A Congener-Substitution Strategy for Docking Heavy Metal Protein-Ligand Complexes with AutoDock Vina
Year: 2026
Type: preprint
Abstract: Molecular docking is widely used to predict ligand-protein interactions, but its application to transition metal complexes, particularly those containing second- and third-row elements, remains limited by the lack of explicit metal parameterization in commonly used programs such as AutoDock Vina. Here, we present a simple, practical strategy for docking heavy transition metal complexes without reparameterization: substituting the metal center with its first-row congener (e.g. Ru → Fe; Ir → Co) prior to docking. We applied this approach to a dataset of approximately 60 crystallographically characterized protein-ligand complexes containing Re, Ru, Os, Rh, Ir, Pt and Pd, and then focused on a streptavidin/avidin-biotin validation set of 18 crystallographically characterized protein-ligand complexes (4 Ru, 14 Ir) retrieved from the Protein Data Bank. The experimentally observed binding pose on the full set (rigid docking) was reproduced in 66% of cases, while for the streptavidin/avidin-biotin systems (flexible docking) the crystallography pose was fully or partially reproduced in 60% of cases (3/4 for the Ru systems and 8/14 for the Ir systems). Despite this outcome heterogeneity, the coordination geometry of the metal center and the broader protein-ligand interaction fingerprint were well preserved across the docked complexes, with a smaller perturbation observed for the Ru/Fe pair than for the Ir/Co pair, consistent with the higher pose-recovery rate obtained for the Ru systems. Overall, these results indicate that congener substitution offers a rapid, accessible route to docking second- and third-row transition metal complexes with unmodified AutoDock Vina, particularly in rigid docking, while revealing possible metal- and system-dependent limitations that should be considered when extending the strategy to other systems.
Source: ChemRxiv
Institutions: University of Fribourg, University of Padua
Language: English
Subfield: Drug Discovery
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7214356825