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@ARTICLE{Rossetti:901934,
      author       = {Rossetti, Giulia and Capelli, Riccardo and Li, Jinyu and
                      Carloni, Paolo and Zhao, Qianqian},
      title        = {{A}n {E}nhanced {S}ampling {A}pproach to the {I}nduced
                      {F}it {D}ocking {P}roblem in {P}rotein-{L}igand {B}inding:
                      the case of mono-{ADP}ribosylationhydrolases inhibitors},
      journal      = {Journal of chemical theory and computation},
      volume       = {17},
      number       = {12},
      issn         = {1549-9618},
      address      = {Washington, DC},
      reportid     = {FZJ-2021-03912},
      pages        = {7899–7911},
      year         = {2021},
      abstract     = {Enhanced sampling methods can predict free-energy
                      landscapes associated with protein/ligand binding,
                      characterizing the involved intermolecular interactions in a
                      precise way. However, these in silico approaches can be
                      challenged by induced-fit effects. Here, we present a
                      variant of volume-based metadynamics tailored to tackle this
                      problem in a general and efficient way. The validity of the
                      approach is established by applying it to substrate/enzyme
                      complexes of pharmacological relevance: mono-ADP-ribose
                      (ADPr) in complex with mono-ADP-ribosylation hydrolases
                      (MacroD1 and MacroD2), where induced-fit phenomena are known
                      to be significant. The calculated binding free energies are
                      consistent with experiments, with an absolute error smaller
                      than 0.5 kcal/mol. Our simulations reveal that in all
                      circumstances, the active loops, delimiting the boundaries
                      of the binding site, undergo significant conformation
                      rearrangements upon ligand binding. The calculations further
                      provide, for the first time, the molecular basis of ADPr
                      specificity and the relative changes in its experimental
                      binding affinity on passing from MacroD1 to MacroD2 and all
                      its mutants. Our study paves the way to the quantitative
                      description of induced-fit events in molecular recognition.},
      cin          = {IAS-5 / INM-9 / JSC},
      ddc          = {610},
      cid          = {I:(DE-Juel1)IAS-5-20120330 / I:(DE-Juel1)INM-9-20140121 /
                      I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511) / 5241 - Molecular
                      Information Processing in Cellular Systems (POF4-524)},
      pid          = {G:(DE-HGF)POF4-5111 / G:(DE-HGF)POF4-5241},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {34813698},
      UT           = {WOS:000752980200045},
      doi          = {10.1021/acs.jctc.1c00649},
      url          = {https://juser.fz-juelich.de/record/901934},
}