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@ARTICLE{Briones:859267,
      author       = {Briones, Rodolfo and Blau, Christian and Kutzner, Carsten
                      and de Groot, Bert L. and Aponte-Santamaría, Camilo},
      title        = {{GRO}maρs: {A} {GROMACS}-{B}ased {T}oolset to {A}nalyze
                      {D}ensity {M}aps {D}erived from {M}olecular {D}ynamics
                      {S}imulations},
      journal      = {Biophysical journal},
      volume       = {116},
      number       = {1},
      issn         = {0006-3495},
      address      = {Bethesda, Md.},
      publisher    = {Soc.},
      reportid     = {FZJ-2019-00141},
      pages        = {4 - 11},
      year         = {2019},
      abstract     = {We introduce a computational toolset, named GROmaρs, to
                      obtain and compare time-averaged density maps from molecular
                      dynamics simulations. GROmaρs efficiently computes density
                      maps by fast multi-Gaussian spreading of atomic densities
                      onto a three-dimensional grid. It complements existing
                      map-based tools by enabling spatial inspection of atomic
                      average localization during the simulations. Most
                      importantly, it allows the comparison between computed and
                      reference maps (e.g., experimental) through calculation of
                      difference maps and local and time-resolved global
                      correlation. These comparison operations proved useful to
                      quantitatively contrast perturbed and control simulation
                      data sets and to examine how much biomolecular systems
                      resemble both synthetic and experimental density maps. This
                      was especially advantageous for multimolecule systems in
                      which standard comparisons like RMSDs are difficult to
                      compute. In addition, GROmaρs incorporates absolute and
                      relative spatial free-energy estimates to provide an
                      energetic picture of atomistic localization. This is an
                      open-source GROMACS-based toolset, thus allowing for static
                      or dynamic selection of atoms or even coarse-grained beads
                      for the density calculation. Furthermore, masking of regions
                      was implemented to speed up calculations and to facilitate
                      the comparison with experimental maps. Beyond map
                      comparison, GROmaρs provides a straightforward method to
                      detect solvent cavities and average charge distribution in
                      biomolecular systems. We employed all these functionalities
                      to inspect the localization of lipid and water molecules in
                      aquaporin systems, the binding of cholesterol to the G
                      protein coupled chemokine receptor type 4, and the
                      identification of permeation pathways through the dermicidin
                      antimicrobial channel. Based on these examples, we
                      anticipate a high applicability of GROmaρs for the analysis
                      of molecular dynamics simulations and their comparison with
                      experimentally determined densities.},
      cin          = {ICS-4},
      ddc          = {570},
      cid          = {I:(DE-Juel1)ICS-4-20110106},
      pnm          = {552 - Engineering Cell Function (POF3-552)},
      pid          = {G:(DE-HGF)POF3-552},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:30558883},
      UT           = {WOS:000455089100003},
      doi          = {10.1016/j.bpj.2018.11.3126},
      url          = {https://juser.fz-juelich.de/record/859267},
}