  We aim to automatize the identification of collective variables to simplify
and speed up enhanced sampling simulations of conformational dynamics in
biomolecules. We focus on anharmonic low-frequency vibrations that exhibit
fluctuations on timescales faster than conformational transitions but describe
a path of least resistance towards structural change. A key challenge is that
harmonic approximations are ill-suited to characterize these vibrations, which
are observed at far-infrared frequencies and are easily excited by thermal
collisions at room temperature.
  Here, we approached this problem with a frequency-selective anharmonic
(FRESEAN) mode analysis that does not rely on harmonic approximations and
successfully isolates anharmonic low-frequency vibrations from short molecular
dynamics simulation trajectories. We applied FRESEAN mode analysis to
simulations of alanine dipeptide, a common test system for enhanced sampling
simulation protocols, and compare the performance of isolated low-frequency
vibrations to conventional user-defined collective variables (here backbone
dihedral angles) in enhanced sampling simulations.
  The comparison shows that enhanced sampling along anharmonic low-frequency
vibrations not only reproduces known conformational dynamics but can even
further improve sampling of slow transitions compared to user-defined
collective variables. Notably, free energy surfaces spanned by low-frequency
anharmonic vibrational modes exhibit lower barriers associated with
conformational transitions relative to representations in backbone dihedral
space. We thus conclude that anharmonic low-frequency vibrations provide a
promising path for highly effective and fully automated enhanced sampling
simulations of conformational dynamics in biomolecules.
