As we discuss above, most programs for conformer generation employ DG to explore the conformational space with the assumption that by constraining lower and upper distance bounds between all pairs of atoms, all possible conformers can be covered. Some empirical information, such as bond length, bond angles and torsion angles may also be added to the distance bounds matrix for better sampling. Nonetheless, the generated structures via this algorithm still can have distorted geometry and torsional angle values beyond the experimental range because within the distance constraints, atomic coordinates are randomly generated. Therefore, error checking or geometry filtration is essential to ensure high-quality conformations. In contrast, CREST utilizes a RMSD based bias potential to run meta-dynamics for its conformer search. The extra potential drives the structure far away from previously visited geometries, allowing for a wide screening of the PES. To ensure the lowest energy conformer is searched, all generated conformations are optimized and energetically sorted, and the meta-dynamics simulations are run multiple times until no lower conformer is found. While CREST can provide reasonable chemical structures, its computational cost is far more expensive than the DG-based methods.