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NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems.

NAMD is written using the Charm++ parallel programming model, noted for its parallel efficiency and often used to simulate large systems (millions of atoms). NAMD is implemented using the Converse runtime system. Converse provides machine-independent interface to all popular parallel computers as well as workstation clusters.

 NAMD 2.11

Free to download


Non-Exclusive, Non-Commercial Use License

Theoretical and Computational Biophysics Group (TCB) and the Parallel Programming Laboratory (PPL)


System Requirements
Charm++ 6.0 or higher
TCL and FFTW libraries
VMD plugins

Parallel Programming Laboratory, User Guide, Wiki, Tutorials, Mailing List

Selected Reviews:

Features include:

  • VMD used to prepare molecular structure for simulation
  • Also reads X-PLOR, CHARMM, AMBER, and GROMACS input files
  • Psfgen tool generates structure and coordinate files for CHARMM force field
  • Efficient conjugate gradient minimization
  • Fixed atoms and harmonic restraints
  • Thermal equilibration via periodic rescaling, reinitialization, or Langevin dynamics
  • Force Field Compatibility
  • Efficient Full Electrostatics Algorithms
  • Multiple Time Stepping
  • Input and Output Compatibility
  • Dynamics Simulation Options - MD simulations using options such as:
    • Constant energy dynamics
    • Constant temperature dynamics via:
      • Velocity rescaling
      • Velocity reassignment
      • Langevin dynamics
    • Periodic boundary conditions
    • Constant pressure dynamics via
      • Berendsen pressure coupling
      • Nosť-Hoover Langevin piston
    • Energy minimization
    • Fixed atoms
    • Rigid waters
    • Rigid bonds to hydrogen
    • Harmonic restraints
    • Spherical or cylindrical boundary restraints
  • Interactive molecular dynamics simulations
  • Accelerated molecular dynamics provides a robust biasing potential that increases the escape rates from potential wells, while still converging to the correct canonical distribution.
  • Load balancing
  • Shared-Memory Multicore and SMP Builds
  • Replica-based umbrella sampling via collective variables module
  • Optimized shared-memory single-node and multiple-node CUDA builds
  • CUDA GPU-accelerated generalized Born implicit solvent (GBIS) model
  • CUDA GPU-accelerated energy evaluation and minimization
  • Native CRAY XE/XK uGNI network layer implementation
  • Faster grid forces and lower-accuracy "lite" implementation
  • Hybrid MD with knowledge-based Go forces to drive folding
  • Linear combination of pairwise overlaps (LCPO) SASA for GBIS model
  • Weeks-Chandler-Anderson decomposition for alchemical FEP simulations
  • Native replica-exchange implementation for CRAY XE/XK and BlueGene/Q

NAMD in action

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Last Updated Monday, May 25 2015 @ 12:25 PM EDT

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