AI-Driven Prediction and Evaluation of Medicinal Properties of Metal–Heterocyclic Complexes

The This review discusses how Artificial Intelligence (AI) is helping scientists develop new metalheterocyclic drugs more efficiently and accurately. Artificial Intelligence can predict biological activity, optimize molecular design, and evaluate the safety of drug candidates for human use. It plays an important role in the development of platinum, ruthenium, gold, and silver complexes with anticancer, antibacterial, and other therapeutic activities. Some compounds, such as Platin AI and gold–N-heterocyclic carbene (NHC) complexes, show high selectivity toward cancer cells while minimizing damage to healthy tissues. Artificial Intelligence also assists in identifying optimal metal centers, ligand structures, and metal–ligand combinations for enhanced efficacy and reduced toxicity. Overall, Artificial Intelligence simplifies, accelerates, and reduces the cost of discovering new metal-based drugs for future medical applications.