Modeling Concentration-dependent Phase Separation Processes Involving Peptides and RNA via Residue-Based...

Area of Science:

• Biophysics
• Computational Biology
• Molecular Biology

Background:

• Biomolecular condensation, particularly liquid-liquid phase separation (LLPS), is vital for cellular functions.
• Understanding the molecular composition driving LLPS is crucial but challenging.
• Developing efficient and accurate computational models for LLPS has been a significant hurdle.

Purpose of the Study:

• To introduce COCOMO, a novel coarse-grained model for simulating biomolecular condensation.
• To balance polymer behavior of peptides/RNA with phase separation propensity.
• To provide a computationally efficient yet physically realistic modeling approach.

Main Methods:

• Developed COCOMO, a residue-based coarse-grained model.
• Incorporated bonded, short-range, and long-range interactions.
• Included a Debye-Hückel solvation term to account for solvent effects.
• Validated the model against experimental data for phase-separating systems.

Main Results:

• COCOMO accurately predicts experimental data for model phase-separating systems.
• The model effectively balances polymer characteristics with phase separation behavior.
• Demonstrated computational efficiency, enabling simulations at relevant biological scales.

Conclusions:

• COCOMO offers a powerful tool for investigating biomolecular condensation and LLPS.
• The model's efficiency and accuracy facilitate understanding of phase separation drivers.
• COCOMO can be used to explore biological processes occurring at relevant spatial and temporal scales.