Dual Biomolecule Recognition by Diruthenium Paddlewheel Complexes: A Combined Computational Thermodynamics and Bioinformatic Structural Analysis

The development of novel metallodrugs is an important direction to address the limitations of conventional therapeutics. In this study, we investigated the dual biomolecule recognition capabilities of diruthenium paddlewheel complexes, a promising class of anticancer agents. We integrated two complementary approaches: density functional theory (DFT) calculations and bioinformatic structural analysis. Our DFT calculations characterized the thermodynamic feasibility of axial ligand substitution by key protein nucleophiles, namely cysteine (Cys), histidine (His), and adenine, while also probing the resulting structural motifs, including the effect on the ruthenium-ruthenium (Ru─Ru) bond distance. This analysis revealed the energetic spontaneity of complex formation with these nucleophiles and, notably, a nuanced flexibility of the Ru─Ru core that accommodates diverse ligand combinations. Subsequently, the computationally derived geometric assets were utilized to perform a comprehensive motif search within the Protein Data Bank (PDB) database. The PDB screening successfully identified the presence of these motifs, particularly Cys-His, Cys-Cys, and His-His, within numerous protein structures, including several clinically relevant targets. This work confirms the potential of the diruthenium paddlewheel complex as a multitargeting agent and establishes a robust, integrated methodology for the rational design and prevalidation of such metallodrugs by bridging atomic-level theoretical understanding with real-world biological structural data.