ELF: An Extended-Lagrangian Free Energy Calculation Module for Multiple Molecular Dynamics Engines

Extended adaptive biasing force (eABF),
a collective variable (CV)-based
importance-sampling algorithm, has proven to be very robust and efficient
compared with the original ABF algorithm. Its implementation in Colvars,
a software addition to molecular dynamics (MD) engines, is, however,
currently limited to NAMD and LAMMPS. To broaden the scope of eABF
and its variants, like its generalized form (egABF), and make them
available to other MD engines, e.g., GROMACS, AMBER, CP2K, and openMM,
we present a PLUMED-based implementation, called extended-Lagrangian
free energy calculation (ELF). This implementation can be used as
a stand-alone gradient estimator for other CV-based sampling algorithms,
such as temperature-accelerated MD (TAMD) and extended-Lagrangian
metadynamics (MtD). ELF provides the end user with a convenient framework
to help select the best-suited importance-sampling algorithm for a
given application without any commitment to a particular MD engine.