Evidence map›Paper›PMID 40093099›Full record

ArticlebioRxiv : the preprint server for biology2025

Prediction of small-molecule partitioning into biomolecular condensates from simulation.

Alina Emelianova, Pablo L Garcia, Daniel Tan, Jerelle A Joseph

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

5 · Who and what money

Authors and funding

4 authors.

Alina EmelianovaDepartment of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0002-3528-5478
Pablo L GarciaDepartment of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA.ORCID 0009-0009-5768-4945
Daniel TanDepartment of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA.ORCID 0009-0005-4021-2176
Jerelle A JosephDepartment of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0003-4525-180X

Funding

Inside Condensates: Bridging molecular structure and condensate material properties through simulationR35GM155259 · NIGMS · PRINCETON UNIVERSITY · PI Jerelle Aurelia Joseph · 2024 to 2026
$1.2M
NIGMS NIH HHS R35 GM155259
6 · The paper itself

Abstract

Predicting small-molecule partitioning into biomolecular condensates is key to developing drugs that selectively target aberrant condensates. However, the molecular mechanisms underlying small-molecule partitioning remain largely unknown. Here, we first exploit atomistic molecular dynamics simulations of model condensates to elucidate physicochemical rules governing small-molecule partitioning. We find that while hydrophobicity is a major determinant, solubility becomes a stronger regulator of partitioning in more polar condensates. Additionally, more polar condensates exhibit selectivity toward certain compounds, suggesting that condensate-specific therapeutics can be engineered. Building on these insights, we develop minimal models (MAPPS) for efficient prediction of small-molecule partitioning into biologically relevant condensates. We demonstrate that this approach reproduces atomistic partition coefficients in both model systems and condensates composed of the low complexity domain (LCD) of FUS. Applying MAPPS to various LCD-based condensates shows that protein sequence can exert a selective pressure, thereby influencing small-molecule partitioning. Collectively, our findings reveal that partitioning is driven by both small-molecule-protein affinity and the complex interplay between the compounds and the condensate chemical environment.

Identifiers

PMID40093099
PMCPMC11908252

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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.