GROmaρs: A GROMACS-Based Toolset to Analyze Density Maps Derived from Molecular Dynamics Simulations

Area of Science:

• Computational biology
• Biophysics
• Structural biology

Background:

• Molecular dynamics (MD) simulations generate vast amounts of data.
• Comparing simulation outputs with experimental data and different simulation sets is crucial for validation and understanding.
• Existing tools may lack efficient methods for direct comparison of time-averaged density maps.

Purpose of the Study:

• To introduce GROmaρs, a novel computational toolset for generating and comparing time-averaged density maps from MD simulations.
• To provide a method for spatial inspection of atomic localization and comparison with reference maps.
• To enable quantitative analysis of biomolecular systems, including multimolecule complexes.

Main Methods:

• Fast multi-Gaussian spreading of atomic densities onto a 3D grid for efficient map generation.
• Calculation of difference maps, local, and time-resolved global correlation for map comparison.
• Integration of spatial free-energy estimates for energetic insights into atomistic localization.
• Open-source, GROMACS-based toolset allowing flexible atom/bead selection and region masking.

Main Results:

• GROmaρs enables efficient computation and comparison of density maps from MD simulations.
• The tool facilitates quantitative comparison between perturbed and control simulations, and with experimental maps.
• Demonstrated utility in analyzing lipid/water localization in aquaporins, cholesterol binding, and channel permeation pathways.

Conclusions:

• GROmaρs offers a powerful and versatile approach for analyzing MD simulations.
• It significantly aids in comparing simulation data with experimental densities, especially for complex systems.
• The toolset is expected to have broad applicability in structural biology and biophysics research.