Advanced techniques in molecular docking of inorganic complexes for understanding biological relationships

Abstract

The use of molecular docking in structure-based drug design is an indispensable tool in the field of computational chemistry; however, the application of molecular docking to metal complexes (such as Pt, Pd, Au, and Ag) poses unique challenges because of the variety of coordination geometries and electronic properties of metal complexes that are not represented by the typical force field. The literature (2010–2025) was reviewed and summarized in a peer-reviewed manner, concentrating on the application of inorganic complexes in the field of anticancer. The 13 representative case studies were identified by a systematic search of PubMed, Scopus and Web of Science and analysed for binding energies, RMSD values, software protocols and metal-specific parameterisation strategies. Majority of the studies used AutoDock4, AutoDock Vina or MOE with binding energies ranging from − 96.35 to − 1.48 kcal·mol⁻¹. Only three studies reported RMSD values < 2.0 Å, which is considered to be reliable pose prediction. The major drawbacks are: (i) absence of built-in metal coordination bond support in standard software; (ii) reporting of grid parameters and force field versions varies from one software to another; and (iii) very little quantum mechanical pre-optimization. Specialized tools (MetalDock, MCPB.py) increase accuracy, but are very time consuming to parameterise manually. Parameterisation, experimental validation (XRD, NMR, bioassays) and transparency of reporting are essential for reliable docking of metal complexes. Machine learning scoring functions are expected to be combined with quantum mechanical methods in the future. This review offers a practical guide and a warning for researchers who are designing metallodrugs by using docking.