It takes a query molecule and comparison dataset as inputs, and outputs the aligned molecules with their associated Tanimoto and Tversky scores, including both shape and pharmacophore similarity. In the rest of this note, we refer to pharmacophore similarity as "color" similarity. The optional aligned .sdf file output is compatible with all modern 3D molecular visualization packages. In the following sections, we provide more details for each step described in Figure . Input and Conformer Generation. ROSHAMBO uses RDKit 2023.03 to load and process molecules. Its inputs are a query molecule, which will be used as the reference for the alignment, and a dataset of one or more comparison molecules, which will be aligned to the query. Both query and comparison dataset can be in either .sdf or .smi format, and the dataset file(s) can contain any number of molecules. The user can specify if they wish to generate conformers for the dataset molecules, and, if so, parameters like conformer generation method, number of conformers, and optional force field for minimization. This is done using the EmbedMultipleConfs() method from RDKit. We recommend the most recent ETKDGv3 method followed by an energy minimization using the MMF94s force field. ROSHAMBO's Python API exposes all of RDKit's conformer generation options to aid in user customization.