Abstract：
BACKGROUND: 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).
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).
摘要：
背景：具有二硫代氨基甲酸酯配体的铋配合物因其生物学应用而受到关注，如抗菌剂，Antileishmanial,和抗癌特性。这些复合物对癌细胞具有很高的细胞毒活性，比标准药物顺铂更活跃，阿霉素,还有他莫昔芬.在本研究中,我们研究了一些DFT方法重现Bi（III）二硫代氨基甲酸酯配合物的几何形状和NMR光谱的能力，根据其已证明的抗肿瘤活性进行选择。我们的调查表明，M06-L/def2-TZVP/ECP/CPCM方法在预测几何形状方面具有良好的准确性，而TPSSh/def2-SVP/ECP/CPCM方法在分析这些分子的13CNMR光谱方面被证明是有效的。总的来说,所有检查的方法在预测1HNMR信号方面均表现出可比的性能。
方法：用高斯09程序使用def2-SVP和def2-TZVP基集进行计算，对Bi采用相对论有效核心势(ECP)，并使用CPCM溶剂模型。交换相关函数BP86，PBE，OLYP,M06-L,B3LYP,B3LYP-D3,M06-2X,TPSSh,CAM-B3LYP,和ωB97XD用于研究。几何优化是从剑桥结构数据库中提供的晶体结构开始的。使用均方根偏差（RMSD）将理论结果与实验数据进行比较，平均绝对偏差(MAD)，和线性相关系数(R2)。
方法：用高斯09程序使用def2-SVP和def2-TZVP基集进行计算，对Bi采用相对论有效核心势(ECP)，并使用CPCM溶剂模型。交换相关函数BP86，PBE，OLYP,M06-L,B3LYP,B3LYP-D3,M06-2X,TPSSh,CAM-B3LYP,和ωB97XD用于研究。几何优化是从剑桥结构数据库中提供的晶体结构开始的。使用均方根偏差（RMSD）将理论结果与实验数据进行比较，平均绝对偏差(MAD)，和线性相关系数(R2)。
