IMPORTANCE OF THE FIELD The past decade had witnessed remarkable advances in computer science which had given rise to many new possibilities including the ability to simulate and model life's phenomena. Among one of the greatest gifts computer science had contributed to drug discovery is the ability to predict the biological activity of compounds and in doing so drives new prospects and possibi...

Quantitative structure pharmacokinetic relationship (QSPKR) modeling can be used to predict the biliary clearance and percentage of dose eliminated in bile (PDb) in humans before clinical studies. Recently, a QSPKR model based on in-house compounds was derived using simple physicochemical descriptors to predict the PDb in rats (Drug Metab Dispos 38:422–430, 2010). Our objective was to evaluate ...

Convenient to apply and available on the Internet software CORAL (http://www.insilico.eu/CORAL) has been used to build up quantitative structure-activity relationships (QSAR) for prediction of cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (minus logarithm of concentration for 50% effect pEC50). In this study six random splits of the data into the training and test set w...

Established strategies for validating QSAR models of binary mixtures of chemicals are not applicable to the most challenging case, which is the prediction of binary mixtures created by two compounds not present in the initial training set. In this study, we have addressed this challenge by introducing the “Everything Out” validation strategy where the external sets are deliberately formed by al...

Drugs are adaptive molecules. They realize this peculiarity by generating different ensembles of prototropic forms and conformers that depend on the environment. Among the impressive amount of available computational drug discovery technologies, quantitative structure-activity relationship approaches that rely on computational quantum chemistry descriptors are the most appropriate to model adap...

We consider the problem of identifying the genetic loci (called quantitative trait loci (QTLs)) contributing to variation in a quantitative trait, with data on an experimental cross. A large number of different statistical approaches to this problem have been described; most make use of multiple tests of hypotheses, and many consider models allowing only a single QTL. We feel that the problem i...

With flavone as a structural template, three-dimensional quantitative structure-activity relationship (3D-QSAR) studies and ab initio calculations were performed on a series of flavonoids. A reasonable pharmacophore model was built through CoMFA, CoMSIA, and HQSAR analyses and electrostatic potential calculations. A plausible binding mode for flavonoids with GABA(A) receptors was rationalized. ...

In the spirit of reporting valid and reliable Quantitative Structure-Activity Relationship (QSAR) models, the aim of our research was to assess how the leverage (analysis with Hat matrix, h(i)) and the influential (analysis with Cook's distance, D(i)) of QSAR models may reflect the models reliability and their characteristics. The datasets included in this research were collected from previousl...

The visual analysis of Stereoeletroencephalographic SEEG signals in their anatomical context is aimed at understanding the spatio-temporal dynamics of epileptic processes. The magnitude of these signals may be encoded by graphical glyphs, having a direct impact on the perception of the values. This problem has motivated an evaluation of the quantitative visualization of these signals, specifica...

Starting from a random set of structures taken from the European Chemical Bureau (ECB) Web site, an estimation of the classification by acute category in ecotoxicology was carried out. This estimation was based on two approaches. One approach consists in starting with global quantitative structure-activity relationship (QSAR) equations, analyzing the results and defining an interpretation in te...