G protein-coupled receptors (GPCRs) are a large family of membrane proteins involved in diverse physiological processes and represent important pharmacological targets. However, many orphan GPCRs (oGPCRs) remain poorly characterised, despite increasing evidence linking them to cancer, metabolic disorders and neurological disease. The project will develop a computational framework to investigate how sequence variation, receptor dynamics and membrane interactions contribute to oGPCR function. GPR183 will serve as the principal model system, providing a biologically relevant example of an oGPCR associated with immune regulation and acute myeloid leukaemia. Disease-associated mutations will be used to investigate how local structural changes propagate through the receptor and alter its conformational and signalling landscapes. The computational approach will combine AlphaFold3 structure prediction, conformational ensemble generation, all-atom molecular dynamics simulations in explicit lipid membranes, energy-landscape analysis and multiscale energetic calculations. Graph-based network analysis and first-passage-time calculations will be used to characterise residue-level communication pathways and identify regions involved in long-range allosteric regulation.  Selected systems will undergo long-timescale simulations and free-energy calculations to characterise protein–protein interactions and their dynamic stability. Preliminary studies of the GPR183 A338V mutation demonstrate the potential of this approach. Computational analyses identified mutation-dependent reorganisation of the C-terminal conformational ensemble and allosteric communication networks, while experimental measurements provided functional support through altered GRK2 and β-arrestin recruitment despite preserved Gi signalling. The computational framework will now be extended to additional GPR183 mutations, including L125P and Q229K, and subsequently to other poorly characterised oGPCRs. By integrating sequence, structure, molecular dynamics, energy landscapes and receptor–protein interaction networks, the project will establish a computational framework for understanding how dynamic molecular mechanisms determine signalling specificity in oGPCRs. The resulting models will provide a basis for interpreting disease-associated variants, identifying functionally important receptor regions and generating experimentally testable mechanistic hypotheses for poorly characterised GPCRs.