The next revolution in computational simulations: Harnessing AI and quantum computing in molecular dynamics
Abstract
The integration of artificial intelligence, machine learning and quantum computing into molecular dynamics simulations is catalyzing a revolution in computational biology, improving the accuracy and efficiency of simulations. This review describes the advancements and applications of these technologies to process vast molecular dynamics simulation datasets, adapt parameters of simulations and gain insight into complex biological processes. These advances include the use of predictive force fields, adaptive algorithms and quantum-assisted methodologies. While the integration of artificial intelligence and quantum computing with MD simulations provides insightful and stimulating improvements to our understanding of molecular mechanisms, it could introduce new issues related to data quality, interpretability of models and computational complexity. Modern multidisciplinary approaches are needed to navigate these challenges and exploit the potential of these emerging technologies for MD simulations of biomolecular systems.
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