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Au(III) is highly reactive. At odds with its reduced counterpart, Au(I), it is hardly present in structural databases. And yet, it is the starting reactant to form gold nanoclusters (AuNCs) and the constitutive component of a new class of drugs. Its reactivity is a world apart from that of the iso-electronic Pt(II) species. Rather than DNA, it targets proteins. Its interaction with amino acid residues is manifold. It can strongly interact with the residue backbones, amino acid side chains and protein ends, it can form appropriate complexes whose stabilization energy reaches up to more than 40 kcal mol -1 , it can affect the p K of amino acid residues, and it can promote charge transfer from the residues to the amount that it is reduced. Here, quantum chemical calculations provide quantitative information on all the processes where Au(III) can be involved. A myriad of structural arrangements are examined in order to determine the strongest interactions and quantify the amount of charge transfer between protonated and deprotonated residues and Au(III). The calculated interaction energies of the amino acid side chains with Au(III) quantitatively reproduce the experimental tendency of Au(III) to interact with selenocysteine, cysteine and histidine and negatively charged amino acids such as Glu and Asp. Also, aromatic residues such as tyrosine and tryptophan strongly interact with Au(III). In proteins, basic pH plays a role in the deprotonation of cysteine, lysine and tyrosine and strongly increases the binding affinity of Au(III) toward these amino acids. The amino acid residues in the protein can also trigger the reduction of Au(III) ions. Sulfur-containing amino acids (cysteine and methionine) and selenocysteine provide almost one electron to Au(III) upon binding. Tyrosine also shows a considerable tendency to act as a reductant. Other amino acids, commonly identified in Au-protein adducts, such as Ser, Trp, Thr, Gln, Glu, Asn, Asp, Lys, Arg and His, possess a notable reducing power toward Au(III). These results and their discussion form a vade mecum that can find application in medicinal chemistry and nanotech applications of Au(III).a of amino acid residues, and it can promote charge transfer from the residues to the amount that it is reduced. Here, quantum chemical calculations provide quantitative information on all the processes where Au(III) can be involved. A myriad of structural arrangements are examined in order to determine the strongest interactions and quantify the amount of charge transfer between protonated and deprotonated residues and Au(III). The calculated interaction energies of the amino acid side chains with Au(III) quantitatively reproduce the experimental tendency of Au(III) to interact with selenocysteine, cysteine and histidine and negatively charged amino acids such as Glu and Asp. Also, aromatic residues such as tyrosine and tryptophan strongly interact with Au(III). In proteins, basic pH plays a role in the deprotonation of cysteine, lysine and tyrosine and strongly increases the binding affinity of Au(III) toward these amino acids. The amino acid residues in the protein can also trigger the reduction of Au(III) ions. Sulfur-containing amino acids (cysteine and methionine) and selenocysteine provide almost one electron to Au(III) upon binding. Tyrosine also shows a considerable tendency to act as a reductant. Other amino acids, commonly identified in Au-protein adducts, such as Ser, Trp, Thr, Gln, Glu, Asn, Asp, Lys, Arg and His, possess a notable reducing power toward Au(III). These results and their discussion form a vade mecum that can find application in medicinal chemistry and nanotech applications of Au(III).

Molecular dynamics simulations were used to quantitatively investigate the interactions between the twenty proteinogenic amino acids and C 60 . The conserved amino acid backbone gave a constant energetic interaction ~5.4 kcal mol -1 , while the contribution to the binding due to the amino acid side chains was found to be up to ~5 kcal mol -1 for tryptophan but lower, to a point where it was slightly destabilizing, for glutamic acid. The effects of the interplay between van der Waals, hydrophobic, and polar solvation interactions on the various aspects of the binding of the amino acids, which were grouped as aromatic, charged, polar and hydrophobic, are discussed. Although π-π interactions were dominant, surfactant-like and hydrophobic effects were also observed. In the molecular dynamics simulations, the interacting residues displayed a tendency to visit configurations (i.e., regions of the Ramachandran plot) that were absent when C 60 was not present. The amino acid backbone assumed a "tepee-like" geometrical structure to maximize interactions with the fullerene cage. Well-defined conformations of the most interactive amino acids (Trp, Arg, Met) side chains were identified upon C 60 binding.