In Silico and In Vitro Analysis of Interaction between Ximelagatran and Human Leukocyte Antigen (HLA)-DRB1*07:01

Drug hypersensitivity reactions: review of the state of the science for prediction and diagnosis

Drug hypersensitivity reactions (DHRs) are a type of adverse drug reaction that can occur with different classes of drugs and affect multiple organ systems and patient populations. DHRs can be classified as allergic or non-allergic based on the cellular mechanisms involved. Whereas nonallergic reactions rely mainly on the innate immune system, allergic reactions involve the generation of an adaptive immune response. Consequently, drug allergies are DHRs for which an immunological mechanism, with antibody and/or T cell, is demonstrated. Despite decades of research, methods to predict the potential for a new chemical entity to cause DHRs or to correctly attribute DHRs to a specific mechanism and a specific molecule are not well-established. This review will focus on allergic reactions induced by systemically administered low-molecular weight drugs with an emphasis on drug- and patient-specific factors that could influence the development of DHRs. Strategies for predicting and diagnosing DHRs, including potential tools based on the current state of the science, will also be discussed.

Drug-specific T-cell responses in patients with liver injury following treatment with the BACE inhibitor atabecestat

BACKGROUND

Atabecestat is an orally administered BACE inhibitor developed to treat Alzheimer's disease. Elevations in hepatic enzymes were detected in a number of in trial patients, which resulted in termination of the drug development programme. Immunohistochemical characterization of liver tissue from an index case of atabecestat-mediated liver injury revealed an infiltration of T-lymphocytes in areas of hepatocellular damage. This coupled with the fact that liver injury had a delayed onset suggests that the adaptive immune system may be involved in the pathogenesis. The aim of this study was to generate and characterize atabecestat(metabolite)-responsive T-cell clones from patients with liver injury.

METHODS

Peripheral blood mononuclear cells were cultured with atabecestat and its metabolites (diaminothiazine [DIAT], N-acetyl DIAT & epoxide) and cloning was attempted in a number of patients. Atabecestat(metabolite)-responsive clones were analysed in terms of T-cell phenotype, function, pathways of T-cell activation and cross-reactivity with structurally related compounds.

RESULTS

CD4⁺ T-cell clones activated with the DIAT metabolite were detected in 5 out of 8 patients (up to 4.5% cloning efficiency). Lower numbers of CD4⁺ and CD8⁺ clones displayed reactivity against atabecestat. Clones proliferated and secreted IFN-γ, IL-13 and cytolytic molecules following atabecestat or DIAT stimulation. Certain atabecestat and DIAT-responsive clones cross-reacted with N-acetyl DIAT; however, no cross-reactivity was observed between atabecestat and DIAT. CD4⁺ clones were activated through a direct, reversible compound-HLA class II interaction with no requirement for protein processing.

CONCLUSION

The detection of atabecestat metabolite-responsive T-cell clones activated via a pharmacological interactions pathway in patients with liver injury is indicative of an immune-based mechanism for the observed hepatic enzyme elevations.

Latest advances in diagnosing and predicting DILI: what was new in 2017?

Drug-induced liver injury (DILI) remains an increasingly recognized cause of hepatotoxicity and liver failure worldwide. In 2017, we continued to learn about predicting, diagnosing, and prognosticating drug hepatotoxicity. Areas covered: In this review, we selected from over 1200 articles from 2017 to synopsize updates in DILI. There were new HLA haplotypes associated with medications including HLA-C0401 and HLA-B*14. There has been continued work with quantitative systems pharmacology, particularly with the DILIsym® initiative, which employs mathematical representations of DILI mechanisms to predict hepatotoxicity in simulated populations. Additionally, knowledge regarding microRNAs (miRNAs) continues to expand. Some new miRNAs this past year include miRNA-223 and miRNA-605. Aside from miRNAs, other biomarkers for diagnosis, prognosis, and even prediction of DILI were explored. Studies on K18, OPN, and MCSFR have correlated DILI and liver-associated death within 6 months. Conversely, a new prognostic panel using apolipoportein-A1 and haptoglobin has been proposed to predict recovery. Further study of CDH5 has also provided researchers a possible new biomarker for prediction and susceptibility to DILI. Expert commentary: Although research on DILI remains quite promising, there is yet to be a reliable, simple method to predict, diagnose, and risk assess this form of hepatotoxicity.

Model-based identification of TNFα-induced IKKβ-mediated and IκBα-mediated regulation of NFκB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds

Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive. Here, we combined time-resolved immunoblotting and live-cell imaging data of HepG2 cells and primary human hepatocytes (PHH) with dynamic pathway modeling using ordinary differential equations (ODEs) to describe the complex structure of TNFα-induced NFκB signal transduction and integrated the perturbations of the pathway caused by diclofenac. The resulting mathematical model was used to systematically identify parameters affected by diclofenac. These analyses showed that more than one regulatory module of TNFα-induced NFκB signal transduction is affected by diclofenac, suggesting that hepatotoxicity is the integrated consequence of multiple changes in hepatocytes and that multiple factors define toxicity thresholds. Applying our mathematical modeling approach to other DILI-causing compounds representing different putative DILI mechanism classes enabled us to quantify their impact on pathway activation, highlighting the potential of the dynamic pathway model as a quantitative tool for the analysis of DILI compounds.

