Here, 3D dynamic protein descriptors (3DDPDs) were developed leveraging atom coordinates and partial charges from publicly available MD simulations from GPCRmd. Two descriptor architectures were explored: embedding-like (protein specific -ps3DDPD), and one-hot encodings (residue specific -rs3DDPD). The performance in PCM GPCR bioactivity prediction of these novel protein descriptors was benchmarked against and in combination with a panel of state-of-the-art protein descriptors. Finally, the ability of our 3DDPDs to capture dynamic changes driven by (cancer-related) somatic point mutations in GPCRs was tested. These results highlight 3DDPDs as a stepping stone for further research on protein descriptors used for predicting drug-target interactions based on protein dynamics.