Automatic modeling of mammalian olfactory receptors and docking of odorants

Protein Eng Des Sel. 2012 Aug;25(8):377-86. doi: 10.1093/protein/gzs037. Epub 2012 Jun 12.


We present a procedure that (i) automates the homology modeling of mammalian olfactory receptors (ORs) based on the six three-dimensional (3D) structures of G protein-coupled receptors (GPCRs) available so far and (ii) performs the docking of odorants on these models, using the concept of colony energy to score the complexes. ORs exhibit low-sequence similarities with other GPCR and current alignment methods often fail to provide a reliable alignment. Here, we use a fold recognition technique to obtain a robust initial alignment. We then apply our procedure to a human OR that we have previously functionally characterized. The analysis of the resulting in silico complexes, supported by receptor mutagenesis and functional assays in a heterologous expression system, suggests that antagonists dock in the upper part of the binding pocket whereas agonists dock in the narrow lower part. We propose that the potency of agonists in activating receptors depends on their ability to establish tight interactions with the floor of the binding pocket. We developed a web site that allows the user to upload a GPCR sequence, choose a ligand in a library and obtain the 3D structure of the free receptor and ligand-receptor complex (

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acid Sequence
  • Computer Simulation
  • Databases, Protein
  • Humans
  • Ligands
  • Models, Molecular
  • Molecular Sequence Data
  • Odorants
  • Protein Binding
  • Protein Folding
  • Receptors, Odorant / chemistry*
  • Receptors, Odorant / metabolism*
  • Reproducibility of Results
  • Sequence Alignment
  • Sequence Homology, Amino Acid
  • Thermodynamics


  • Ligands
  • OR1G1 protein, human
  • Receptors, Odorant