New phenotypic cytotoxicity assay for ROS-inducing compounds using rat renal epithelial cells.

An important mechanism of chemical toxicity is the induction of oxidative stress through the production of excess reactive oxygen species (ROS). In this study, we show that the level of drug-induced ROS production between NRK52E and HepG2 cells is significantly different for several marketed drugs and a number of Takeda's internal proprietary compounds. Nifedipine, a calcium channel blocker and the initial focus of the study, was demonstrated to promote in vitro ROS production and a decrease in cell viability in NRK52E cells but not HepG2 cells. ROS production after nifedipine treatment was inhibited by a NOX inhibitor (GKT136901) but not the mitochondrial NADH dehydrogenase inhibitor, rotenone, suggesting that nifedipine decreases NRK52E cell viability primarily through a NOX-mediated pathway. To understand the breadth of NOX-mediated ROS production, 12 commercially available compounds that are structurally and/or pharmacologically related to nifedipine as well as 172 internal Takeda candidate drugs, were also evaluated against these two cell types. Over 15 % of compounds not cytotoxic to HepG2 cells (below 50 µM) were cytotoxic to NRK52E cells. Our results suggest that a combination of cell viability data from both NRK52E and HepG2 cells was superior for the prediction of in vivo toxicity findings when compared to use of only one cell line. Further, the NRK52E cell viability assay is a good predictor of NOX-mediated ROS production and can be used as a follow up assay following a negative HepG2 response to aid in the selection of suitable compounds for in vivo toxicity studies.

The development of structure-activity relationships for mitochondrial dysfunction: uncoupling of oxidative phosphorylation.

Mitochondrial dysfunction has been implicated as an important factor in the development of idiosyncratic organ toxicity. An ability to predict mitochondrial dysfunction early in the drug development process enables the deselection of those drug candidates with potential safety liabilities, allowing resources to be focused on those compounds with the highest chance of success to the market. A database of greater than 2000 compounds was analyzed to identify structural and physicochemical features associated with the uncoupling of oxidative phosphorylation (herein defined as an increase in basal respiration). Many toxicophores associated with potent uncoupling activity were identified, and these could be divided into two main mechanistic classes, protonophores and redox cyclers. For the protonophores, potent uncoupling activity was often promoted by high lipophilicity and apparent stabilization of the anionic charge resulting from deprotonation of the protonophore. The potency of redox cyclers did not appear to be prone to variations in lipophilicity. Only 11 toxicophores were of sufficient predictive performance that they could be incorporated into a structural-alert model. Each alert was associated with one of three confidence levels (high, medium, and low) depending upon the lipophilicity-activity profile of the structural class. The final model identified over 68% of those compounds with potent uncoupling activity and with a value for specificity above 99%. We discuss the advantages and limitations of this approach and conclude that although structural alert methodology is useful for identifying toxicophores associated with mitochondrial dysfunction, they are not a replacement for the mitochondrial dysfunction assays in early screening paradigms.

Latest advances in computational genotoxicity prediction.

INTRODUCTION: Computational approaches for genotoxicity prediction have existed for over two decades. Numerous methodologies have been utilized and the results of various evaluations have published. AREAS COVERED: In silico methods are considered mature enough to be part of draft FDA regulatory guidelines for the assessment of genotoxic impurities. However, aspects of how best to use predictive systems remain unresolved: i) methodologies to measure how similar two compounds need to be in order to assume they have the same biological outcome; and ii) defining whether a compound is close enough to the model training set such that a model prediction can be considered reliable. EXPERT OPINION: In silico prediction of genotoxicity is a fundamental part of screening strategies for the assessment genotoxic impurities in drug products. However, the concept of using chemical similarity to infer mutagenic potential from one of known activity to another whose activity is unknown remains a scientific challenge. Similarly, defining when an in silico model prediction can be considered to be reliable is also difficult. Reaction mechanisms and the functional group building blocks of chemistry are pretty much constant, and so when data-gaps appear, it tends to be for compounds that have been regularly used but rarely tested.

New and emerging technologies for genetic toxicity testing.

