Multiscale simulations of protein and membrane systems

Area of Science:

• Computational physics and chemistry
• Biophysics
• Materials science

Background:

• Biological soft matter systems are complex and require advanced simulation techniques.
• Classical multiscale simulations bridge different scales, enabling the study of biologically relevant systems.

Purpose of the Study:

• To review progress in multiscale simulations for biological soft matter.
• To highlight factors driving advancements in simulating complex biological systems.

Main Methods:

• Multiscale simulations integrating various resolution models.
• Hierarchical subsystem integration.
• Improved computational models and algorithms.

Main Results:

• Access to biologically relevant system sizes and timescales.
• Investigation of complex systems like multidomain proteins, phase separation, biomembranes, and viral complexes.
• Integration of machine learning for data analysis and model improvement.

Conclusions:

• Multiscale simulations are crucial for understanding biological soft matter.
• Progress is driven by improved models, machine learning, and scale-bridging techniques.
• These methods are essential for tackling increasingly complex biological challenges.