Lead identification of novel and selective TYK2 inhibitors

A therapeutic rationale is proposed for the treatment of inflammatory diseases, such as psoriasis and inflammatory bowel diseases (IBD), by selective targeting of TYK2. Hit triage, following a high-throughput screen for TYK2 inhibitors, revealed pyridine 1 as a promising starting point for lead identification. Initial expansion of 3 separate regions of the molecule led to eventual identification of cyclopropyl amide 46, a potent lead analog with good kinase selectivity, physicochemical properties, and pharmacokinetic profile. Analysis of the binding modes of the series in TYK2 and JAK2 crystal structures revealed key interactions leading to good TYK2 potency and design options for future optimization of selectivity.

An approach for integrating toxicogenomic data in risk assessment: the dibutyl phthalate case study

An approach for evaluating and integrating genomic data in chemical risk assessment was developed based on the lessons learned from performing a case study for the chemical dibutyl phthalate. A case study prototype approach was first developed in accordance with EPA guidance and recommendations of the scientific community. Dibutyl phthalate (DBP) was selected for the case study exercise. The scoping phase of the dibutyl phthalate case study was conducted by considering the available DBP genomic data, taken together with the entire data set, for whether they could inform various risk assessment aspects, such as toxicodynamics, toxicokinetics, and dose-response. A description of weighing the available dibutyl phthalate data set for utility in risk assessment provides an example for considering genomic data for future chemical assessments. As a result of conducting the scoping process, two questions--Do the DBP toxicogenomic data inform 1) the mechanisms or modes of action?, and 2) the interspecies differences in toxicodynamics?--were selected to focus the case study exercise. Principles of the general approach include considering the genomics data in conjunction with all other data to determine their ability to inform the various qualitative and/or quantitative aspects of risk assessment, and evaluating the relationship between the available genomic and toxicity outcome data with respect to study comparability and phenotypic anchoring. Based on experience from the DBP case study, recommendations and a general approach for integrating genomic data in chemical assessment were developed to advance the broader effort to utilize 21st century data in risk assessment.

Use of comparative genomics approaches to characterize interspecies differences in response to environmental chemicals: challenges, opportunities, and research needs

A critical challenge for environmental chemical risk assessment is the characterization and reduction of uncertainties introduced when extrapolating inferences from one species to another. The purpose of this article is to explore the challenges, opportunities, and research needs surrounding the issue of how genomics data and computational and systems level approaches can be applied to inform differences in response to environmental chemical exposure across species. We propose that the data, tools, and evolutionary framework of comparative genomics be adapted to inform interspecies differences in chemical mechanisms of action. We compare and contrast existing approaches, from disciplines as varied as evolutionary biology, systems biology, mathematics, and computer science, that can be used, modified, and combined in new ways to discover and characterize interspecies differences in chemical mechanism of action which, in turn, can be explored for application to risk assessment. We consider how genetic, protein, pathway, and network information can be interrogated from an evolutionary biology perspective to effectively characterize variations in biological processes of toxicological relevance among organisms. We conclude that comparative genomics approaches show promise for characterizing interspecies differences in mechanisms of action, and further, for improving our understanding of the uncertainties inherent in extrapolating inferences across species in both ecological and human health risk assessment. To achieve long-term relevance and consistent use in environmental chemical risk assessment, improved bioinformatics tools, computational methods robust to data gaps, and quantitative approaches for conducting extrapolations across species are critically needed. Specific areas ripe for research to address these needs are recommended.