkness, R. W.; Liu, Z. H.; Sun, K.; Huang, T. H.; Head-Gordon, T.; Kay, L.; Forman-Kay, J. D.

2026-07-03 biochemistry
10.64898/2026.07.02.736149 bioRxiv
Show abstract

The unique solvent milieu found in biomolecular condensates can control cellular enzymatic reactions and shift reaction kinetics by modulating reactant concentrations, structural dynamics, and enzyme activities. Here we explore the interplay of multiple regulatory factors within a condensate to control poly(A) RNA deadenylation, the first and rate-limiting step in mRNA turnover. The deadenylase CNOT7, a subunit of the CCR4-NOT deadenylation complex, localizes to cytoplasmic RNA granules and shows increased degradation activity in vitro in condensates formed by the C-terminal low complexity disordered region of CAPRIN1, a component of RNA granules. We use a combination of enzymatic assays, kinetic modeling, microscopy, Nuclear Magnetic Resonance (NMR) spectroscopy, and molecular dynamics simulations to deconvolute and define the components that underlie this enhancement. We found that enzyme and RNA are concentrated in condensates relative to buffer, which increases CNOT7 activity, while the equilibrium between CNOT7's active and inactive states remains unchanged. The concentration-dependent increase in enzymatic rates is counterbalanced by a substantial decrease in the enzyme's catalytic efficiency, likely due to slower diffusion of CNOT7 and RNA within the condensates, which lessens the probability of enzyme-substrate complex formation. Molecular dynamics simulations reveal CNOT7-CAPRIN1 interactions that rely on conserved CAPRIN1 sequence features, hinting at an evolutionarily conserved role for CAPRIN1 condensation. With this quantitative kinetic analysis, we describe the multifaceted mechanism behind regulation of CNOT7 deadenylation by a condensate environment.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nucleic Acids Research
1281 papers in training set
Top 0.9%
16.2%
2
Nature Communications
5641 papers in training set
Top 16%
11.3%
3
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 4%
9.2%
4
RNA
189 papers in training set
Top 0.3%
6.4%
5
Biophysical Journal
631 papers in training set
Top 1%
6.0%
6
Molecular Cell
350 papers in training set
Top 1%
5.2%
50% of probability mass above
7
Journal of Biological Chemistry
690 papers in training set
Top 2%
4.9%
8
Biochemistry
148 papers in training set
Top 0.5%
4.6%
9
Journal of Molecular Biology
232 papers in training set
Top 0.6%
4.1%
10
The EMBO Journal
309 papers in training set
Top 1%
3.9%
11
Cell Reports
1498 papers in training set
Top 11%
3.9%
12
eLife
5828 papers in training set
Top 37%
3.1%
13
Science Advances
1243 papers in training set
Top 14%
2.5%
14
Scientific Reports
3612 papers in training set
Top 60%
1.4%
15
Protein Science
246 papers in training set
Top 2%
1.4%
16
Journal of the American Chemical Society
217 papers in training set
Top 2%
1.1%
17
PLOS Computational Biology
1863 papers in training set
Top 21%
0.8%
18
The Journal of Physical Chemistry B
167 papers in training set
Top 2%
0.8%
19
ACS Chemical Biology
167 papers in training set
Top 3%
0.8%
20
JACS Au
43 papers in training set
Top 0.9%
0.8%
21
PLOS ONE
5266 papers in training set
Top 63%
0.8%
22
Journal of The Royal Society Interface
235 papers in training set
Top 5%
0.6%
23
EMBO Reports
263 papers in training set
Top 9%
0.6%