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Frontiers in Drug Toxicity Prediction

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Toxicology".

Deadline for manuscript submissions: closed (30 November 2018) | Viewed by 61309

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Prof. Dr. Dale Johnson

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University of California, Berkeley, Morgan Hall, Berkeley, CA 94720, USA
Interests: structure-toxicity relationships; translational biomarkers; computational systems toxicology
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Dear Colleagues,

The prediction of potential drug toxicity, early in the drug research and development process, continues to expand in relevance due to the availability of large data sets of classical study information gained through new data mining efforts, multiple available sources of chemical/-omics data, and data from new developing technologies featuring human-based systems, such as organ-on-a-chip and induced pluripotent stem cell-derived models. In addition, the identification of key chemical–cell–tissue fluxes via technologies, such as imaging mass spectrometry, has also enhanced the knowledge of drug toxicity target interactions. The fusion of bioinformatics and computational sciences with molecular biology and chemistry have ushered in the era of Computational Systems Toxicology, which promotes the integration of classical toxicology with quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Computational Systems Toxicology enables the identification of important pathways and molecules from large datasets to allow hypotheses on potential links between drug entities and potential toxicity at both the research and later development stages of drug development. These rapidly developing tools and models hold tremendous promise for advancing applied and basic science, streamlining drug efficacy and safety testing, and to increase the efficiency and effectiveness of predicting off-target toxicities. These approaches also offer the potential to improve toxicological experimental design, reduce the overall number of experimental toxicology studies needed, and reduce the number of animals used in experimentation. Predictive toxicology is multi-disciplinary and includes research in medicinal chemistry, molecular biology including the identification of genes/proteins as desired and/or unwanted targets of chemicals, rapid advances in biomarker identification, chemical/protein docking to identify potential target interactions, and imaging pathology including from bio-banked tissues. The field also includes the personalized prediction of potential toxicity for individual patients with certain genetic susceptibilities, toxicity from multiple drugs within a regimen (polypharmacy), and potential drug interactions with dietary supplements and/or herbal medicine formulations. Advances in all phases of predictive toxicology are showing promise to provide better analyses of potential human toxicity from single and multiple drugs.

Prof. Dr. Dale Johnson
Guest Editor

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Keywords

computational systems toxicology
off-target toxicities
safety biomarkers
bioinformatics
human-based technologies
biological pathways
in vitro and in vivo extrapolations
SAR–QSAR
expert systems
database mining

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Published Papers (9 papers)

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Research

Jump to: Review

11 pages, 1107 KiB

Open AccessArticle

Selenium and Glutathione-Depleted Rats as a Sensitive Animal Model to Predict Drug-Induced Liver Injury in Humans

by Keisuke Goda, Kyotaka Muta, Yuzo Yasui, Shin-ichi Oshida, Kanae Kitatani and Susumu Takekoshi

Int. J. Mol. Sci. 2019, 20(13), 3141; https://doi.org/10.3390/ijms20133141 - 27 Jun 2019

Cited by 10 | Viewed by 3178

Abstract

Drug-induced liver injury (DILI) is one of the most serious and frequent drug-related adverse events in humans. Selenium (Se) and glutathione (GSH) have a crucial role for the hepatoprotective effect against reactive metabolites or oxidative damage leading to DILI. The hepatoprotective capacity related to Se and GSH in rodents is considered to be superior compared to the capacity in humans. Therefore, we hypothesize that Se/GSH-depleted rats could be a sensitive animal model to predict DILI in humans. In this study, Se-deficiency is induced by feeding a Se-deficient diet and GSH-deficiency is induced by l-buthionine-S,R-sulfoxinine treatment via drinking water. The usefulness of this animal model is validated using flutamide, which is known to cause DILI in humans but not in intact rats. In the Se/GSH-depleted rats from the present study, decreases in glutathione peroxidase-1 protein expression and GSH levels and an increase in malondialdehyde levels in the liver are observed without any increase in plasma liver function parameters. Five-day repeated dosing of flutamide at 150 mg/kg causes hepatotoxicity in the Se/GSH-depleted rats but not in normal rats. In conclusion, Se/GSH-depleted rats are the most sensitive for detecting flutamide-induced hepatotoxicity in all the reported animal models. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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15 pages, 6505 KiB

