Metadynamics is an enhanced sampling technique used in molecular dynamics (MD) simulations to efficiently explore the free energy landscape of molecular systems. By adding history-dependent biasing potentials to selected collective variables, metadynamics accelerates the sampling of rare events, such as ligand binding/unbinding, conformational changes, and protein folding, enabling the calculation of free energy profiles and identification of transition states. Metadynamics might be best for slow transitions through unknown energy landscapes. Other enhanced sampling techniques can be used when the reaction coordinate is known e.g. ligand unbinding.
Importance in Computational Drug Discovery:
- Enables the exploration of slow or rare events (e.g., ligand binding, conformational transitions) that are inaccessible to standard MD timescales.
- Facilitates the calculation of binding free energies and elucidation of binding/unbinding pathways for drug candidates.
- Supports the identification of metastable states, transition states, and key intermediates in biomolecular processes.
- Assists in understanding allosteric modulation and induced-fit effects in protein–ligand interactions.
- Integrates with structure-based drug design workflows to provide mechanistic insights and guide lead optimization.
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