Computational Approaches for Decoding Select Odorant-Olfactory Receptor Interactions Using Mini-Virtual Screening.
|Title||Computational Approaches for Decoding Select Odorant-Olfactory Receptor Interactions Using Mini-Virtual Screening.|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Harini K, Sowdhamini R|
Olfactory receptors (ORs) belong to the class A G-Protein Coupled Receptor superfamily of proteins. Unlike G-Protein Coupled Receptors, ORs exhibit a combinatorial response to odors/ligands. ORs display an affinity towards a range of odor molecules rather than binding to a specific set of ligands and conversely a single odorant molecule may bind to a number of olfactory receptors with varying affinities. The diversity in odor recognition is linked to the highly variable transmembrane domains of these receptors. The purpose of this study is to decode the odor-olfactory receptor interactions using in silico docking studies. In this study, a ligand (odor molecules) dataset of 125 molecules was used to carry out in silico docking using the GLIDE docking tool (SCHRODINGER Inc Pvt LTD). Previous studies, with smaller datasets of ligands, have shown that orthologous olfactory receptors respond to similarly-tuned ligands, but are dramatically different in their efficacy and potency. Ligand docking results were applied on homologous pairs (with varying sequence identity) of ORs from human and mouse genomes and ligand binding residues and the ligand profile differed among such related olfactory receptor sequences. This study revealed that homologous sequences with high sequence identity need not bind to the same/ similar ligand with a given affinity. A ligand profile has been obtained for each of the 20 receptors in this analysis which will be useful for expression and mutation studies on these receptors.
|Alternate Journal||PLoS ONE|
|PubMed Central ID||PMC4519343|