Reconstruction of atomistic details from coarse-grained structures.

Area of Science:

• Computational Chemistry and Molecular Modeling
• Biomolecular Simulation
• Materials Science

Background:

• Coarse-grained (CG) models simplify complex molecular systems for large-scale simulations.
• Reconstructing atomistic detail from CG models is crucial for in-depth analysis but remains challenging.
• Existing methods often lack efficiency or broad applicability for diverse molecular systems.

Purpose of the Study:

• To present a novel algorithm for reconstructing atomistic structures from CG representations.
• To implement this algorithm within the GROMACS molecular dynamics (MD) software package.
• To demonstrate the algorithm's utility across various molecular systems, from small molecules to biomembranes.

Main Methods:

• Developed an algorithm centered around simulated annealing MD simulations.
• Employed restraints to couple CG and atomistic structures during the reconstruction process.
• Integrated the algorithm into the GROMACS MD simulation package for practical application.

Main Results:

• Successfully reconstructed low-energy atomistic structural ensembles from CG counterparts.
• Demonstrated reconstruction for individual molecules (NCQ tripeptide, lipids, cholesterol) in vacuo.
• Validated applicability to complex condensed-phase systems, including bulk water and a transmembrane peptide in a lipid bilayer.

Conclusions:

• The presented algorithm provides an effective method for atomistic structure reconstruction from CG models.
• The GROMACS implementation facilitates the application of this technique to diverse biomolecular and condensed-phase systems.
• This approach bridges the gap between CG simplification and atomistic detail, enabling more comprehensive molecular simulations.