Molecular Dynamics Simulations: A Systematic Review of Techniques and Applications in Biochemistry
Abstract
Molecular dynamics (MD) simulations have become a pivotal tool in biochemical research, providing profound insights into molecular interactions and dynamic behaviors at the atomic level. This study comprehensively reviews the historical development, fundamental theories, and key techniques of MD simulations, including all-atom simulations, coarse-grained simulations, and hybrid quantum mechanics/molecular mechanics (QM/MM) simulations. Enhanced sampling techniques, such as metadynamics, replica exchange molecular dynamics (REMD), and adaptive biasing force (ABF) methods, are discussed, with a focus on their roles in overcoming energy barriers and sampling rare events. Advanced analysis methods, including trajectory visualization, energy decomposition analysis, and principal component analysis (PCA), are also reviewed, with an emphasis on their applications in protein conformational studies. This study aims to highlight the central role of MD simulations in elucidating biomolecular behaviors and to provide guidance for their future research and technological development.
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Evidence Hub reads this as a systematic review, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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