# Understanding Biases in Liquid–Liquid Phase Separation: Investigating Amino Acid Enrichments in Phase-Separating Proteins toward Peptide Design

**Authors:** Joana Calvário, Diogo Antunes, Rita Cipriano, Daniela Kalafatovic, Goran Mauša, Ana S. Pina

PMC · DOI: 10.1021/acs.biomac.4c00224 · Biomacromolecules · 2025-09-22

## TL;DR

This paper identifies amino acid patterns in proteins that drive liquid-liquid phase separation and uses them to design synthetic peptides with similar properties.

## Contribution

The study discovers new peptide motifs associated with phase separation and uses them to design functional synthetic peptides.

## Key findings

- 129 enriched peptide motifs (3–6 residues) were identified in phase-separating proteins.
- Designed peptides based on these motifs showed liquid-like behavior in experiments.
- Motif trios with co-occurrence patterns were used to guide peptide design.

## Abstract

Liquid–liquid phase separation (LLPS) facilitates
the formation
of membraneless organelles, enhancing biochemical processes. The stickers-and-spacers
model explains LLPS but is mainly validated in prion-like RNA-binding
proteins. To broaden our understanding, we investigated peptide motifs
associated with LLPS across diverse protein contexts using a computational
approach on the droplet-promoting regions (DPRs) of 178 phase-separating
proteins. The study identified 129 enriched peptide motifs (3–6
residues), characterized by Gly-rich sequences interspersed with aromatic,
charged, and polar residues, as well as homopeptide repeats (e.g.,
GGDR, SRGG, QQQQ). Analysis of motif presence and frequency revealed
a widespread distribution across DPRs and significant repetitive patterns.
Motif trios with a higher likelihood of co-occurrence were utilized
in a data-driven approach to design peptides with LLPS propensity.
The designed peptides exhibited liquid-like behavior with different
dynamics upon experimental validation. This work provides insights
into sequence determinants of phase separation and offers the potential
for designing synthetic condensates with tailored properties.

## Full-text entities

- **Chemicals:** Amino Acid (MESH:D000596)

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12818744/full.md

## References

93 references — full list in the complete paper: https://tomesphere.com/paper/PMC12818744/full.md

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Source: https://tomesphere.com/paper/PMC12818744