Computational Studies of Au(I) and Au(III) Anticancer MetalLodrugs: A Survey

Abstract

Owing to the growing hardware capabilities and the enhancing efficacy of computational methodologies, computational chemistry approaches have constantly become more important in the development of novel anticancer metallodrugs. Besides traditional Pt-based drugs, inorganic and organometallic complexes of other transition metals are showing increasing potential in the treatment of cancer. Among them, Au(I)- and Au(III)-based compounds are promising candidates due to the strong affinity of Au(I) cations to cysteine and selenocysteine side chains of the protein residues and to Au(III) complexes being more labile and prone to the reduction to either Au(I) or Au(0) in the physiological milieu. A correct prediction of metal complexes’ properties and of their bonding interactions with potential ligands requires QM computations, usually at the ab initio or DFT level. However, MM, MD, and docking approaches can also give useful information on their binding site on large biomolecular targets, such as proteins or DNA, provided a careful parametrization of the metal force field is employed. In this review, we provide an overview of the recent computational studies of Au(I) and Au(III) antitumor compounds and of their interactions with biomolecular targets, such as sulfur- and selenium-containing enzymes, like glutathione reductases, glutathione peroxidase, glutathione-S-transferase, cysteine protease, thioredoxin reductase and poly (ADP-ribose) polymerase 1.