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@ARTICLE{AlfonsoPrieto:862730,
      author       = {Alfonso-Prieto, Mercedes and Navarini, Luciano and Carloni,
                      Paolo},
      title        = {{U}nderstanding {L}igand {B}inding to {G}-{P}rotein
                      {C}oupled {R}eceptors {U}sing {M}ultiscale {S}imulations},
      journal      = {Frontiers in molecular biosciences},
      volume       = {6},
      issn         = {2296-889X},
      address      = {Lausanne},
      publisher    = {Frontiers},
      reportid     = {FZJ-2019-02973},
      pages        = {29},
      year         = {2019},
      abstract     = {Human G-protein coupled receptors (GPCRs) convey a wide
                      variety of extracellular signals inside the cell and they
                      are one of the main targets for pharmaceutical intervention.
                      Rational drug design requires structural information on
                      these receptors; however, the number of experimental
                      structures is scarce. This gap can be filled by
                      computational models, based on homology modeling and docking
                      techniques. Nonetheless, the low sequence identity across
                      GPCRs and the chemical diversity of their ligands may limit
                      the quality of these models and hence refinement using
                      molecular dynamics simulations is recommended. This is the
                      case for olfactory and bitter taste receptors, which
                      constitute the first and third largest GPCR groups and show
                      sequence identities with the available GPCR templates below
                      $20\%.$ We have developed a molecular dynamics approach,
                      based on the combination of molecular mechanics and coarse
                      grained (MM/CG), tailored to study ligand binding in GPCRs.
                      This approach has been applied so far to bitter taste
                      receptor complexes, showing significant predictive power.
                      The protein/ligand interactions observed in the simulations
                      were consistent with extensive mutagenesis and functional
                      data. Moreover, the simulations predicted several binding
                      residues not previously tested, which were subsequently
                      verified by carrying out additional experiments. Comparison
                      of the simulations of two bitter taste receptors with
                      different ligand selectivity also provided some insights
                      into the binding determinants of bitter taste receptors.
                      Although the MM/CG approach has been applied so far to a
                      limited number of GPCR/ligand complexes, the excellent
                      agreement of the computational models with the mutagenesis
                      and functional data supports the applicability of this
                      method to other GPCRs for which experimental structures are
                      missing. This is particularly important for the challenging
                      case of GPCRs with low sequence identity with available
                      templates, for which molecular docking shows limited
                      predictive power.},
      cin          = {IAS-5 / INM-9},
      ddc          = {570},
      cid          = {I:(DE-Juel1)IAS-5-20120330 / I:(DE-Juel1)INM-9-20140121},
      pnm          = {574 - Theory, modelling and simulation (POF3-574)},
      pid          = {G:(DE-HGF)POF3-574},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31131282},
      UT           = {WOS:000466812100001},
      doi          = {10.3389/fmolb.2019.00029},
      url          = {https://juser.fz-juelich.de/record/862730},
}