SWINGER: a clustering algorithm for concurrent coupling of atomistic and supramolecular liquids

Area of Science:

• Computational chemistry
• Biomolecular simulations
• Multiscale modeling

Background:

• Dynamic clustering algorithms are crucial for efficient molecular simulations.
• Multiscale molecular simulations require methods to handle varying levels of detail.
• Accurate solvent representation is key in biomolecular system studies.

Purpose of the Study:

• To review recent developments and applications of the SWINGER algorithm.
• To highlight SWINGER's utility in multiscale molecular simulations of biomolecular systems.
• To demonstrate the integration of SWINGER with adaptive resolution schemes.

Main Methods:

• The SWINGER algorithm dynamically clusters and redistributes solvent molecules.
• Integration with adaptive resolution schemes couples atomistic and coarse-grained representations.
• Applications utilize established models like MARTINI and dissipative particle dynamics.

Main Results:

• SWINGER enables on-the-fly redistribution of solvent molecules.
• The combined approach effectively couples different molecular representations.
• Versatile applications to biomolecular systems are showcased.

Conclusions:

• SWINGER is a versatile tool for multiscale biomolecular simulations.
• The integration with adaptive resolution schemes enhances simulation efficiency.
• Future work will expand the applicability of this multiscale approach.