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Efficient implementation of the three-dimensional reference interaction site model method in the fragment molecular

Norio Yoshida¹

¹Department of Chemistry, Graduate School of Sciences, Kyushu University, 6-10-1, Hakozaki, Higashi-ku, Fukuoka 812-8581, Japan.

The Journal of Chemical Physics

|June 9, 2014

Summary

We developed the Fragment Molecular Orbital/3D-Reference Interaction Site Model (FMO/3D-RISM) method to efficiently calculate electronic structures and solvent distribution for macromolecules. This approach reduces computational costs for electrostatic potential calculations, enabling faster simulations.

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Area of Science:

Computational Chemistry
Quantum Chemistry
Molecular Modeling

Background:

The 3D-Reference Interaction Site Model (3D-RISM) method calculates solvent distribution around solutes.
The Fragment Molecular Orbital (FMO) method treats large molecules by dividing them into fragments.
Calculating electrostatic potential in 3D-RISM is computationally expensive.

Purpose of the Study:

To implement the 3D-RISM method within the FMO framework, creating the FMO/3D-RISM method.
To reduce the computational cost of electrostatic potential calculations in FMO/3D-RISM.
To enable efficient treatment of electronic structure and solvent distribution for macromolecules.

Main Methods:

Developed the FMO/3D-RISM method, combining FMO and 3D-RISM formalisms.
Proposed a strategy to decrease computational costs by evaluating electrostatic potential based on solute-solvent distance.
Utilized direct integration of molecular orbitals near the solute and multipole expansion with a fast multipole method analog for distant solvent interactions.

Main Results:

Successfully implemented the FMO/3D-RISM method.
Demonstrated significant reduction in computational cost for electrostatic potential calculations.
Validated the method's accuracy on a water trimer and three biomolecular systems.

Conclusions:

The FMO/3D-RISM method provides an efficient approach for studying macromolecule electronic structure and solvation.
The developed computational cost reduction strategy allows for reasonable calculation times while maintaining accuracy.
This method facilitates more accessible computational studies of complex biological systems.