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@ARTICLE{Fierro:837557,
      author       = {Fierro, Fabrizio and Suku, Eda and Alfonso-Prieto, Mercedes
                      and Giorgetti, Alejandro and Cichon, Sven and Carloni,
                      Paolo},
      title        = {{A}gonist {B}inding to {C}hemosensory {R}eceptors: {A}
                      {S}ystematic {B}ioinformatics {A}nalysis},
      journal      = {Frontiers in molecular biosciences},
      volume       = {4},
      issn         = {2296-889X},
      address      = {Lausanne},
      publisher    = {Frontiers},
      reportid     = {FZJ-2017-06445},
      pages        = {63},
      year         = {2017},
      abstract     = {Human G-protein coupled receptors (hGPCRs) constitute a
                      large and highly pharmaceutically relevant membrane receptor
                      superfamily. About half of the hGPCRs' family members are
                      chemosensory receptors, involved in bitter taste and
                      olfaction, along with a variety of other physiological
                      processes. Hence these receptors constitute promising
                      targets for pharmaceutical intervention. Molecular modeling
                      has been so far the most important tool to get insights on
                      agonist binding and receptor activation. Here we investigate
                      both aspects by bioinformatics-based predictions across all
                      bitter taste and odorant receptors for which site-directed
                      mutagenesis data are available. First, we observe that
                      state-of-the-art homology modeling combined with previously
                      used docking procedures turned out to reproduce only a
                      limited fraction of ligand/receptor interactions inferred by
                      experiments. This is most probably caused by the low
                      sequence identity with available structural templates, which
                      limits the accuracy of the protein model and in particular
                      of the side-chains' orientations. Methods which transcend
                      the limited sampling of the conformational space of docking
                      may improve the predictions. As an example corroborating
                      this, we review here multi-scale simulations from our lab
                      and show that, for the three complexes studied so far, they
                      significantly enhance the predictive power of the
                      computational approach. Second, our bioinformatics analysis
                      provides support to previous claims that several residues,
                      including those at positions 1.50, 2.50, and 7.52, are
                      involved in receptor activation.},
      cin          = {IAS-5 / INM-9 / INM-1},
      ddc          = {570},
      cid          = {I:(DE-Juel1)IAS-5-20120330 / I:(DE-Juel1)INM-9-20140121 /
                      I:(DE-Juel1)INM-1-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571) / 574 - Theory,
                      modelling and simulation (POF3-574)},
      pid          = {G:(DE-HGF)POF3-571 / G:(DE-HGF)POF3-574},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:28932739},
      UT           = {WOS:000455311400028},
      doi          = {10.3389/fmolb.2017.00063},
      url          = {https://juser.fz-juelich.de/record/837557},
}