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.

Key Features

• 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.

Website: www.ks.uiuc.edu/Research/namd
Support:
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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