Abstract
Olfactory receptors (ORs) constitute the largest superfamily of G protein-coupled receptors (GPCRs). ORs are involved in sensing odorants as well as in other ectopic roles in non-nasal tissues. Matching of an enormous number of the olfactory stimulation repertoire to its counterpart OR through machine learning (ML) will enable understanding of olfactory system, receptor characterization, and exploitation of their therapeutic potential. In the current study, we have selected two broadly tuned ectopic human OR proteins, OR1A1 and OR2W1, for expanding their known chemical space by using molecular descriptors. We present a scheme for selecting the optimal features required to train an ML-based model, based on which we selected the random forest (RF) as the best performer. High activity agonist prediction involved screening five databases comprising ~23 M compounds, using the trained RF classifier. To evaluate the effectiveness of the machine learning based virtual screening and check receptor binding site compatibility, we used docking of the top target ligands to carefully develop receptor model structures. Finally, experimental validation of selected compounds with significant docking scores through in vitro assays revealed two high activity novel agonists for OR1A1 and one for OR2W1.
Highlights
G protein-coupled receptors (GPCRs, known as seven transmembrane or 7TM receptors) represent the largest family of cell surface receptors
We report the machine learning (ML)-based virtual screening workflow for agonist identification of two broadly tuned ectopic Olfactory receptors (ORs): OR1A1 and OR2W1
support vector machines (SVMs) was applied to OR1A1 and OR2W1 to screen a test set of 258 compounds and resulted in the identification of novel agonists for both receptors, with a hit rate of 39 to 40% for these ORs [14]
Summary
G protein-coupled receptors (GPCRs, known as seven transmembrane or 7TM receptors) represent the largest family of cell surface receptors. Olfactory receptors (ORs) [2], first reported in 1991, represent the largest sub-group of G protein-coupled receptors (GPCRs) [3]. A recent study has reported the localization of a subset of ORs in various tissues including the brain, prostate, sperm, colon, breast, lungs and kidneys [6]. Functional characterization of these ectopic ORs in different tissues support their roles in cell-cell recognition, migration, proliferation, apoptosis, exocytosis, and novel alternate pathways. The absence of any experimentally determined animal OR structure is attributed to ORs being low abundance, tissue-specific hydrophobic membrane proteins, which are difficult to crystallize. ORs show poor trafficking to the plasma membrane, due to mRNA retention when expressed heterologously in different cell types [11]
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