Quantitative structure-activity relationships global models

More recently (2006) we performed and reported quantitative structure-activity relationship (QSAR) modeling of the same compounds based on their atomic linear indices, for finding fimctions that discriminate between the tyrosinase inhibitor compounds and inactive ones [50]. Discriminant models have been applied and globally good classifications of 93.51 and 92.46% were observed for nonstochastic and stochastic hnear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67 and 89.44% [50]. In addition to this, these fitted models have also been employed in the screening of new cycloartane compounds isolated from herbal plants. Good behavior was observed between the theoretical and experimental results. These results provide a tool that can be used in the identification of new tyrosinase inhibitor compounds [50]. 

Abstract Quantitative structure-activity relationship (QSAR) models are generated for biological activity and toxicity in terms of global and local reactivity descriptors within a conceptual density functional theory framework. Possible anticancer activity of two new metal-borane clusters is analyzed. 

Yuan, H., Wang, Y, Cheng, Y. Local and global quantitative structure-activity relationship modeling and prediction for the baseline toxicity. J. Chem. Inf. Model. 2007, 47, 159-169. 

Helgee EA, Carlsson L, Boyer S, et al. Evaluation of quantitative structure-activity relationship modeling strategies Local and global models. J Chem Inf Model 2010 50 677-689. 

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