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This mini-review reports the recent advances in biomolecular simulations, particularly for nucleic acids, and provides the potential effects of the emerging exascale computing on nucleic acid simulations, emphasizing the need for advanced computational strategies to fully exploit this technological frontier. Specifically, we introduce recent breakthroughs in computer architectures for large-scale biomolecular simulations and review the simulation protocols for nucleic acids regarding force fields, enhanced sampling methods, coarse-grained models, and interactions with ligands. We also explore the integration of machine learning methods into simulations, which promises to significantly enhance the predictive modeling of biomolecules and the analysis of complex data generated by the exascale simulations. Finally, we discuss the challenges and perspectives for biomolecular simulations as we enter the dawning exascale computing era.
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http://dx.doi.org/10.1016/j.sbi.2024.102847 | DOI Listing |
Curr Opin Struct Biol
July 2025
Molecular Biophysics Unit, Indian Institute of Science, Bangalore, Karnataka 560012, India. Electronic address:
Since the publication of the first papers in the early 1990s, molecular simulation as a reliable biophysical tool in the area of membrane biophysics has come a long way. Advances in simulation algorithms, coupled with exascale computing have pushed the size and time scales of biomolecular membrane simulations to scales where connections to experiments are made with higher fidelity. When integrated with experimental data in a theoretically well-grounded manner, current biomolecular simulations are providing indispensable insights that cannot be obtained through experiments alone.
View Article and Find Full Text PDFJ Chem Theory Comput
August 2025
Department of Chemistry, University of Chicago, Chicago, Illinois 60637, United States.
Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes.
View Article and Find Full Text PDFJ Phys Chem Lett
June 2025
Collaboratory for Advanced Computing and Simulation, University of Southern California, Los Angeles, California 90089-0242, United States.
We present a foundation model for exascale molecular dynamics simulations by leveraging an E(3) equivariant network architecture (Allegro) and a set of large-scale organic and inorganic materials data sets merged by the Total Energy Alignment framework. The obtained model (Allegro-FM) is versatile for various material simulations for diverse downstream tasks covering 89 elements in the training sets. Allegro-FM exhibits excellent agreement with high-level quantum chemistry theories in describing structural, mechanical, and thermodynamic properties, while exhibiting emergent capabilities for structural correlations, reaction kinetics, mechanical strengths, fracture, and solid/liquid dissolution, for which the model has not been trained.
View Article and Find Full Text PDFChem Commun (Camb)
July 2025
Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
Real-space Kohn-Sham density functional theory (real-space KS-DFT) enables large-scale electronic structure simulations that is particularly well-suited for the modern high-performance computing (HPC) architectures. This feature article reviews its theoretical foundations, highlights the algorithmic advances and recent developments, and showcases applications in complex nano systems. We aim to provide a perspective on the trajectory of real-space KS-DFT as an emerging tool for computational chemistry and materials science in the exascale era.
View Article and Find Full Text PDFPhys Rev E
March 2025
Queen's University Belfast, Centre for Light Matter Interactions, School of Mathematics and Physics, Belfast BT7 1NN, United Kingdom.
With advances in laser technology reaching the multipetawatt era, the expanding experimental prospects for high-order harmonic generation from solid targets prompt more rigorous particle-in-cell (PIC) simulation campaigns for elucidating the generation mechanisms. However, accurately representing a broad range of high frequencies in multidimensional simulations remains challenging. The commonly employed finite difference time domain (FDTD) method, the Yee stencil, introduces artificial numerical dispersion, inducing unphysical angular deviation of higher-order harmonics.
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