g_elpot: A Tool for Quantifying Biomolecular Electrostatics from Molecular Dynamics Trajectories

Area of Science:

• Biophysics
• Computational Biology
• Molecular Dynamics

Background:

• Electrostatic forces are crucial for biomolecular interactions and processes.
• Molecular dynamics (MD) simulations capture biomolecular configurations but lack quantitative electrostatic potential calculations.
• Existing methods struggle to connect MD-derived electrostatics to energetics.

Purpose of the Study:

• To introduce g_elpot, a novel tool for calculating electrostatic potentials from MD simulations.
• To enable quantitative analysis of biomolecular electrostatics and its role in energetics.
• To provide insights into diverse biomolecular systems using MD data.

Main Methods:

• Developed g_elpot, a GROMACS-based tool.
• Utilized the smooth particle mesh Ewald method for electrostatic potential calculation.
• Calculated potentials within explicitly simulated water molecules in MD trajectories.

Main Results:

• g_elpot successfully quantifies electrostatic potentials from MD trajectories.
• The tool can extract global electrostatic potential distributions and time courses.
• Applied g_elpot to P2X3 receptor, TMEM16 scramblases, GltPh transporter, and DNA-cationic polymer complexes.

Conclusions:

• g_elpot provides a quantitative link between MD simulations and biomolecular electrostatics.
• The tool enhances understanding of electrostatic contributions to biomolecular processes.
• g_elpot is suitable for diverse biomolecular systems, aiding biophysical insights.