With this methodology, we decomposed the high-dimensional chemical space of proteins into fragments containing up to 8 heavy atoms (362 of them in total), which is much easier to cover systematically. We subsequently implemented an active learning strategy to sample representative conformations from xTB MD trajectories and further sampled from NequIP-based MD trajectories at temperatures ranging from 100 to 800 K. As a result, the conformations in our database adequately cover all relevant regions of the potential energy surface for nonreactive MD simulations of protein fragments within a reasonable temperature range at the DFT level.