Lixivaptan - an evidence-based review of its clinical potential in the treatment of hyponatremia

In Silico Repurposed Drugs against Monkeypox Virus

Monkeypox is an emerging epidemic of concern. The disease is caused by the monkeypox virus and an increasing global incidence with a 2022 outbreak that has spread to Europe amid the COVID-19 pandemic. The new outbreak is associated with novel, previously undiscovered mutations and variants. Currently, the US Food and Drug Administration (FDA) approved poxvirus treatment involves the use of tecovirimat. However, there is otherwise limited pharmacopoeia and research interest in monkeypox. In this study, virtual screening and molecular dynamics were employed to explore the potential repurposing of multiple drugs previously approved by the FDA or other jurisdictions for other applications. Several drugs are predicted to tightly bind to viral proteins, which are crucial in viral replication, including molecules which show high potential for binding the monkeypox D13L capsid protein, whose inhibition has previously been demonstrated to suppress viral replication.

Metabolic Reprogramming and Reconstruction: Integration of Experimental and Computational Studies to Set the Path Forward in ADPKD

Metabolic reprogramming is a key feature of Autosomal Dominant Polycystic Kidney Disease (ADPKD) characterized by changes in cellular pathways occurring in response to the pathological cell conditions. In ADPKD, a broad range of dysregulated pathways have been found. The studies supporting alterations in cell metabolism have shown that the metabolic preference for abnormal cystic growth is to utilize aerobic glycolysis, increasing glutamine uptake and reducing oxidative phosphorylation, consequently resulting in ADPKD cells shifting their energy to alternative energetic pathways. The mechanism behind the role of the polycystin proteins and how it leads to disease remains unclear, despite the identification of numerous signaling pathways. The integration of computational data analysis that accompanies experimental findings was pivotal in the identification of metabolic reprogramming in ADPKD. Here, we summarize the important results and argue that their exploitation may give further insights into the regulative mechanisms driving metabolic reprogramming in ADPKD. The aim of this review is to provide a comprehensive overview on metabolic focused studies and potential targets for treatment, and to propose that computational approaches could be instrumental in advancing this field of research.

Comparison of the Hepatotoxic Potential of Two Treatments for Autosomal-Dominant Polycystic Kidney DiseaseUsing Quantitative Systems Toxicology Modeling

Purpose

Autosomal-dominant polycystic kidney disease (ADPKD) is an orphan disease with few current treatment options. The vasopressin V₂ receptor antagonist tolvaptan is approved in multiple countries for the treatment of ADPKD, however its use is associated with clinically significant drug-induced liver injury.

Methods

In prior studies, the potential for hepatotoxicity of tolvaptan was correctly predicted using DILIsym®, a quantitative systems toxicology (QST) mathematical model of drug-induced liver injury. In the current study, we evaluated lixivaptan, another proposed ADPKD treatment and vasopressin V₂ receptor antagonist, using DILIsym®. Simulations were conducted that assessed the potential for lixivaptan and its three main metabolites to cause hepatotoxicity due to three injury mechanisms: bile acid accumulation, mitochondrial dysfunction, and oxidative stress generation. Results of these simulations were compared to previously published DILIsym results for tolvaptan.

Results

No ALT elevations were predicted to occur at the proposed clinical dose for lixivaptan, in contrast to previously published simulation results for tolvaptan. As such, lixivaptan was predicted to have a markedly lower risk of hepatotoxicity compared to tolvaptan with respect to the hepatotoxicity mechanisms represented in DILIsym.

Conclusions

These results demonstrate the potential for using QST methods to differentiate drugs in the same class for their potential to cause hepatotoxicity.

Electronic supplementary material

The online version of this article (10.1007/s11095-019-2726-0) contains supplementary material, which is available to authorized users.