To estimate how well conformational ensembles of lipids are converged in trajectories, the Principal Component Analysis (PCA) following the PCALipids protocol was used . To this end, each lipid configuration was first aligned to the average structure of that lipid type, and PCA analysis was then applied on the Cartesian coordinates of all heavy atoms of the lipid. Because the motions along the first, major, principal component are the slowest ones , the equilibration of each lipid type was estimated from the ratio between the distribution convergence of the trajectories projected on the first PC and the trajectory length, τ rel = τ convergence /τ sim 70, 71 . If τ rel < 1, simulations can be considered to be sufficiently long for the lipid molecules to have sampled their conformational ensembles, while in simulations with τ rel > 1 individual molecules may not have fully sampled their conformational ensembles. Rigid molecules that do not exhibit significant conformational fluctuations, such as sterols, were excluded from the analysis. In practise, the distribution convergence times were calculated utilising its linear dependence on autocorrelation decay times, τ convergence = kτ autocorrelation , because calculation of autocorrelation decay times is faster and computationally more stable than direct calculation of distribution convergence times . The empirical coefficient k = 49 was calculated based on the analysis of 8 trajectories with the length of more than 200 ns, including simulations of POPC, POPS, POPE, POPG, and DPPC with the CHARMM36 force field. Because the coefficient k does not depend on the force field , the value determined from these CHARMM36 simulations can be used for all simulations in the Databank. The script that calculates the equilibration of lipids is available at Scripts/BuildDatabank/NMRPCA_timerelax.py in the NMRlipids Databank repository. The resulting values are stored in files named eq_times.json at folders in /Data/Simulations in the NMRlipids Databank repository.