Automated Coarse-Grained Mapping Algorithm for the Martini Force Field and Benchmarks for Membrane-Water Partitioning

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Biophysics

Background:

• Accurate molecular modeling requires robust force fields for simulations.
• The Martini force field is widely used for coarse-grained simulations of biological systems.
• Efficient parameterization of diverse organic molecules is crucial for expanding simulation scope.

Purpose of the Study:

• To present an automated system for mapping and parameterizing organic molecules for the Martini force field.
• To enable high-throughput simulations of a broader range of chemical structures.
• To improve the accuracy of partition coefficient calculations for organic molecules.

Main Methods:

• Utilized a graph-based analysis of molecular bonding networks for mapping.
• Developed specialized parameterization techniques for aromatic rings and rigid molecules.
• Implemented an adaptive method for extracting partition coefficients from free-energy profiles.
• Tested the system on 87 diverse neutral organic molecules.

Main Results:

• The automated system successfully mapped and parameterized 87 organic molecules.
• The resulting models accurately captured octanol-water partition coefficients.
• The method effectively determined membrane-water partition coefficients, considering interfacial effects.
• Probed the influence of cholesterol on membrane-water partitioning using the generated models.

Conclusions:

• The presented automated system offers a scalable and general approach for organic molecule parameterization.
• This advancement significantly enhances the capability for high-throughput molecular simulations.
• The methodology improves the prediction of molecular partitioning behavior in complex systems.