Unifying coarse-grained force fields for folded and disordered proteins.

Area of Science:

• Biophysics
• Computational Biology
• Molecular Dynamics

Background:

• Biological condensates form via liquid-liquid phase separation, crucial for cellular processes like transcriptional regulation and signal sensing.
• Computational modeling offers high-resolution insights into condensate structure and stability.
• Proteins in phase separation often possess both ordered domains and disordered linkers, requiring versatile simulation methods.

Purpose of the Study:

• To critically review existing coarse-grained force fields for disordered proteins.
• To identify challenges in applying these force fields to folded proteins.
• To propose an optimization strategy for improved computational models.

Main Methods:

• Literature review of coarse-grained force fields for protein simulations.
• Analysis of force field performance for intrinsically disordered proteins (IDPs) and folded proteins.
• Discussion of force field parameterization algorithms.

Main Results:

• Existing coarse-grained force fields present challenges when applied to proteins with both ordered and disordered regions.
• Current models may lack consistent accuracy across diverse protein structures involved in phase separation.
• An optimization strategy is outlined to enhance model transferability.

Conclusions:

• Developing accurate and transferable computational models is essential for understanding biological condensate formation and function.
• Addressing the limitations of current force fields is key to advancing simulations of phase-separating proteins.
• The proposed strategy aims to create more reliable computer models for diverse protein types.