evaluations over multiple cores. The timing difference between cis and trans GPGG originates from the longer initialization of a complete cis population that has the ten- All in all, in the case of AMOEBA, the pools of low-energy candidate structures for GPGG and gramicidin were sampled in respectively 2.5 and 7 hours on a single workstation for 10 serial GA runs, without monitoring or restart procedures, in contrast to the previously employed B3LYP/6-31G SA search for GPGG that took several days with multiple runs, with different heating temperatures and annealing rates and a post-processing analysis of trajectories to extract promising candidates. Such an ab initio exploration is simply out of reach for gramicidin and only SA based on classical force fields employing additional experimentally observed constraints could provide the GM. Regardless of the search approach employed, a final ab initio refinement with large basis set is necessary for calculating properties, e.g. reliably assigning IR frequencies to experimental spectra. DFT re-optimizations and (harmonic) vibrational analyses are far more demanding than the GA searches themselves; in fact, they required 6 days on two workstations for all AMOEBA/GAFF GPGG LM (276 structures) while 4 days on 8 16-core compute nodes were needed for the AMOEBA gramicidin (48 structures). However, similar to the previous SA searches, experimental information like ion mobility cross-sections 1 or symmetry constraints derived from typical vibrational fingerprints 30 can be used as additional pre-filter for GA applications, to further narrow down the pool of candidate geometries instead of retaining all structures within a given energy range. This would drastically reduce the computational demand when treating larger systems.