Evaluation of DFT methods for predicting geometries and NMR spectra of Bi(III) dithiocarbamate complexes with antitumor properties

Context: Bismuth complexes with dithiocarbamate ligands have attracted attention because of their biological applications, such as antimicrobial, antileishmanial, and anticancer properties. These complexes have high cytotoxic activity against cancer cells, being more active than the standard drugs cisplatin, doxorubicin, and tamoxifen. In the present study, we investigated the ability of some DFT methods to reproduce the geometries and NMR spectra of the Bi(III) dithiocarbamate complexes, selected based on their proven antitumor activity. Our investigation revealed that the M06-L/def2-TZVP/ECP/CPCM method presented good accuracy in predicting geometries, while the TPSSh/def2-SVP/ECP/CPCM method proved effective in analyzing the ¹³C NMR spectra of these molecules. In general, all examined methods exhibited comparable performance in predicting ¹H NMR signals.

Methods: Calculations were performed with the Gaussian 09 program using the def2-SVP and def2-TZVP basis sets, employing relativistic effective core potential (ECP) for Bi and using the CPCM solvent model. The exchange-correlation functionals BP86, PBE, OLYP, M06-L, B3LYP, B3LYP-D3, M06-2X, TPSSh, CAM-B3LYP, and ωB97XD were used in the study. Geometry optimizations were started from crystallographic structures available at the Cambridge Structural Database. The theoretical results were compared with experimental data using the mean root-mean-square deviation (RMSD), mean absolute deviations (MAD), and linear correlation coefficient (R²).