Tetra­chlorido(2,3-di-2-pyridylpyrazine-κ2 N 1,N 2)platinum(IV)

In the title complex, [PtCl4(C14H10N4)], the PtIV atom is six-coordinated in an octa­hedral configuration by two N atoms from one 2,3-di-2-pyridylpyrazine ligand and four terminal Cl atoms. Inter­molecular C—H⋯Cl and C—H⋯N hydrogen bonds stabilize the crystal structure

cis-Tetra­chloridobis(1H-imidazole-κN 3)platinum(IV)

In the title complex, cis-[PtCl4(C3H4N2)2], the PtIV ion lies on a twofold rotation axis and is coordinated in a slightly distorted octa­hedral geometry. The dihedral angle between the imidazole rings is 69.9 (2)°. In the crystal, mol­ecules are linked by N—H⋯Cl hydrogen bonds, forming a three-dimensional network

Calculation of lipophilicity for Pt(II) complexes: Experimental comparison of several methods.

Platinum containing compounds are promising antitumor agents, but must enter cells before reaching their main biological target, namely DNA. Their distribution within the body, and hence their activity is to a large extent determined by their lipophilicity, thus there is a strong interest to develop computational methods to predict this important property. This study analyses accuracy of five methods, namely ALOGPS, KOWWIN, CLOGP and two quantum chemical approaches, to predict octanol/water partition coefficients (logP) for sets of 43 and 12 Pt(II) complexes, collected from the literature and measured by the authors, respectively. All methods gave generally poor results with mean absolute error (MAE) of between 0.8 and 3 log units for prediction of new compounds. Extension of the ALOGPS program with data from the literature set resulted in the best prediction ability, MAE=0.46, for the measured molecules. The program was also able to correctly predict errors in calculated logP values. It is freely available for interactive use at http://www.vcclab.org

Calculation of lipophilicity for Pt(II) complexes: Experimental comparison of several methods

Platinum containing compounds are promising antitumor agents, but must enter cells before reaching their main biological target, namely DNA. Their distribution within the body, and hence their activity is to a large extent determined by their lipophilicity, thus there is a strong interest to develop computational methods to predict this important property. This study analyses accuracy of five methods, namely ALOGPS, KOWWIN, CLOGP and two quantum chemical approaches, to predict octanol/water partition coefficients (log P) for sets of 43 and 12 Pt(II) complexes, collected from the literature and measured by the authors, respectively. All methods gave generally poor results with mean absolute error (MAE) of between 0.8 and 3 log units for prediction of new compounds. Extension of the ALOGPS program with data from the literature set resulted in the best prediction ability, MAE = 0.46, for the measured molecules. The program was also able to correctly predict errors in calculated log P values. It is freely available for interactive use at http://www.vcclab.org

Chemistry Central Journal Poster presentation Calculation of lipophilicity for Pt(II) complexes: experimental comparison of several methods

© 2008 Tetko et al. Platinum containing compounds are promising antitumor agents, but must enter cells before reaching their main biological target, namely DNA. Their distribution within the body, and hence their activity is to a large extent determined by their lipophilicity, thus there is a strong interest to develop computational methods to predict this important property. This study analyses accuracy of five methods, namely ALOGPS [1], KOWWIN [2], CLOGP [3] and two quantum chemical approaches [4,5], to predict octanol/water partition coefficients (logP) for sets of 43 and 12 Pt(II) complexes, collected from the literature and measured by the authors, respectively. Fragment-based methods for logP estimation give generally poor results due to lack of suitable values for metal-containing fragments. However, the ALOGPS program can be extended with data from the first set in LIBRARY mode [6,7], and in this way resulted in the highest prediction ability for the measured molecules. The program was also able to correctly predict errors in calculated logP values for new molecules using the algorithm described in [8]