Comparing the performance of meta-classifiers-a case study on selected imbalanced data sets relevant for prediction of liver toxicity.

Cheminformatics datasets used in classification problems, especially those related to biological or physicochemical properties, are often imbalanced. This presents a major challenge in development of in silico prediction models, as the traditional machine learning algorithms are known to work best on balanced datasets. The class imbalance introduces a bias in the performance of these algorithms due to their preference towards the majority class.

Predicting drug-induced liver injury: The importance of data curation.

Drug-induced liver injury (DILI) is a major issue for both patients and pharmaceutical industry due to insufficient means of prevention/prediction. In the current work we present a 2-class classification model for DILI, generated with Random Forest and 2D molecular descriptors on a dataset of 966 compounds. In addition, predicted transporter inhibition profiles were also included into the models.

Curated human hyperbilirubinemia data and the respective OATP1B1 and 1B3 inhibition predictions.

Hyperbilirubinemia is a pathological condition, very often indicative of underlying liver condition that is characterized by excessive accumulation of conjugated or unconjugated bilirubin in sinusoidal blood. In literature there are several indications associating the inhibition of the basolateral hepatic transporters Organic anion transporting polypeptide 1B1 and 1B3 (OATP1B1 and 1B3) with hyperbilirubinemia. In this article, we present a curated human hyperbilirubinemia dataset and the respective OATP1B1 and 1B3 inhibition predictions obtained from an effort to generate a classification model for hyperbilirubinemia.

Predicting Drug-Induced Cholestasis with the Help of Hepatic Transporters-An in Silico Modeling Approach.

Cholestasis represents one out of three types of drug induced liver injury (DILI), which comprises a major challenge in drug development. In this study we applied a two-class classification scheme based on k-nearest neighbors in order to predict cholestasis, using a set of 93 two-dimensional (2D) physicochemical descriptors and predictions of selected hepatic transporters' inhibition (BSEP, BCRP, P-gp, OATP1B1, and OATP1B3). In order to assess the potential contribution of transporter inhibition, we compared whether the inclusion of the transporters' inhibition predictions contributes to a significant increase in model performance in comparison to the plain use of the 93 2D physicochemical descriptors.

Linking organic anion transporting polypeptide 1B1 and 1B3 (OATP1B1 and OATP1B3) interaction profiles to hepatotoxicity - The hyperbilirubinemia use case.

Hyperbilirubinemia is a pathological condition of excessive accumulation of conjugated or unconjugated bilirubin in blood. It has been associated with neurotoxicity and non-neural organ dysfunctions, while it can also be a warning of liver side effects. Hyperbilirubinemia can either be a result of overproduction of bilirubin due to hemolysis or dyserythropoiesis, or the outcome of impaired bilirubin elimination due to liver transporter malfunction or inhibition.

Identification of Novel Inhibitors of Organic Anion Transporting Polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) Using a Consensus Vote of Six Classification Models.

Organic anion transporting polypeptides 1B1 and 1B3 are transporters selectively expressed on the basolateral membrane of the hepatocyte. Several studies reveal that they are involved in drug-drug interactions, cancer, and hyperbilirubinemia. In this study, we developed a set of classification models for OATP1B1 and 1B3 inhibition based on more than 1700 carefully curated compounds from literature, which were validated via cross-validation and by use of an external test set.

Synthesis of derivatives of the keto-pyrrolyl-difluorophenol scaffold: some structural aspects for aldose reductase inhibitory activity and selectivity.

Seven novel ARIs (3a-c, 4a-c and 5) were synthesized with the implementation of an optimized and, partially, selective synthetic procedure, via a Friedel-Crafts acylation reaction. The synthesized ARIs have values of IC(50)(ALR2) ranging from 0.19μM (in case of compound 3b) to 2.

Novel aldose reductase inhibitors: a patent survey (2006--present).

Introduction: Initially studied for its central role in the pathogenesis of chronic diabetic complications, aldose reductase (ALR2) gains more attention over the years as its implication in inflammatory diseases is being established, along with the therapeutic potential of its inhibitors.

Areas Covered: Reviewing the patents that were published since 2006, it is getting clear that the search for new chemical entities has subsided, giving rise to natural products and plant extracts with ALR2 inhibitory activity. Other aspects that were prominent were the search for proper forms of known inhibitors, in a way to improve their impaired physicochemical profile, as well as potential combination therapies with other compounds of pharmaceutical interest.