Freely Available Conformer Generation Methods: How Good Are They?

Conformer generation has important implications in cheminformatics,
particularly in computational drug discovery where the quality of
conformer generation software may affect the outcome of a virtual
screening exercise. We examine the performance of four freely available
small molecule conformer generation tools (Balloon, Confab, Frog2, and RDKit) alongside a commercial
tool (MOE). The aim of this study is 3-fold: (i) to identify which
tools most accurately reproduce experimentally determined structures;
(ii) to examine the diversity of the generated conformational set;
and (iii) to benchmark the computational time expended. These aspects
were tested using a set of 708 drug-like molecules assembled from
the OMEGA validation set and the Astex Diverse Set. These molecules
have varying physicochemical properties and at least one known X-ray
crystal structure. We found that RDKit and Confab are statistically better than other methods at generating low rmsd
conformers to the known structure. RDKit is particularly
suited for less flexible molecules while Confab, with its
systematic approach, is able to generate conformers which are geometrically
closer to the experimentally determined structure for molecules with
a large number of rotatable bonds (≥10). In our tests RDKit also resulted as the second fastest method after Frog2. In order to enhance the performance of RDKit, we developed
a postprocessing algorithm to build a diverse and representative set
of conformers which also contains a close conformer to the known structure.
Our analysis indicates that, with postprocessing, RDKit is
a valid free alternative to commercial, proprietary software.