A combination of D-optimal onion design and hierarchical partial least squares modelling was applied to construct a global model of hERG blockade in order to maximize the applicability domain of the model and to enhance its interpretability. Additionally, easily interpretable hERG specific fragment-based descriptors were developed. The data can be downloaded from QSAR World here: http://www.qsarworld.com/qsar-datasets-gavaghan.php

The aim of the present study is to evaluate the quantitative contribution of passive permeability to P-glycoprotein-mediated (P-gp-mediated) efflux and the functional activity of P-gp in determining intestinal absorption of drugs, and demonstrate the relationship between efflux parameters and intestinal permeability. The associated datasets are available on QSAR world at: http://www.qsarworld.com/qsar-datasets-varma.php

We have collated literature data for 99 diverse hERG inhibitors to generate Kohonen maps, Sammon maps, and recursive partitioning models. Our aim was to investigate whether these computational models could be used either individually or together in a consensus approach to predict the binding of a prospectively selected test set of 35 diverse molecules and at the same time to offer further insights into hERG inhibition. The recursive partitioning model provided a quantitative prediction, which was markedly improved when Tanimoto similarity was included as a filter to remove molecules from the test set that were too dissimilar to the training set (r2 = 0.83, Spearman rho = 0.75, p = 0.0003 for the 18 remaining molecules, >0.77 similarity).The datasets can be downloaded from the WSAR world pages: http://www.qsarworld.com/qsar-datasets-ekins.php

Presented herein is a naive Bayes classifier to categorize hERG blockers into active and inactive classes, by using a universal, generic molecular descriptor system. The naive Bayes classifier was built from a training set containing 1979 corporate compounds, and exhibited an ROC accuracy of 0.87. The model was validated on an external test set of 66 drugs, of which 58 were correctly classified. The dataset is available from QSAR World: http://www.qsarworld.com/qsar-datasets-sun.php

68 Compounds and their hERG pIC50 values have been provided in the paper."A-56268" was retrieved as "Clarithromycin" and "Hismanal" as "Astemizole" from ChemIDPlus. "RP-58866" was not found at ChemIDPlus. Thus, 67 compounds and their pIC50 values have been provided here. The compounds used as a 'test set' have been labelled so in the AMP file. The dataset is available from the QSAR World website: http://www.qsarworld.com/qsar-datasets-keseru.php

Using descriptors which have clear physicochemical meanings and are familiar to medicinal chemists, the authors carried out 2D-quantitative structure−activity relationship (2D-QSAR) studies on 104 HERG channel blockers with diverse structures collected from the literature, and formulated interpretable models to guide chemical-modification studies and virtual screening. The links to the dataset are on QSAR world at this URL: http://www.qsarworld.com/qsar-datasets-niwa.php

A diverse set of 90 compounds with hERG IC50 inhibition data was collected from literature references. Fragment-based QSAR descriptors and three different statistical methods, support vector regression, partial least squares, and random forests, were employed to construct QSAR models for hERG binding affinity. Important fragment descriptors relevant to hERG binding affinity were identified through an efficient feature selection method based on sparse linear support vector regression. The support vector regression predictive model built upon selected fragment descriptors outperforms the other two statistical methods in this study, resulting in an r2 of 0.912 and 0.848 for the training and testing data sets, respectively. The following URL can access the datasets at the QSAR world pages: http://www.qsarworld.com/qsar-datasets-song.php

The blockade of HERG K+ channels is one of the most important molecular mechanisms through which QT-prolonging drugs increase cardiac action potential duration. Since QT prolongation is one of the most undesirable side effects of drugs, the authors first tried to identify the minimum set of molecular features responsible for this action and then attempted to develop a quantitative model correlating the 3D stereoelectronic characteristics of the molecules with their HERG blocking potency. The datasets can be downloaded from QSAR World here: http://www.qsarworld.com/qsar-datasets-cavalli.php