Biomarkers of drug-induced liver injury

Zhou, Yong; Qin, Shizhen; Wang, Kai

doi:10.2147/cbf.s27900

Cited by 5 publications

(4 citation statements)

References 90 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is well‐known that DILI has complicated mechanisms, and most mechanisms are involved chemical reactions with proteins and other macromolecules in liver cells 1,4–5,49. The six fragments were separated into two categories to explain their mechanisms.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method

Zhang

Cheng

et al. 2016

Molecular Informatics

View full text Add to dashboard Cite

Drug-induced liver injury (DILI) is a leading cause of acute liver failure in the US and less severe liver injury worldwide. It is also one of the major reasons of drug withdrawal from the market. Thus, DILI has become one of the most important concerns of drugs, and should be predicted in very early stage of drug discovery process. In this study, a comprehensive data set containing 1317 diverse compounds was collected from publications. Then, high accuracy classification models were built using five machine learning methods based on MACCS and FP4 fingerprints after evaluating by substructure pattern recognition method. The best model was built using SVM method together with FP4 fingerprint at the IG value threshold of 0.0005. Its overall predictive accuracies were 79.7 % and 64.5 % for the training and test sets, separately, which yielded overall accuracy of 75.0 % for the external validation dataset, consisting of 88 compounds collected from a benchmark DILI database - the Liver Toxicity Knowledge Base. This model could be used for drug-induced liver toxicity prediction. Moreover, some key substructure patterns correlated with drug-induced liver toxicity were also identified as structural alerts.

show abstract

Section: Resultsmentioning

confidence: 99%

“…It is an important disease in clinical practice. However, the diagnosis of DILI is challenging because there are no specific clinical features or laboratory tests found in all cases 3–4. Meanwhile, DILI is the most frequent reason cited for drug withdrawal from the market 5.…”

Section: Introductionmentioning

confidence: 99%

In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method

Zhang

Cheng

et al. 2016

Molecular Informatics

View full text Add to dashboard Cite

show abstract

“…Recent advances in biomedical research have underscored the excessive generation of highly reactive oxygen/nitrogen species (ROS/RNS), notably ONOO−, within mitochondria following medication overdose, thereby precipitating severe hepatotoxicity (DiMasi, 2001;Rudin, 2005;Bertolini et al, 2006;Uetrecht, 2010;Amacher et al, 2013). Furthermore, the enzymatic activity of leucine aminopeptidase (LAP) is markedly elevated during hepatic dysfunction compared to physiological states (Aithal et al, 2011;Wang and Zhou, 2013;Atallah et al, 2021). Notably, both ONOO− and LAP have been substantiated as early diagnostic biomarkers for drug-induced liver diseases by numerous investigators (Pacher et al, 2007;Howell et al, 2018).…”

Section: Liver Injury Enzymementioning

confidence: 99%

Shining a light on liver health: advancements in fluorescence-enhanced enzyme biosensors for early disease detection

Liu,

Yin,

Liu

et al. 2024

Front. Bioeng. Biotechnol.

View full text Add to dashboard Cite

Early detection of liver diseases holds paramount importance in optimizing treatment outcomes and prognosis, thereby significantly enhancing the likelihood of recovery while mitigating the risk of progression to liver cancer. Liver diseases encompass a spectrum of conditions, each potentially manifesting distinct enzymatic profiles. Monitoring these enzymes in situ facilitates timely intervention and therapeutic management. In recent years, the field of biosensor technology has witnessed remarkable advancement, owing to strides in biomedicine and computational sciences. Biosensors have garnered widespread utility across medical and biological domains, spanning the detection of disease biomarkers, drug release tracking, ion imaging, and fluorescence imaging within living organisms. These applications have markedly enhanced imaging resolution and have the potential to refine disease diagnosis accuracy for clinicians. A pivotal aspect in the successful application of this technology lies in the construction of fluorescence probes adept at swiftly and selectively identifying target enzymes by amalgamating liver disease enzymes with fluorescence probe technology. However, research in this niche area remains relatively scarce. Building upon this foundational understanding, the present review delineates the utilization of biosensors in the early diagnosis of liver disease. Serving as a theoretical framework, this review envisages the development of high-performance biosensors tailored for the early detection of liver cancer. Furthermore, it offers insights into the potential of biosensor technology to progress and broaden its practical applications, thus contributing to the advancement of diagnostic methodologies in liver disease management.

show abstract

“…Understanding the molecular mechanisms underlying the transition from desired drug effects to adverse events induced by therapeutic and toxic doses, respectively, is of general importance for both clinical diagnostics and curative intervention strategies [ 10 ]. In this regard, robust clinical biomarkers may significantly improve patient safety and health [ 11 , 12 , 13 , 14 , 15 ] by the initial identification of cellular mechanisms indicating drug toxicity in order to implement appropriate interventions at an early stage [ 16 , 17 , 18 , 19 ]. Comparatively analyzing cellular responses following the transition from therapeutic to toxic doses supports the identification of molecular biomarkers and would clearly help to investigate to what extent specific drugs similarly contribute to characteristic toxicological processes and, furthermore, to find out potential interactions between those drugs, which might act on a mutual target gene.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations

et al. 2017

View full text Add to dashboard Cite

Drug-induced toxicity is a significant problem in clinical care. A key problem here is a general understanding of the molecular mechanisms accompanying the transition from desired drug effects to adverse events following administration of either therapeutic or toxic doses, in particular within a patient context. Here, a comparative toxicity analysis was performed for fifteen hepatotoxic drugs by evaluating toxic changes reflecting the transition from therapeutic drug responses to toxic reactions at the cellular level. By use of physiologically-based pharmacokinetic modeling, in vitro toxicity data were first contextualized to quantitatively describe time-resolved drug responses within a patient context. Comparatively studying toxic changes across the considered hepatotoxicants allowed the identification of subsets of drugs sharing similar perturbations on key cellular processes, functional classes of genes, and individual genes. The identified subsets of drugs were next analyzed with regard to drug-related characteristics and their physicochemical properties. Toxic changes were finally evaluated to predict both molecular biomarkers and potential drug-drug interactions. The results may facilitate the early diagnosis of adverse drug events in clinical application.

show abstract

Biomarkers of drug-induced liver injury

Cited by 5 publications

References 90 publications

In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method

In silico Prediction of Drug Induced Liver Toxicity Using Substructure Pattern Recognition Method

Shining a light on liver health: advancements in fluorescence-enhanced enzyme biosensors for early disease detection

A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations

Contact Info

Product

Resources

About