In the field of molecular simulation for drug design, traditional molecular mechanic force
fields and quantum chemical theories have been instrumental but limited in terms of …

Biomolecular dynamics simulation is a fundamental technology for life sciences research,
and its usefulness depends on its accuracy and efficiency,–. Classical molecular dynamics …

Geometric deep learning has been revolutionizing the molecular modeling field. Despite the
state-of-the-art neural network models are approaching ab initio accuracy for molecular …

In the last quarter-century, the field of molecular dynamics (MD) has undergone a
remarkable transformation, propelled by substantial enhancements in software, hardware …

Photocatalytic N2 fixation offers promise for ammonia synthesis, yet traditional
photocatalysts encounter challenges such as low efficiency and short carrier lifetimes …

Platelet-activating factor (PAF) is a potent phospholipid mediator crucial in multiple
inflammatory and immune responses through binding and activating the PAF receptor …

Graph neural network (GNN) architectures have emerged as promising force field models,
exhibiting high accuracy in predicting complex energies and forces based on atomic …

Hierarchical porous carbon (HPC) has gained extensive application in recent decades in the
fields including adsorption, catalysis, and electrochemistry. The incorporated meso/macro …

The molecular force field (FF) determines the accuracy of molecular dynamics (MD) and is
one of the major bottlenecks that limits the application of MD in molecular design. Recently …

The only NMR-active oxygen isotope, oxygen-17 (17O), serves as a sensitive probe due to
its large chemical shift range, the electric field gradient at the oxygen site, and the …