iloprost and Chemical-and-Drug-Induced-Liver-Injury

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60-70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the "Rule of Three" was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.

Topics: Animals; Anti-Infective Agents; Anti-Inflammatory Agents; Chemical and Drug Induced Liver Injury; Databases, Factual; Drug-Related Side Effects and Adverse Reactions; Humans; Liver; Models, Biological; Predictive Value of Tests

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chemical structures is critical to help guide experimental drug discovery projects toward safer medicines. In this study, we have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontological rules. We have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chemical determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. We found that the concordance of liver effects was relatively low (ca. 39-44%) between different species, raising the possibility that species specificity could depend on specific features of chemical structure. Compounds were clustered by their chemical similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, additional biological assertions were identified, which were in line with expectations based on compounds' chemical similarities. The assertions were further converted to binary annotations of underlying chemicals (i.e., liver effect vs no liver effect), and binary quantitative structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of our knowledge, this is the first study for chemical toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automate

Topics: Animals; Chemical and Drug Induced Liver Injury; Cluster Analysis; Databases, Factual; Humans; MEDLINE; Mice; Models, Chemical; Molecular Conformation; Quantitative Structure-Activity Relationship

Prostaglandins (PGs) are lipid compounds that mediate the variety of physiological and pathological functions in almost all body tissues and organs. Prostacyclin (prostaglandin 12, PGI2), which is synthesized by the vascular endothelium, is a potent vasodilator, inhibits the aggregation of platelets in vitro and has cytoprotective effect on gastrointestinal mucosa. The aim of this study was to determine whether PGI2 is playing a role in host defense to toxic effect of acetaminophen (APAP). This was investigated in C57Black/6 mice which were intoxicated with single lethal or high sublethal dose of APAP. APAP was administered to mice by gastric lavage and PGI2 agonists or antagonists were given intraperitoneally (i.p.) 30 minutes before or 2 hours after administration of APAP. The toxicity of APAP was determined by observing the survival of mice during 48 hours, by measuring the concentration of alanine-aminotransferase (ALT) in plasma 20-24 hours after APAP administration, and by liver histology. Mice were given either pure PGI2 (PGI2 sodium salt), its stable agonist (iloprost) or inhibitor of prostacyclin (IP)-receptor (CAY-10441). The results have shown that PGI2 exibits a strong hepatoprotective effect when it was given to mice either before or after APAP (both increase of survival of mice and decrease of plasma ALT levels were statistical significant). Iloprost has not shown a similar effect and CAY-10441 increased toxic effect of APAP if given 2 hours after its administration. Histopathological changes in liver generally support these findings. These investigations support the view that PGI2 is involved in defense of organism to noxious effects of xenobiotics on liver.

Topics: Acetaminophen; Alanine Transaminase; Analgesics, Non-Narcotic; Animals; Chemical and Drug Induced Liver Injury; Cytoprotection; Epoprostenol; Female; Iloprost; Male; Mice; Mice, Inbred C57BL; Receptors, Epoprostenol

Intravenous injection of murine recombinant tumor necrosis factor alpha(TNF-alpha) to male NMRI albino mice in doses greater than 4 micrograms/kg (specific activity 4 x 10(7) U/mg) resulted in a fulminant hepatitis when animals had been sensitized 1 hr before by intraperitoneal administration of 700 mg/kg galactosamine. Liver injury was assessed by measurement of serum transaminases as well as sorbitol dehydrogenase activity 8 hr after administration of TNF-alpha. Pretreatment with either galactosamine or 40 micrograms/kg TNF-alpha alone did not cause hepatitis. Pretreatment of galactosamine/TNF-alpha-injured mice with 800 mg/kg uridine or with 6 mg/kg calmidazolium fully protected the animals, while administration of either verapamil or nifedipine (100 mg/kg, respectively) had no significant effect. The following inhibitors of generation or action of leukotriene D4, which were previously shown to block galactosamine/endotoxin-induced hepatitis in mice, failed to protect against galactosamine/TNF-alpha-induced intoxication: 200 micrograms/kg dexamethasone, 174 mg/kg BW 755 C or 13 x 10 mg/kg FPL 55712. In addition, unlike in the galactosamine/endotoxin model no prevention was achieved by pretreatment of galactosamine/TNF-alpha-injured animals with the following substances blocking the development of an ischemia/reperfusion syndrome: 2 x 100 mg/kg allopurinol, 3.3 x 10(4) U/kg superoxide dismutase, 10(6) U/kg catalase or 10 micrograms/kg iloprost. We conclude from our results that tumor necrosis factor alpha is likely to act as a final mediator of endotoxin action in a sequence of events which includes formation of leukotriene D4 and reactive oxygen species.

Topics: Allopurinol; Animals; Chemical and Drug Induced Liver Injury; Eicosanoic Acids; Endotoxins; Epoprostenol; Galactosamine; Iloprost; Imidazoles; Male; Mice; Mice, Inbred Strains; Nifedipine; Superoxide Dismutase; Tumor Necrosis Factor-alpha; Verapamil; Xanthine Oxidase

It was investigated whether the prostacyclin derivative Iloprost (Schering, Berlin) protects rat hepatocytes against lethal damage induced by carbon tetrachloride (CCl4) and bromobenzene (BB). Iloprost was tested in whole animal experiments (intoxication with 2 ml CCl4/kg) and with primary hepatocyte cultures (intoxication with 1.6 mM BB). Cell damage was estimated by light microscopic examination of hepatocellular morphology and by the release of hepatocellular enzymes (glutamic-pyruvic transaminase, GPT; glutamic-oxalacetic transaminase, GOT; lactic dehydrogenase, LDH) into the blood or culture medium. In both experimental set-ups, Iloprost (0.1 micrograms/kg/min in whole animal experiments and 10(-9)-10(-12) M in primary hepatocyte cultures) largely preserved normal hepatocellular morphology after intoxication. Furthermore, the toxin-induced release of hepatocellular enzymes into the blood (GOT, GPT) or into the culture medium (LDH) was reduced by 50%-70% in the presence of Iloprost. It is concluded that the prostacyclin derivative Iloprost possesses cytoprotective activity on rat hepatocytes against lethal injury by CCl4 or BB.

Topics: Alanine Transaminase; Animals; Aspartate Aminotransferases; Bromobenzenes; Carbon Tetrachloride Poisoning; Chemical and Drug Induced Liver Injury; Epoprostenol; Iloprost; L-Lactate Dehydrogenase; Liver Diseases; Male; Necrosis; Rats