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Published on: April 17, 2018
Coiled-coils as emerging drivers of liquid-liquid phase separation
Ryosuke Anzai1, Akira Mabuchi1, Shoji Hata1,2
1Department of Physiological Chemistry, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-0033, Japan.
Coiled-coils, ubiquitous protein motifs, drive biological liquid-liquid phase separation (LLPS) through tunable interactions. They offer a functional duality distinct from intrinsically disordered regions, modulating condensate properties.
Area of Science:
- Biochemistry
- Cell Biology
- Structural Biology
Background:
- Liquid-liquid phase separation (LLPS) is crucial for organizing cellular biochemistry within membraneless compartments.
- Biomolecular interactions, particularly weak multivalent ones, mediate LLPS.
- Intrinsically disordered regions (IDRs) are known drivers of LLPS, but other motifs are also involved.
Purpose of the Study:
- To systematically review the diverse roles of coiled-coils in LLPS.
- To contrast the contributions of coiled-coils with those of IDRs in LLPS.
- To highlight the unique properties of coiled-coils that influence condensate formation and material characteristics.
Main Methods:
- Literature review of studies on coiled-coils and LLPS.
- Comparative analysis of coiled-coil versus IDR functions in phase separation.
- Exploration of the biophysical properties, including interaction affinities, of coiled-coils.
Main Results:
- Coiled-coils are versatile contributors to LLPS, distinct from IDRs.
- Coiled-coils exhibit a broad dynamic range of interaction affinities (pM to mM).
- This tunability allows coiled-coils to function as both high-affinity oligomerization platforms and weak interaction modules.
Conclusions:
- Coiled-coils possess a unique functional duality enabling diverse roles in LLPS.
- Their tunable interactions are key to modulating phase separation propensity and condensate material properties.
- Coiled-coils represent an important class of biomolecular motifs driving cellular organization via LLPS.
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