Cellular membrane lipid composition is implicated in diseases and controls major biological functions, but membranes are difficult to study experimentally due to their intrinsic disorder and complex phase behaviour. Molecular dynamics (MD) simulations have been useful in understanding membrane systems, but they require significant computational resources and often suffer from inaccuracies in model parameters. Applications of data-driven and machine learning methods, currently revolutionising many fields, remain of limited use for membrane systems due to the lack of suitable training sets. Here we present the NMRlipids Databank—a community-driven, open-for-all database featuring programmatic access to quality- evaluated atom-resolution MD simulations of lipid bilayers. The NMRlipids Databank will benefit scientists in different disciplines by providing automatic ranking of simulations based on their quality against experiments, programmable interface for flexible implementation of data-driven and machine learning applications, and rapid access to simulation data through a graphical user interface. To demonstrate how it unlocks possibilities beyond current MD simulation studies, we analyzed the NMRlipids Databank to reveal how anisotropic diffusion of water and cholesterol flip-flop rates depend on membrane properties.
