The advantages of our direct combination of NMR experiments and MD simulations are demonstrated here for peptides in SDS detergent micelles, yet the presented approach can be applied to any biomolecular aggregate for which experimental spin relaxation times are accessible and realistic MD simulations can be performed. This includes many systems that are difficult to characterize by currently available experimental methods, such as fully or partially disordered proteins, bicelles or nanodiscs, membraneless organelles, and lipid droplets. In addition to the interpretation of experimental NMR data, the presented approach will be useful also for the evaluation and improvement of MD simulation quality. In the era of data science and machine learning, such benchmark data is becoming increasingly important and endeavours to define such data for proteins and lipids are ongoing.