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This study presents a computational framework to simulate protein liquid-liquid phase separation (LLPS) at the residue level. The model accurately predicts phase diagrams and the impact of mutations on LLPS for key proteins.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Molecular Biology

Background:

  • Membraneless organelles form via liquid-liquid phase separation (LLPS).
  • Many proteins driving LLPS are intrinsically disordered, complicating experimental study.
  • Understanding LLPS mechanisms requires robust theoretical and simulation approaches.

Purpose of the Study:

  • To develop a residue-level computational framework for simulating protein LLPS.
  • To determine phase diagrams and coexistence densities for proteins undergoing LLPS.
  • To investigate sequence determinants and effects of mutations on LLPS.

Main Methods:

  • Developed a computational framework incorporating short-range contacts and electrostatic energy.
  • Optimized interaction parameters against experimental radius of gyration data for intrinsically disordered proteins (IDPs).
  • Applied the model to FUS low-complexity domain and LAF-1, using a novel simulation method for phase diagrams.

Main Results:

  • The model successfully captured LLPS behavior for FUS and LAF-1.
  • Simulations predicted qualitative changes in phase diagrams due to phosphomimetic mutations in FUS and domain presence in LAF-1.
  • Results showed consistency with Flory-Huggins theory regarding chain length and multivalency effects.

Conclusions:

  • The presented computational framework enables detailed simulation of protein LLPS.
  • This methodology is adaptable for various potentials, sampling methods, and biological systems.
  • The study provides insights into the molecular mechanisms and sequence determinants of LLPS.