A coarse-grained model for disordered proteins under crowded conditions

Area of Science:

• Biophysics
• Computational Biology
• Protein Dynamics

Background:

• Macromolecular crowding profoundly influences protein dynamics and function, especially for intrinsically disordered proteins.
• Understanding crowding effects on protein chain compaction and phase separation (PS) is crucial for biological function.
• Previous studies utilized synthetic crowders like polyethylene glycol (PEG) and ficoll, alongside theoretical models and simulations.

Purpose of the Study:

• To develop a residue-based coarse-grained model for PEG compatible with the CALVADOS protein model.
• To optimize PEG model parameters using experimental data on PEG's single-chain behavior and its effect on protein compaction.
• To quantify phase separation propensities of proteins with weak PS tendencies using the developed PEG model.

Main Methods:

• Developed a residue-based coarse-grained model for polyethylene glycol (PEG).
• Optimized PEG model parameters by comparing simulation data with experimental results.
• Applied the model to study PEG-induced compaction and phase separation of disordered proteins.

Main Results:

• The developed PEG model accurately reproduces experimental data on PEG compaction of disordered proteins.
• PEG titrations effectively quantify phase separation propensities, even for proteins with weak tendencies.
• Crowding response to PEG varied between charge patterning variants of α-synuclein, but not for aromatic residue variants in A1-LCD.

Conclusions:

• The new PEG model aids in interpreting crowding experiments with disordered proteins.
• This model serves as a foundation for studying proteins with weak phase separation propensities.
• The findings highlight the differential impact of crowding on protein variants based on their sequence features.