Antitargets prediction

Vaz RJ, Klabunde T eds. Antitargets Prediction and Prevention of Drug Side Effects. Wiley-VCH, Weinheim 2008. 

Drug name State The number of predicted antitargets... 

Zakharov AV, Peach ML, Sitzmann M et al (2012) Computational tools and resources for metabolism-related property predictions. 2. Application to prediction of half-life time in human liver microsomes. Future Med Chem 4 1933-1944. doi 10.4155/fmc.l2.152 Zakharov AV, Lagunin AA, Filimonov DA, Poroikov VV (2012) Quantitative prediction of antitarget interaction profiles for chemical compounds. Chem Res Toxicol 25 2378-2385. doi 10.1021/tx300247r... 

The simplest methodology is two-dimensional (2D) quantitative structure-activity relationships (QSAR), in which calculated descriptors of molecules are related to an end point of interest via a mathematical relationship to estimate a numerical or categorical value for that end point. The mathematical relationship is fitted to a training set of compounds for which data for the end point has been measured experimentally. New molecules can then be described with the descriptors used in the model and their end point values predicted. 2D QSAR methods can be used to predict the interaction of compoimds with protein targets or antitargets and are widely used for prediction of physicochemical and ADME properties, such as hpophilicity, solubility, hiunan intestinal absorption, and blood-brain barrier penetration [18]. An excellent review of the strategies and pitfalls of 2D QSAR has been published by Lewis and Wood [19]. 

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