Computational analysis identifies peptide motifs in phase-separating proteins, highlighting sequence patterns and potential implications for LLPS design.
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.
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Calvário et al. (2025) studied this question.
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