Molecular Dynamics Simulations: Principles, Algorithms, and Emerging Applications

Molecular dynamics (MD) simulation is a fundamental technique for resolving biomolecular structures and functions at atomic resolution. Accelerated by GPU computing and machine learning-integrated force fields (FF), modern MD simulation facilitates the study of large-scale systems and rare biological events, such as protein folding, allosteric transitions, etc. While advanced sampling methods and AI integration have significantly enhanced efficiency in drug discovery and protein engineering, the field still faces challenges regarding FF accuracy, timescale constraints, and quantum effects. Continued development of hybrid quantum and molecular mechanics methods and standardized workflows is essential to further improve the predictive power and reproducibility of MD in biotechnological research. In this review, we attempted to provide the latest developments in the MD simulations.