Evaluating Ligand Similarity in Databases

The similarity degree of the ligands reported in the curated ChEMBL and DrugBank datasets were evaluated as follows. First, an all-against-all 2D-fingerprint-based similarity assessment was performed by using an in-house-developed Python script. The degree of 2D similarity was calculated according to the MACCS and circular (i.e., ECFP4) type of fingerprints available on OpenEye Python toolkits [194 ], and by using the Tanimoto coefficient (Tc) as an index for ligands similarity measurement. Then, the results of the 2D similarity calculations were filtered to retain only those with MACCS and ECFP4 Tanimoto coefficients equal to or higher than 0.8 and 0.3, respectively, in agreement with previously reported studies [196 (link)]. Afterward, extensive 3D shape and atom type similarity calculations of compounds resulting as significantly similar in the 2D estimations were performed by using the ROCS software [117 ]. In this case, the similarity degree between ligands was assessed according to the Tanimoto Combo (TCc) coefficient [117 ]. Finally, the results of the 3D-shape-based similarity calculations were filtered to retain only similarity records with a TCc ≥ 1.5, which is a commonly accepted threshold of similarity [196 (link)].