Summary: Title: Enhancing olfactory receptor expression for biochemical studies of odorant- receptor interactions Our sense of smell is mediated by olfactory receptors (ORs), which are the largest family of G protein-coupled receptors (GPCRs). Some ORs also function outside the nose to coordinate important physiology; OR function has been shown to be important in kidney, skin, prostate, and in multiple cancer tissues. Despite groundbreaking advances in delineating the structural basis of GPCR action, ORs remain among the most unexplored class GPCRs in terms of structure, ligand binding and activation mechanism. This is primarily because: 1) low expression of ORs in heterologous cell lines impedes structure-function studies and 2) we lack small molecules that can potently activate and inhibit OR function. In the past two years, Matsunami and Vaidehi have uncovered amino acid sequence evolution and structural properties that contribute to OR expression. Simultaneously, Matsunami and Manglik used engineered ORs with enhanced expression to validate new approaches to purify ORs in detergents for structural and biochemical studies. Building on these successes, we propose to address fundamental challenges in OR expression and ligand discovery in iterative predict-test cycles combining novel computational methods and experimental testing with two aims. In Aim 1, we propose to engineer mutant ORs for six human ORs to enable overexpression of these receptors for in vitro studies and tractability for large-scale purification in detergents. In Aim 2, we will map OR ligand binding sites and discover new high affinity agonists and antagonists using a combination of structural modeling, ligand docking and biochemical experiments. We will also develop approaches to determine structures of active ORs bound to odorants and G proteins by cryo-EM. The outcome of the proposed work will provide new foundations to interrogate OR function and widely available computational approaches to accelerate the OR field.

Narrative: Understanding the molecular mechanism of how olfactory receptors recognize multitude of odorants lays the foundation to our understanding of the olfactory system. The proposed interdisciplinary research will develop computational methods using machine learning techniques, concurrent with in vitro cell based assays and cryo-EM studies to push this understanding forward by enhancing the in vitro expression of olfactory receptors and enabling the structure-function studies. The combination of computational methods and experiments will provide unprecedented insights into mechanisms of odorant-olfactory receptor recognition and map the residues involved in such recognition events.