Mining for Context-Sensitive Bioisosteric Replacements in Large Chemical Databases

Mining for Context-Sensitive Bioisosteric Replacements in Large Chemical Databases 

George Papadatos, Michael J. Bodkin, Valerie J. Cillet, and Peter Willett 

BioisosUres in MeMcinal ChanKtry, First Fdition. Edited by Nathan Brown 

that result from the application of particular transformations, AS, and hence provide an inverse quantitative structure-activity relationship (QSAR) approach to lead optimization [19]. Another difference is that, given an appropriate source of data, they can model not only biological activity, the principal focus of the bioisosterism approaches, but also any chemical, physicochemical, or ADMETproperty that needs to be optimized. 

This chapter follows the large-scale MMP analysis paradigm and studies the relationship between molecular transformations and the resulting changes in experimental property, particularly human liver microsomal metabolic stability. More specifically, the ultimate aim has been the identification of metabolic stability isosteres, that is, transformations and replacements with zero or positive effect on metabolic stability. Furthermore, in line with the recent study of Papadatos et al. [18], the possibility of context-dependent isosteric replacements is explored. 

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I 6 Mining for Context-Sensitive Bioisosteric Replacement in Large Chemical Databases -NH2 -0H... 

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