Interaction of Nevirapine with the Peptide Binding Groove of HLA-DRB1*01:01 and Its Effect on the Conformation of HLA-Peptide Complex

Human leukocyte antigen (HLA)-DRB1*01:01 has been shown to be involved in nevirapine-induced hepatic hypersensitivity reactions. In the present study, in silico docking simulations and molecular dynamics simulations were performed to predict the interaction mode of nevirapine with the peptide binding groove of HLA-DRB1*01:01 and its possible effect on the position and orientation of the ligand peptide derived from hemagglutinin (HA). In silico analyses suggested that nevirapine interacts with HLA-DRB1*01:01 around the P4 pocket within the peptide binding groove and the HA peptide stably binds on top of nevirapine at the groove. The analyses also showed that binding of nevirapine at the groove will significantly change the inter-helical distances of the groove. An in vitro competitive assay showed that nevirapine (1000 μM) increases the binding of the HA peptide to HLA-DRB1*01:01 in an allele-specific manner. These results indicate that nevirapine might interact directly with the P4 pocket and modifies its structure, which could change the orientation of loaded peptides and the conformation of HLA-DRB1*01:01; these changes could be distinctively recognized by T-cell receptors. Through this molecular mechanism, nevirapine might stimulate the immune system, resulting in hepatic hypersensitivity reactions.

Adverse drug reactions triggered by the common HLA-B*57:01 variant: virtual screening of DrugBank using 3D molecular docking

BACKGROUND

Idiosyncratic adverse drug reactions have been linked to a drug's ability to bind with a human leukocyte antigen (HLA) protein. However, due to the thousands of HLA variants and limited structural data for drug-HLA complexes, predicting a specific drug-HLA combination represents a significant challenge. Recently, we investigated the binding mode of abacavir with the HLA-B*57:01 variant using molecular docking. Herein, we developed a new ensemble screening workflow involving three X-ray crystal derived docking procedures to screen the DrugBank database and identify potentially HLA-B*57:01 liable drugs. Then, we compared our workflow's performance with another model recently developed by Metushi et al., which proposed seven in silico HLA-B*57:01 actives, but were later found to be experimentally inactive.

METHODS

After curation, there were over 6000 approved and experimental drugs remaining in DrugBank for docking using Schrodinger's GLIDE SP and XP scoring functions. Docking was performed with our new consensus-like ensemble workflow, relying on three different X-ray crystals (3VRI, 3VRJ, and 3UPR) in presence and absence of co-binding peptides. The binding modes of HLA-B*57:01 hit compounds for all three peptides were further explored using 3D interaction fingerprints and hierarchical clustering.

RESULTS

The screening resulted in 22 hit compounds forecasted to bind HLA-B*57:01 in all docking conditions (SP and XP with and without peptides P1, P2, and P3). These 22 compounds afforded 2D-Tanimoto similarities being less than 0.6 when compared to the structure of native abacavir, whereas their 3D binding mode similarities varied in a broader range (0.2-0.8). Hierarchical clustering using a Ward Linkage revealed different clustering patterns for each co-binding peptide. When we docked Metushi et al.'s seven proposed hits using our workflow, our screening platform identified six out of seven as being inactive. Molecular dynamic simulations were used to explore the stability of abacavir and acyclovir in complex with peptide P3.

CONCLUSIONS

This study reports on the extensive docking of the DrugBank database and the 22 HLA-B*57:01 liable candidates we identified. Importantly, comparisons between this study and the one by Metushi et al. highlighted new critical and complementary knowledge for the development of future HLA-specific in silico models.

Harnessing a catalytic lysine residue for the one-step preparation of homogeneous antibody-drug conjugates

Current strategies to produce homogeneous antibody-drug conjugates (ADCs) rely on mutations or inefficient conjugation chemistries. Here we present a strategy to produce site-specific ADCs using a highly reactive natural buried lysine embedded in a dual variable domain (DVD) format. This approach is mutation free and drug conjugation proceeds rapidly at neutral pH in a single step without removing any charges. The conjugation chemistry is highly robust, enabling the use of crude DVD for ADC preparation. In addition, this strategy affords the ability to precisely monitor the efficiency of drug conjugation with a catalytic assay. ADCs targeting HER2 were prepared and demonstrated to be highly potent and specific in vitro and in vivo. Furthermore, the modular DVD platform was used to prepare potent and specific ADCs targeting CD138 and CD79B, two clinically established targets overexpressed in multiple myeloma and non-Hodgkin lymphoma, respectively.

Current strategies for producing antibody-drug conjugates often rely on inefficient conjugation chemistry or on generating mutations in the antibody sequence. Here the authors demonstrate a mutation-free, single-step conjugation platform utilizing a buried lysine residue.