NAMD – high-performance simulation of large biomolecular systems

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.

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.
      • Nosé-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.

Developer: Theoretical and Computational Biophysics Group (TCB) and the Parallel Programming Laboratory (PPL)
License: Non-Exclusive, Non-Commercial Use License


NAMD is written in C++. Learn C++ with our recommended free books and free tutorials.

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