Chigusa Kobayashi

In molecular dynamics (MD) simulations, enforcing holonomic constraints on specific interatomic distances is crucial to extend the integration time step while maintaining numerical stability. While double‐precision arithmetic has traditionally been used to ensure numerical accuracy, there is a growing demand for single‐ and mixed‐precision calculations as GPU‐accelerated MD simulations become increasingly widespread. In this study, we present improvements to the constraint solvers through an analytical treatment for bonds involving a single hydrogen atom ( groups). For more complex groups with multiple hydrogens ( and ), we introduce two precision‐level implementation strategies: (1) a mixed‐precision approach, where variables are generally described in single‐precision while temporary coordinate updates are handled in double‐precision and (2) a pairwise arithmetic approach, where temporary coordinate variables are represented as pairs of single‐precision values to reduce rounding errors. These implementation strategies reduce velocity‐update errors compared with schemes using single precision for all variables. Energy drift analysis in microcanonical simulations confirms that these strategies maintain accuracy comparable to full double‐precision implementations. Performance benchmarks on GPUs with limited FP64 throughput (RTX 3080 and A6000 Ada) show that our proposed implementation strategies substantially reduce runtime compared with full double‐precision calculations. Conversely, on architectures with balanced FP32 and FP64 performance, such as CPUs or H100 GPUs, full double‐precision arithmetic remains the preferred choice for the constraint kernels evaluated in this study. Overall, these findings demonstrate that the proposed strategies provide an effective balance between numerical accuracy and computational performance on GPUs with limited FP64 throughput.

F ₁ -ATPase comprises the stator ring consisting of α ₃ β ₃ subunits and the rotor γ subunit. The γ subunit rotation mechanism has been extensively investigated by biochemical analyses, structural studies, single-molecule measurements, and computational studies. Recent cryoelectron microscopy (cryo-EM) structures of F ₁ -ATPase from the thermophilic bacterium Bacillus PS3 (TF ₁ ) provide us with further possibilities for a better understanding of the γ-rotation mechanisms. Using cryo-EM structures having the γ-rotation angles close to the binding dwell and catalytic dwell states, we investigate the relationships between the γ subunit rotation, conformational changes of the stator α ₃ β ₃ subunits, and the nucleotide-binding and release. We performed targeted molecular dynamics (MD) simulations with external forces on the α ₃ β ₃ subunits and observed 80° substep rotations of the γ subunit. Then, we optimized the most probable transition pathway through the mean-force string method simulations with 64 images. Finally, using umbrella sampling, we calculated the potential of mean forces along the minimum free energy pathway during the 80° substep rotation. Our MD simulations suggest that 80° substep rotation is divided into the first rotation, resting, and the second rotation. Notably, the first rotation is driven by the distortion of the stator α ₃ β ₃ subunits, and the second rotation is induced mainly by direct β/γ subunit interactions. This model, which we call the distortion–push mechanism, is consistent with the residue-level experimental analysis on F ₁ -ATPase and the atomic structures determined by X-ray crystallography and cryo-EM.

F ₁ -ATPase comprises the stator ring consisting of α₃β₃ subunits and the rotor γ subunit. The γ subunit rotation mechanism has been extensively investigated by biochemical analyses, structural studies, single-molecule measurements, and computational studies. Recent cryo-electron microscopy (cryo-EM) structures of F ₁ -ATPase from the thermophilic bacterium Bacillus PS3 (TF ₁ ) provide us with further possibilities for a better understanding of the γ-rotation mechanisms. Using cryo-EM structures having the γ-rotation angles close to the binding dwell and catalytic dwell states, we investigate the relationships between the γ subunit rotation, conformational changes of the stator α ₃ β ₃ subunits, and the nucleotide-binding and release. We performed targeted molecular dynamics (MD) simulations with external forces on the α₃β₃ subunits and observed 80° substep rotations of the γ subunit. Then, we optimized the most probable transition pathway through the mean-force string method simulations with 64 images. Finally, using umbrella sampling, we calculated the potential of mean forces along the minimum free energy pathway during the 80° substep rotation. Our MD simulations suggest that 80° substep rotation is divided into the first rotation, resting, and the second rotation. Notably, the first rotation is driven by the distortion of the stator α ₃ β ₃ subunits, and the second rotation is induced mainly by direct β/γ subunit interactions. This model, which we call the distortion-push mechanism, is consistent with the residue-level experimental analysis on F ₁ -ATPase and the atomic structures determined by X-ray crystallography and cryo-EM.

