Article ID Journal Published Year Pages File Type
444776 Journal of Molecular Graphics and Modelling 2007 17 Pages PDF
Abstract

Genetic algorithms (GA) were used to develop specific technetium metal–ligand force field parameters for the MM3 force field. These parameters were developed using automated procedures within the program FFGenerAtor from a combination of crystallographic structures and ab initio calculations. These new parameters produced results in good agreement with experiment when tested against a blind validation set. To illustrate the utility of these new force field parameters, quantitative structure–activity relationship (QSAR) models were developed to predict the P-glycoprotein uptake (log10 VI) of a series of hexakis(areneisonitrile)technetium(I) complexes and to predict their biodistribution. The log10 VI QSAR model, built using a training set of 16 Tc(I) isonitrile complexes, exhibited a correlation between the experimental log10 VI and 5 simple descriptors as follows: r2 = 0.94, q2 = 0.93. When applied to an external test set of six Tc(I) isonitrile complexes, the QSAR preformed with great accuracy q2 = 0.78 based on a leave-one-out cross-validation analysis. Further QSAR models were developed to predict the biodistribution of the same set of Tc(I) isonitrile complexes; a QSAR model to predict hepatic uptake exhibited a correlation between the experimental log10(Blood/Liver) with six simple descriptors as follows: r2 = 0.97, q2 = 0.96. A QSAR model to predict renal uptake exhibited a correlation between the experimental log10(Blood/Kidney) and six simple descriptors as follows: r2 = 0.85, q2 = 0.82. When applied to the external test set the QSAR models preformed with great accuracy, q2 = 0.78 and 0.56, respectively.

Related Topics
Physical Sciences and Engineering Chemistry Physical and Theoretical Chemistry
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