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Computational modeling was applied to far-infrared (FIR) spectra of Pt-based anticancer drugs to study the hydrolysis of these important molecules. Here, we present a study that investigates the influence of different factors-basis sets on non-Pt atoms, relativistic effective core potentials (RECPs) on the Pt atom, density functional theory (DFT) functionals, and solvation models-on the prediction of FIR spectra of two Pt-based anticancer drugs, cisplatin and carboplatin. Geometry optimizations and frequency calculations were performed with a range of functionals (PBE, PBE0, M06-L, and M06-2X), Dunning's correlation-consisted basis sets (VDZ, VTZ, aVDZ, and aVTZ), RECPs (VDZ-pp, VTZ-pp, aVDZ-pp, and aVTZ-pp), and solvation models (IEFPCM, CPCM, and SMD). The best combination of the basis set/DFT functional/solvation model was identified for each anticancer drug by comparing with experimentally available FIR spectra. Different combinations were established for cisplatin and carboplatin, which was rationalized by means of the partial atomic charge scheme, ChelpG, that was utilized to study the charge transfer between the Pt ion and ligands in both cisplatin and carboplatin.

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Influence of DFT Functionals and Solvation Models on the Prediction of Far-Infrared Spectra of Pt-Based Anticancer Drugs: Why Do Different Complexes Require Different Levels of Theory?