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.
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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