MetAP DB and Metal-FP: a database and fingerprint framework for advancing metal-based drug discovery

Metal-based drugs have historically been used for different therapeutic and diagnostic applications. The need to advance metal-based drugs and drug candidates has contributed to the development of computational strategies to handle metal-containing chemical structures for drug discovery applications. However, most of them have limitations related to their computational cost, scalability, capacity to be used in different chemical contexts, and data accessibility. This study introduces the first open-access metal-based approved drug database (MetAP DB) with FDA-approved drugs across various therapeutic applications and clinical diagnostic outcomes. It also introduces the first versions of molecular metal-based fingerprints (Metal-FP) representations proposed as a general protocol for representing metal-based compounds. The proposed fingerprints encode chemical data related to the presence of metals, their valence and oxidation states, the presence of specific functional groups, and the atom connectivity of metal-based compounds. The fingerprints Metal-FP2 and Metal-FP3 showed highlighting the effectiveness in differentiating metal-based compounds according to distance metrics, data visualizations, random forest, and logistic regression algorithms.