7 papers
Let's Stalk About Membranes: Committor-Based Enhanced Sampling of Stalk Formation
Giorgia Rossi, Enrico Trizio, Davide Bochicchio +2
Membrane fusion is essential for cellular communication and function, and understanding how two lipid bilayers merge is key to informing therapeutic strategies. Functionalized nano…
Ceci n'est pas un committor, yet it samples like one: efficient sampling via approximated committor functions
Enrico Trizio, Giorgia Rossi, Michele Parrinello
Atomistic simulations are widely used to investigate reactive processes but are often limited by the rare event problem due to kinetic bottlenecks. We recently introduced an enhanc…
Committors without Descriptors
Peilin Kang, Jintu Zhang, Enrico Trizio +2
The study of rare events is one of the major challenges in atomistic simulations, and several enhanced sampling methods towards its solution have been proposed. Recently, it has be…
Enhanced Sampling in the Age of Machine Learning: Algorithms and Applications
Kai Zhu, Enrico Trizio, Jintu Zhang +4
Molecular dynamics simulations hold great promise for providing insight into the microscopic behavior of complex molecular systems. However, their effectiveness is often constraine…
Everything everywhere all at once: a probability-based enhanced sampling approach to rare events
Enrico Trizio, Peilin Kang, Michele Parrinello
The problem of studying rare events is central to many areas of computer simulations. In a recent paper [Kang, P., et al., Nat. Comput. Sci. 4, 451-460, 2024], we have shown that a…
Descriptors-free Collective Variables From Geometric Graph Neural Networks
Jintu Zhang, Luigi Bonati, Enrico Trizio +4
Enhanced sampling simulations make the computational study of rare events feasible. A large family of such methods crucially depends on the definition of some collective variables…