GENeralized-Ensemble SImulation System (GENESIS) is a molecular dynamics (MD) software developed to simulate the conformational dynamics of a single biomolecule, as well as molecular interactions in large biomolecular assemblies and between multiple biomolecules in cellular environments. To achieve the latter purpose, the earlier versions of GENESIS emphasized high performance in atomistic MD simulations on massively parallel supercomputers, with or without graphics processing units (GPUs). Here, we implemented multiscale MD simulations that include atomistic, coarse-grained, and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations. They demonstrate high performance and are integrated with enhanced conformational sampling algorithms and free-energy calculations without using external programs except for the QM programs. In this article, we review new functions, molecular models, and other essential features in GENESIS version 2.1 and discuss ongoing developments for future releases.

Generalized replica exchange with solute tempering (gREST) is one of the enhanced sampling algorithms for proteins or other systems with rugged energy landscapes. Unlike the replica‐exchange molecular dynamics (REMD) method, solvent temperatures are the same in all replicas, while solute temperatures are different and are exchanged frequently between replicas for exploring various solute structures. Here, we apply the gREST scheme to large biological systems containing over one million atoms using a large number of processors in a supercomputer. First, communication time on a multi‐dimensional torus network is reduced by matching each replica to MPI processors optimally. This is applicable not only to gREST but also to other multi‐copy algorithms. Second, energy evaluations, which are necessary for the multistate bennet acceptance ratio (MBAR) method for free energy estimations, are performed on‐the‐fly during the gREST simulations. Using these two advanced schemes, we observed 57.72 ns/day performance in 128‐replica gREST calculations with 1.5 million atoms system using 16,384 nodes in Fugaku. These schemes implemented in the latest version of GENESIS software could open new possibilities to answer unresolved questions on large biomolecular complex systems with slow conformational dynamics.

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations.

Spike (S) protein is the primary antigenic target for neutralization and vaccine development for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It decorates the virus surface and undergoes large motions of its receptor binding domains (RBDs) to enter the host cell. Here, we observe Down, one-Up, one-Open, and two-Up-like structures in enhanced molecular dynamics simulations, and characterize the transition pathways via inter-domain interactions. Transient salt-bridges between RBD_A and RBD_C and the interaction with glycan at N343_B support RBD_A motions from Down to one-Up. Reduced interactions between RBD_A and RBD_B in one-Up induce RBD_B motions toward two-Up. The simulations overall agree with cryo-electron microscopy structure distributions and FRET experiments and provide hidden functional structures, namely, intermediates along Down-to-one-Up transition with druggable cryptic pockets as well as one-Open with a maximum exposed RBD. The inherent flexibility of S-protein thus provides essential information for antiviral drug rational design or vaccine development.

Residue-level coarse-grained (CG) models have become one of the most popular tools in biomolecular simulations in the trade-off between modeling accuracy and computational efficiency. To investigate large-scale biological phenomena in molecular dynamics (MD) simulations with CG models, unified treatments of proteins and nucleic acids, as well as efficient parallel computations, are indispensable. In the GENESIS MD software, we implement several residue-level CG models, covering structure-based and context-based potentials for both well-folded biomolecules and intrinsically disordered regions. An amino acid residue in protein is represented as a single CG particle centered at the Cα atom position, while a nucleotide in RNA or DNA is modeled with three beads. Then, a single CG particle represents around ten heavy atoms in both proteins and nucleic acids. The input data in CG MD simulations are treated as GROMACS-style input files generated from a newly developed toolbox, GENESIS-CG-tool. To optimize the performance in CG MD simulations, we utilize multiple neighbor lists, each of which is attached to a different nonbonded interaction potential in the cell-linked list method. We found that random number generations for Gaussian distributions in the Langevin thermostat are one of the bottlenecks in CG MD simulations. Therefore, we parallelize the computations with message-passing-interface (MPI) to improve the performance on PC clusters or supercomputers. We simulate Herpes simplex virus (HSV) type 2 B-capsid and chromatin models containing more than 1,000 nucleosomes in GENESIS as examples of large-scale biomolecular simulations with residue-level CG models. This framework extends accessible spatial and temporal scales by multi-scale simulations to study biologically relevant phenomena, such as genome-scale chromatin folding or phase-separated membrane-less condensations. Author summary Molecular dynamics (MD) simulations have been widely used to investigate biological phenomena that are difficult to study only with experiments. Since all-atom MD simulations of large biomolecular complexes are computationally expensive, coarse-grained (CG) models based on different approximations and interaction potentials have been developed so far. There are two practical issues in biological MD simulations with CG models. The first issue is the input file generations of highly heterogeneous systems. In contrast to well-established all-atom models, specific features are introduced in each CG model, making it difficult to generate input data for the systems containing different types of biomolecules. The second issue is how to improve the computational performance in CG MD simulations of heterogeneous biological systems. Here, we introduce a user-friendly toolbox to generate input files of residue-level CG models containing folded and disordered proteins, RNAs, and DNAs using a unified format and optimize the performance of CG MD simulations via efficient parallelization in GENESIS software. Our implementation will serve as a framework to develop novel CG models and investigate various biological phenomena in the cell.