The dopamine D2 receptor (D2R) is a major G protein-coupled receptor (GPCR) and an established pharmacological target, particularly in neuropsychiatry. Despite extensive pharmacological study, the chemical space compatible with D2R binding remains only sparsely explored. This project applies large-scale structure-based virtual screening to identify and characterize novel D2R chemotypes and extends the same methodology to comparative ligand discovery across related receptors. An established hierarchical workflow combines structural and knowledge-based filtering, safety and drug-property screening, molecular docking with AutoDock Vina, high-resolution refinement with Rosetta GALigandDock, and molecular dynamics simulations with GROMACS. Computationally inexpensive stages progressively reduce very large compound populations before increasingly expensive structural calculations are applied. The initial D2R campaign starts from approximately 11 million immediately available structures, while the underlying searchable chemical space approaches 100 billion theoretical compounds, providing substantial scope for subsequent campaigns and methodological development. The computational infrastructure and reproducible workflow have already been developed, tested and calibrated on Dardel within the preceding NAISS SMALL allocation. The proposed project therefore represents a transition from workflow development and calibration to production-scale screening. In addition to identifying candidate D2R chemotypes and enabling comparisons across related receptors, the project will evaluate a reproducible and scalable methodology applicable to large-scale structure-based virtual screening more generally.