Open AccessArticle

Network-Based Assessment of Adverse Drug Reaction Risk in Polypharmacy Using High-Throughput Screening Data

by Guillermo de Anda-Jáuregui, Kai Guo and Junguk Hur

Int. J. Mol. Sci. 2019, 20(2), 386; https://doi.org/10.3390/ijms20020386 - 17 Jan 2019

Cited by 11 | Viewed by 5228

Abstract

The risk of adverse drug reactions increases in a polypharmacology setting. High-throughput drug screening with transcriptomics applied to human cells has shown that drugs have effects on several molecular pathways, and these affected pathways may be predictive proxy for adverse drug reactions. Depending on the way that different drugs may contribute to adverse drug reactions, different options may exist in the clinical setting. Here, we formulate a network framework to integrate the relationships between drugs, biological functions, and adverse drug reactions based on the high-throughput drug perturbation data from the Library of Integrated Network-Based Cellular Signatures (LINCS) project. We present network-based parameters that indicate whether a given reaction may be related to the effect of a single drug or to the combination of several drugs, as well as the relative risk of adverse drug reaction manifestation given a certain drug combination. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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17 pages, 2272 KiB

Open AccessArticle

Metallothionein and Superoxide Dismutase—Antioxidative Protein Status in Fullerene-Doxorubicin Delivery to MCF-7 Human Breast Cancer Cells

by Marta Kepinska, Rene Kizek and Halina Milnerowicz

Int. J. Mol. Sci. 2018, 19(10), 3253; https://doi.org/10.3390/ijms19103253 - 20 Oct 2018

Cited by 17 | Viewed by 4027

Abstract

Doxorubicin (DOX) is one of the most frequently used anticancer drugs in breast cancer treatment. However, clinical applications of DOX are restricted, largely due to the fact that its action disturbs the pro/antioxidant balance in both cancerous and non-cancerous cells. The aim of this study was to investigate the influence of fullerene (C₆₀) in cell treatment by DOX on the proliferation of human breast cancer cells (MCF-7), concentration of metallothionein (MT) and superoxide dismutase (SOD), and SOD activity in these cells. The use of C₆₀ in complexes with DOX causes a change in the level of cell proliferation of about 5% more than when caused by DOX alone (from 60–65% to 70%). The use of C₆₀ as a DOX nanotransporter reduced the MT level increase induced by DOX. C₆₀ alone caused an increase of SOD1 concentration. On the other hand, it led to a decrease of SOD activity. C₆₀ in complex with DOX caused a decrease of the DOX-induced SOD activity level. Exposure of MCF-7 cells to DOX-C₆₀ complexes results in a decrease in viable cells and may become a new therapeutic approach to breast cancer. The effects of C₆₀ in complexes with DOX on MCF-7 cells included a decreased enzymatic (SOD activity) and nonenzymatic (MT) antioxidant status, thus indicating their prooxidant role in MCF-7 cells. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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18 pages, 3197 KiB

Open AccessArticle

The Efficacy of Amifostine against Multiple-Dose Doxorubicin-Induced Toxicity in Rats

by Vesna Jaćević, Viktorija Dragojević-Simić, Željka Tatomirović, Silva Dobrić, Dubravko Bokonjić, Aleksandra Kovačević, Eugenie Nepovimova, Martin Vališ and Kamil Kuča

Int. J. Mol. Sci. 2018, 19(8), 2370; https://doi.org/10.3390/ijms19082370 - 12 Aug 2018

Cited by 36 | Viewed by 4748

Abstract

Amifostine is well known cytoprotector which is efficient when administered before a wide range of antineoplastic agents. The aim of our study was to investigate amifostine effects on doxorubicin-induced toxic changes in rats. Amifostine (75 mg/kg ip) was given 30 min before each dose of doxorubicin (cumulatively 20 mg/kg ip, for 28 days). The animals’ whole-body, liver, and kidney weight, serum biochemical examination, as well as microscopic examination of bone marrow, peripheral blood, liver, and kidney, were done on day 56 of the study. Hepatic and renal alterations were carefully quantified by semiquantitative grading scales—hepatic and renal damage score, respectively. In amifostine-pretreated rats, the number of peripheral blood leukocytes was significantly higher in comparison to doxorubicin-only treated group, preferentially protecting neutrophils. In the same group of rats, hepatic and renal alterations associated with polymorphonuclear cell infiltrates were significantly less severe than those observed in animals receiving only doxorubicin. Our results showed that amifostine successfully protected rats against multiple-dose doxorubicin-induced toxicity by complex, and still not fully elucidated mechanisms of action. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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13 pages, 20456 KiB

