GridFF: Efficient Simulation of Organic Molecules on Rigid Substrates

We present GridFF, an efficient method for simulating molecules on rigid substrates, derived from techniques used in protein-ligand docking in biochemistry. By projecting molecule-substrate interactions onto precomputed spatial grids with tricubic B-spline interpolation, GridFF reduces the computational cost by orders of magnitude compared to traditional pairwise atomistic models, without compromising the accuracy of forces or trajectories. The CPU implementation of GridFF in the open-source FireCore package provides a 100-1000× speedup over all-atom simulations using LAMMPS, while the GPU implementation - running thousands of system replicas in parallel - samples millions of configurations per second, enabling an exhaustive exploration of the configuration space of small flexible molecules on surfaces within minutes. Furthermore, as demonstrated in our previous application of a similar technique to high-resolution scanning probe microscopy, GridFF can be extended beyond empirical pairwise potentials to those derived from <i>ab initio</i> electron densities. Altogether, this unlocks accurate high-throughput modeling of molecular self-assembly, adsorption, and scanning probe manipulation in surface science.

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2025-11-26
DOI
https://doi.org/10.1021/acs.jctc.5c01223
Primary Topic
Force Microscopy Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

GridFF: Efficient Simulation of Organic Molecules on Rigid Substrates

Prokop Hapala, Indranil Mal, Paolo Nicolini, Milan Kočí
Journal of Chemical Theory and Computation
Force Microscopy Techniques and Applications
article

GridFF: Efficient Simulation of Organic Molecules on Rigid Substrates

Prokop Hapala, Indranil Mal, Paolo Nicolini, Milan Kočí
article en

Abstract

We present GridFF, an efficient method for simulating molecules on rigid substrates, derived from techniques used in protein-ligand docking in biochemistry. By projecting molecule-substrate interactions onto precomputed spatial grids with tricubic B-spline interpolation, GridFF reduces the computational cost by orders of magnitude compared to traditional pairwise atomistic models, without compromising the accuracy of forces or trajectories. The CPU implementation of GridFF in the open-source FireCore package provides a 100-1000× speedup over all-atom simulations using LAMMPS, while the GPU implementation - running thousands of system replicas in parallel - samples millions of configurations per second, enabling an exhaustive exploration of the configuration space of small flexible molecules on surfaces within minutes. Furthermore, as demonstrated in our previous application of a similar technique to high-resolution scanning probe microscopy, GridFF can be extended beyond empirical pairwise potentials to those derived from <i>ab initio</i> electron densities. Altogether, this unlocks accurate high-throughput modeling of molecular self-assembly, adsorption, and scanning probe manipulation in surface science.

Journal of Chemical Theory and ComputationVol. 21(23)
Czech Academy of Sciences (CZ), Institute of Physics of the Slovak Academy of Sciences (SK), Czech Technical University in Prague (CZ)
Openalex Percentile: Top 71%
Force Microscopy Techniques and Applications
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