Abstract Body: G-protein coupled Receptors (GPCRs) have become the most significant target for drug development and are either blocked or activated by a third of FDA-approved drugs. However, despite our substantial knowledge of GPCR structure and activity, there are still over 140 non-olfactory GPCRs for which an endogenous ligand has not yet been identified, and consequently, their physiological function is still largely undiscovered. These groups of receptors are termed orphan GPCRs, and they are a great source of untapped, therapeutic potential, particularly in the cardiovascular system where they are implicated to be involved in cardiovascular control, with altered expression implicating them in physiological dysfunction and disease. Without knowledge of what substances, both endogenous and designed, activate, or inhibit their regulatory signaling pathways, it is extremely challenging to develop effective compounds to target them clinically and treat disease. The focus of this study, was to first, identify orphan GPCRs in resistance-sized systemic arteries that regulate blood pressure, and determine whether their expression is altered in male and/or female mice, with cardiovascular diseases, such as hypertension. Second, the aim was to pair Alphafold models for those orphan GPCRs of interest, with the Schrödinger machine learning algorithm, to generate tools, whether they are agonists or antagonists, to determine the vascular function of these receptors and their importance in the development of cardiovascular disease.