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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Biophysics

Background:

  • Eukaryotic proteins and RNAs feature low-complexity domains (LCDs) crucial for phase separation into biomolecular condensates.
  • Mutations in LCDs can disrupt condensate dynamics, leading to pathological transitions to solid-like states.
  • Understanding the sequence grammar of LCDs is vital for elucidating their biological roles and evolutionary pressures.

Purpose of the Study:

  • To develop an energy landscape framework for analyzing LCDs without relying on explicit sequence alphabets.
  • To investigate how sequence features, such as periodicity and disorder, govern condensate material and dynamical properties.
  • To provide a unifying perspective on sequence-encoded material properties in biomolecular condensates.

Main Methods:

  • Developed a continuous 'stickiness' energy scale framework for LCDs.
  • Characterized sequences using Wasserstein distance relative to shuffled or random counterparts.
  • Mapped material and dynamical properties based on energy landscape features and LCD complexity.

Main Results:

  • Highly periodic LCD patterns correlate with elasticity-dominated behavior; random sequences show viscosity-dominated properties.
  • A minimum sticker periodicity is essential for maintaining condensate fluidity and preventing glassy or solid states.
  • The framework explains experimental findings on prion domains and predicts condensate viscoelasticity changes.

Conclusions:

  • The energy landscape framework offers a unifying perspective on sequence-encoded material properties of LCDs.
  • Conserved energy landscape features can explain conserved condensate properties despite sequence variability.
  • This approach is crucial for understanding condensate dynamics, biological functions, and disease-related transitions.