Fast intermolecular interaction energy calculation with the OPLS-AA force field

HessFit: Deriving Molecule-Specific Force Fields from Quantum Mechanical Hessians.

Free Energies of Solvation in Cyclohexane and Water: United-Atom vs All-Atom.

Free energies of solvation (ΔGsol) in a prototypical liquid alkane, cyclohexane, have been computed for 101 organic molecules at 25 °C. Monte Carlo statistical mechanics (MC) was used with free-energy perturbation theory (FEP) and both OPLS united-atom (UA) and all-atom (AA) force fields. Updated OPLS-UA parameters are provided along with thermodynamic results for 23 liquid alkanes; the modifications make the UA and AA force fields fully compatible. The average errors for ΔGsol in comparison to experimental data are ca. 0.5 kcal/mol for both force fields. This supports general use of the UA model, since it reduces the required computation times by 5-10-fold. The largest errors are about 1 kcal/mol and occur for small molecules with relatively large dipole moments and for perfluorocarbons. The former case is attributable to the lack of solvent-polarization in the force fields, and the latter issue can be remedied by reducing the Lennard-Jones well depth for the interaction of saturated carbon and fluorine. Results for free energies of hydration are also provided for the 101 solutes in TIP4P water and the average error is again 0.5 kcal/mol. The combined results provide cyclohexane/water free energies of transfer with average errors of 0.7 kcal/mol. In conjunction with prior results for solvation in benzene and perfluorobenzene, the 0.5 kcal/mol level of accuracy seems general for the performance of current generation, nonpolarizable force fields. Implications for modeling hydrophobic effects and protein-ligand binding are also considered.

Fast-Forward: Automatic Assignment and Assessment of Bonded Parameters for the Martini Force Field

Coarse-grained molecular dynamics simulations of bio- and macromolecular systems offer a method of accessing otherwise unobtainable time and length scales, compared to atomistic simulation techniques. However, a limiting step is often the generation and validation of the coarse-grained models. Here, we describe a new software package, Fast-Forward, which aids parametrization of models for the widely used Martini coarse-grained force field. In comparison to other similar packages, Fast-Forward offers a system-agnostic suite of tools to parametrize molecules of any size, existing in any environment. It achieves this while maintaining ease of use and the use of interoperable file formats from the Martini software ecosystem. Through its three subprograms, the package offers tools for trajectory mapping, parameter generation, and model validation. We demonstrate the potential of the package for several different use cases, from small biological molecules (glutathione and glutathione disulfide) to models of synthetic polymers (poly(methyl methacrylate), PMMA).

Efficient Force Evaluation via Fragmentation: Toward Geometry Optimization of Protein-Ligand Systems with Quantum Mechanical Accuracy.

This work presents a hybrid fragmentation-based approach, FragQMMM, that enables efficient and accurate force evaluation for large molecular systems, and successfully reproduces the hydrogen-bond network and preserving the underlying structure-activity relationship.

High-Fidelity Surrogate Framework for Rapid Solvation of Gas-Phase and Interfacial Reaction Potential Energy Surfaces.

Solvent can reorganize reaction paths and barriers, but bringing those effects into mechanistic calculations remains expensive, because every image in a solvated climbing-image nudged elastic band search requires a new self-consistent reaction-field calculation. Here, we present a high-fidelity surrogate framework that keeps a preconstructed nonsolvated reaction valley as the backbone and models only the geometry-dependent solvent contribution needed to transform it into the solution-phase potential of mean force, i.e., the solvent-shaped free-energy surface. Using uncertainty-selected evaluations with the plane-wave implicit solvation model based on electron density (PW-SMD), the method optimizes solvated reaction paths on the fly and recovers 300 K free-energy profiles from local surrogate Hessians. For 16 small-molecule reactions in water and 17 Cu(111) interfacial reactions, the framework reduces the average number of solvent-response calculations from 826.3 to 67.3 and from 1231.9 to 51.5, respectively, while maintaining small-molecule barrier differences of only 0.04 eV on average and an interfacial reaction barrier agreement within a few hundredths of an eV for most reactions. The surrogate also reproduces representative room-temperature activation and reaction free energies. These results show that solvent-induced reshaping of reaction pathways can be captured accurately from a sparse, strategically chosen set of solution-phase calculations, turning solvated reaction-path and free-energy calculations into a practical tool for molecular and interfacial mechanistic studies.

Gaussian Accelerated Molecular Dynamics in GROMACS

Gaussian accelerated molecular dynamics (GaMD) enhances conformational sampling by adding a smooth boost potential without requiring predefined collective variables, but an engine-integrated implementation has not been available in GROMACS. Here, we implement total-, dihedral-, and dual-boost GaMD in GROMACS 2025.4, including staged energy-statistics collection, GPU-based bias evaluation and force scaling, restart support, and outputs required for cumulant-based free-energy reweighting. The implementation was evaluated using four benchmark systems spanning conformational free energies, protein folding, and ligand recognition. For alanine dipeptide, a reweighted 100 ns GaMD trajectory recovered the major free-energy basins and rotational barriers in overall agreement with a 1000 ns conventional MD simulation. For chignolin and TC5b, all three independent trajectories for each system sampled native-like folded states from extended conformations within 300 ns and 1 μs, respectively; the best TC5b structure had a minimum backbone RMSD of 0.03 nm from the experimental structure. In the benzene–T4 lysozyme system, two of five independent 500 ns trajectories captured both ligand binding and dissociation, yielding a bound pose with a minimum ligand RMSD of 0.06 nm from the crystal structure. Across all four systems, the boost-potential distributions were approximately Gaussian, and second-order cumulant reweighting resolved the expected conformational and binding free-energy basins. These results demonstrate that GROMACS-GaMD provides a practical, GPU-enabled, collective-variable-free enhanced-sampling framework for biomolecular free-energy calculations, protein folding, and ligand-binding studies.