A novel virus, severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2), causing coronavirus disease 2019 (COVID-19) worldwide appeared in 2019. Currently, we do not have a medicament that treats the disease. One of the rea-sons for the absence of treatment is related to the scarcity of detailed scientific knowledge of the members of the Coro-naviridae family, including the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). Structural studies of the MERS-CoV proteins in the current literature are extremely limited. We present here detailed characterization of the struc-tural properties of MERS-CoV macro domain in aqueous solution at the atomic level with dynamics. For this study, we conducted extensive replica exchange molecular dynamics simulations linked to a generative neural networks and we use the resulting trajectories for structural analysis. We perform structural clustering based on the radius of gyration and end-to-end distance of MERS-CoV macro domain in aqueous solution with dynamics at the atomic level. We also report and analyze the residue-level intrinsic disorder features, flexibility and secondary structure. Furthermore, we study the pro-pensities of this macro domain for protein-protein interactions and for the RNA and DNA binding. Results are in agree-ment with available nuclear magnetic resonance spectroscopy findings and present more detailed insights into the struc-tural properties of MERS CoV macro domain. Overall, this work further shows that neural networks can be used as an exploratory tool for the studies of CoV family molecular conformational space at the nano level.