The profile of shapes presented by a cyclic peptide modulates
its
therapeutic efficacy and is represented by the ensemble of its sampled
conformations. Although some algorithms excel at creating a diverse
ensemble of cyclic peptide conformations, they seldom address the
entropic contribution of flexible conformations and often have significant
practical difficulty producing an ensemble with converged and reliable
thermodynamic properties. In this study, an accelerated molecular
dynamics (MD) method, namely, reservoir replica exchange MD (R-REMD
or Res-REMD), was implemented in GROMACS ver. 4.6.7 and benchmarked
on two small cyclic peptide model systems: a cyclized furin cleavage
site of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
spike (cyclo-(CGPRRARSG)) and oxytocin (disulfide-bonded CYIQNCPLG).
Additionally, we also benchmarked Res-REMD on alanine dipeptide and
Trpzip2 to demonstrate its validity and efficiency over REMD. For
Trpzip2, Res-REMD coupled with an umbrella-sampling-derived reservoir
generated similar folded fractions as regular REMD but on a much faster
time scale. For cyclic peptides, Res-REMD appeared to be marginally
faster than REMD in ensemble generation. Finally, Res-REMD was more
effective in sampling rare events such as trans to cis peptide bond
isomerization. We provide a GitHub page with the modified GROMACS
source code for running Res-REMD at .