The International Life Sciences Institute (ILSI) Health and Environmental Sciences Institute (HESI) Project Committee on the Relevance and Follow-up of Positive Results in In Vitro Genetic Toxicity (IVGT) Testing established an Emerging Technologies and New Strategies Workgroup to review the current State of the Art in genetic toxicology testing. The aim of the workgroup was to identify promising technologies that will improve genotoxicity testing and assessment of in vivo hazard and risk, and that have the potential to help meet the objectives of the IVGT. As part of this initiative, HESI convened a workshop in Washington, DC in May 2008 to discuss mature, maturing, and emerging technologies in genetic toxicology. This article collates the abstracts of the New and Emerging Technologies Workshop together with some additional technologies subsequently considered by the workgroup. Each abstract (available in the online version of the article) includes a section addressed specifically to the strengths, weaknesses, opportunities, and threats associated with the respective technology. Importantly, an overview of the technologies and an indication of how their use might be aligned with the objectives of IVGT are presented. In particular, consideration was given with regard to follow-up testing of positive results in the standard IVGT tests (i.e., Salmonella Ames test, chromosome aberration assay, and mouse lymphoma assay) to add weight of evidence and/or provide mechanism of action for improved genetic toxicity risk assessments in humans.

Developing structure-activity relationships for the prediction of hepatotoxicity.

Drug-induced liver injury is a major issue of concern and has led to the withdrawal of a significant number of marketed drugs. An understanding of structure-activity relationships (SARs) of chemicals can make a significant contribution to the identification of potential toxic effects early in the drug development process and aid in avoiding such problems. This process can be supported by the use of existing toxicity data and mechanistic understanding of the biological processes for related compounds. In the published literature, this information is often spread across diverse sources and can be varied and unstructured in quality and content. The current work has explored whether it is feasible to collect and use such data for the development of new SARs for the hepatotoxicity endpoint and expand upon the limited information currently available in this area. Reviews of hepatotoxicity data were used to build a structure-searchable database, which was analyzed to identify chemical classes associated with an adverse effect on the liver. Searches of the published literature were then undertaken to identify additional supporting evidence, and the resulting information was incorporated into the database. This collated information was evaluated and used to determine the scope of the SARs for each class identified. Data for over 1266 chemicals were collected, and SARs for 38 classes were developed. The SARs have been implemented as structural alerts using Derek for Windows (DfW), a knowledge-based expert system, to allow clearly supported and transparent predictions. An evaluation exercise performed using a customized DfW version 10 knowledge base demonstrated an overall concordance of 56% and specificity and sensitivity values of 73% and 46%, respectively. The approach taken demonstrates that SARs for complex endpoints can be derived from the published data for use in the in silico toxicity assessment of new compounds.

The computational prediction of genotoxicity.

IMPORTANCE OF THE FIELD: The computational prediction of genotoxicity is important to the early identification of those chemical entities that have the potential to cause carcinogenicity in humans. AREAS COVERED IN THIS REVIEW: The review discusses key scientific developments in the prediction of Ames mutagenicity and in vitro chromosome damage over the past 4 - 5 years. The performance and limitations of computational approaches are discussed in relation to published and internal validation exercises. Their application to the modern drug discovery paradigm is also discussed. WHAT THE READER WILL GAIN: Key highlights of a review of the recent scientific literature for the prediction of Ames mutagenicity and chromosome damage and an appreciation of the factors that limit the predictive performance of in silico systems. TAKE HOME MESSAGE: Current in silico systems perform well in the mutagenicity prediction of the publicly-derived data on which they are based, but their performance outside the applicability domain is considerably lower. We conclude that it is the lack of mechanistic structure-activity relationships and limited access to high quality proprietary data which are holding back computational genotoxicity from reaching higher predictive levels.

Cyclin-dependent kinase 4 inhibitors as a treatment for cancer. Part 1: identification and optimisation of substituted 4,6-bis anilino pyrimidines.

Using a high-throughput screening campaign, we identified the 4,6-bis anilino pyrimidines as inhibitors of the cyclin-dependent kinase, CDK4. Herein we describe the further chemical modification and use of X-ray crystallography to develop potent and selective in vitro inhibitors of CDK4.