When cleaning the data, we found errors in the structural assignments of the original ChemDraw files, as well as in our original conversion from ChemDraw to SMILES. One of the most common errors were misassigned sidechains. Given the dataset's size (558 data points with 143 unique donors and 261 unique acceptors), we implemented a semi-automated cleaning procedure. Structures with multiple unique labels were identified automatically. Tanimoto similarities were calculated for each pair of unique donor or acceptor labels. When the Tanimoto similarity was unity, we reviewed the structures manually. Most often, the same molecular structure was labeled with different namesa common issue in the literature. In those cases, we selected a principal label and replaced all occurrences with that label. Incorrect structures or incorrect sidechain assignments had to be verified manually because no suitable automated solution was identified. For this, we wrote a script to iterate through each unique SMILES, display the structure, check it against the structure in the associated paper (by DOI), and apply corrections if necessary.