Packmol: a package for building initial configurations for molecular dynamics simulations. Adequate initial configurations for molecular dynamics simulations consist of arrangements of molecules distributed in space in such a way to approximately represent the system’s overall structure. In order that the simulations are not disrupted by large van der Waals repulsive interactions, atoms from different molecules must keep safe pairwise distances. Obtaining such a molecular arrangement can be considered a packing problem: Each type molecule must satisfy spatial constraints related to the geometry of the system, and the distance between atoms of different molecules must be greater than some specified tolerance. We have developed a code able to pack millions of atoms, grouped in arbitrarily complex molecules, inside a variety of three-dimensional regions. The regions may be intersections of spheres, ellipses, cylinders, planes, or boxes. The user must provide only the structure of one molecule of each type and the geometrical constraints that each type of molecule must satisfy. Building complex mixtures, interfaces, solvating biomolecules in water, other solvents, or mixtures of solvents, is straightforward. In addition, different atoms belonging to the same molecule may also be restricted to different spatial regions, in such a way that more ordered molecular arrangements can be built, as micelles, lipid double-layers, etc. The packing time for state-of-the-art molecular dynamics systems varies from a few seconds to a few minutes in a personal computer. The input files are simple and currently compatible with PDB, Tinker, Molden, or Moldy coordinate files. The package is distributed as free software and can be downloaded from∼martinez/packmol/. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009

References in zbMATH (referenced in 12 articles )

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  1. Birgin, E. G.; Gardenghi, J. L.; Martínez, J. M.; Santos, S. A.: On the use of third-order models with fourth-order regularization for unconstrained optimization (2020)
  2. Birgin, E. G.; Lobato, R. D.: A matheuristic approach with nonlinear subproblems for large-scale packing of ellipsoids (2019)
  3. Birgin, E. G.; Haeser, G.; Ramos, Alberto: Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points (2018)
  4. Birgin, E. G.; Lobato, R. D.; Martínez, J. M.: A nonlinear programming model with implicit variables for packing ellipsoids (2017)
  5. Kundalwal, S. I.; Meguid, S. A.: Multiscale modeling of regularly staggered carbon fibers embedded in nano-reinforced composites (2017)
  6. Michael E. Fortunato, Coray M. Colina: pysimm: A python package for simulation of molecular systems (2017) not zbMATH
  7. Vanherpe, Liesbeth; Kanari, Lida; Atenekeng, Guy; Palacios, Juan; Shillcock, Julian: In situ synthesis and simulation of polydisperse amphiphilic membranes (2016)
  8. De Cola, F.; Falco, S.; Barbieri, E.; Petrinic, N.: New 3D geometrical deposition methods for efficient packing of spheres based on tangency (2015)
  9. Martínez, J. M.; Raydan, M.: Separable cubic modeling and a trust-region strategy for unconstrained minimization with impact in global optimization (2015)
  10. Birgin, Ernesto G.; Bustamante, Luis Henrique; Callisaya, Hector Flores; Martínez, Jose Mario: Packing circles within ellipses (2013)
  11. Birgin, Ernesto G.; Fernández, Damián; Martínez, J. M.: The boundedness of penalty parameters in an augmented Lagrangian method with constrained subproblems (2012)
  12. Martínez, L.; Andrade, R.; Birgin, E. G.; Martínez, J. M.: PACKMOL: A package for building initial configurations for molecular dynamics simulations (2009) ioport