We evaluated the performance of our method on the Platinum dataset, including 4,548 organic ligands from the Protein Data Bank . For testing, we used 4,432 fragments from the Open Crystallographic Database (COD) to avoid overlap of "training" and test sets. If fragments were drawn from test set molecules, RMSD and other geometric errors would reduce unfairly as fragments know the "answer" of the prediction. For comparison, we considered the most recent release of Open Babel (v. 2.4.1), RDKit (Release 2018.09.1) with the ETKDG method and this new implementation. Each molecule was supplied to the programs as the corresponding SMILES string.