METALICA: METAdynamics and repLICA exchange for enhanced diffusion sampling
Many proteins function through transitions between conformational states, yet rare states are rarely sampled by diffusion models trained on an equilibrium ensemble, demanding better sampling methods. We introduce METALICA, which implements Metadynamics on a pretrained diffusion model via Replica Exchange. It accumulates a bias potential along a Collective Variable, repels new samples from previous ones through biased sampling, and reweights samples onto the unbiased distribution. METALICA holds one replica per diffusion level, forming a Markov Chain that evolves through inter-replica communication and is refined in place as the bias grows. METALICA is the dual of sequential control, in wh...
| Authors | Alireza Omidi, Jiajun He, Jörg Gsponer et al. |
|---|---|
| Primary category | stat.ML |
| Published | 15 September 2026 |
| Last updated at source | 15 September 2026 |
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