Open AccessArticle

Rhein Induces Cell Death in HepaRG Cells through Cell Cycle Arrest and Apoptotic Pathway

by Longtai You, Xiaoxv Dong, Xingbin Yin, Chunjing Yang, Xin Leng, Wenping Wang and Jian Ni

Int. J. Mol. Sci. 2018, 19(4), 1060; https://doi.org/10.3390/ijms19041060 - 2 Apr 2018

Cited by 31 | Viewed by 4932

Abstract

Rhein, a naturally occurring active anthraquinone found abundantly in various medicinal and nutritional herbs, possesses a wide spectrum of pharmacological effects. Furthermore, previous studies have reported that rhein could induce hepatotoxicity in rats. However, its cytotoxicity and potential molecular mechanisms remain unclear. Therefore, the present study aimed to investigate the cytotoxicity of rhein on HepaRG cells and the underlying mechanisms of its cytotoxicity. Our results demonstrate, by 3-(4,5-dimethyl thiazol-2-yl-)-2,5-diphenyl tetrazolium bromide (MTT) and Annexin V-fluoresce isothiocyanate (FITC)/propidium iodide (PI) double-staining assays, that rhein significantly inhibited cell viability and induced apoptosis in HepaRG cells. Moreover, rhein treatment resulted in the generation of reactive oxygen species (ROS), loss of mitochondrial membrane potential (MMP), and S phase cell cycle arrest. The results of Western blotting showed that rhein treatment resulted in a significant increase in the protein levels of Fas, p53, p21, Bax, cleaved caspases-3, -8, -9, and poly(ADP-ribose)polymerase (PARP). The protein expression of Bcl-2, cyclin A, and cyclin-dependent kinase 2 (CDK 2) was decreased. In conclusion, these results suggest that rhein treatment could inhibit cell viability of HepaRG cells and induce cell death through cell cycle arrest in the S phase and activation of Fas- and mitochondrial-mediated pathways of apoptosis. These findings emphasize the need to assess the risk of exposure for humans to rhein. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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13 pages, 13190 KiB

Open AccessArticle

Cytotoxic and Apoptotic Activity of the Novel Harmine Derivative ZC-14 in Sf9 Cells

by Jingjing Zhang, Zhijun Zhang, Benshui Shu, Gaofeng Cui and Guohua Zhong

Int. J. Mol. Sci. 2018, 19(3), 811; https://doi.org/10.3390/ijms19030811 - 11 Mar 2018

Cited by 15 | Viewed by 4711

Abstract

Harmine, one of the natural β-carboline alkaloids extracted from Peganum harmala L., exhibits broad spectrum but limited insecticidal ability against many pests. So there is an urgent need to synthesize novel derivatives with high efficiency. In the present study, a new synthetic compound, [1-(2-naphthyl)-3-(2-thioxo-1,3,4-oxadiazol-5-yl) β-carboline] (ZC-14), showed a strong proliferation inhibition effect against the Spodoptera frugiperda Sf9 cell line in a dose-dependent manner. Simultaneously, apoptosis induced by 7.5 μg/mL ZC-14 was confirmed with physiological and biochemical evidence, including typical apoptosis characteristics with shrinkage, apoptotic bodies, nuclear condensation/fragmentation, a clear DNA ladder, and a series of apoptotic rates. In addition, mitochondria were confirmed to be involved in apoptosis induced by ZC-14 accompanied with the loss of mitochondrial membrane potential (Δψm), the release of cytochrome c from mitochondria into the cytosol and increased expression of cleaved-caspase-3. However, harmine could not induce apoptosis at the same concentration. In summary, these data indicated that compound ZC-14 has a higher cytotoxicity than harmine against Sf9 cells. Besides, it exhibited an anti-proliferative effect in Sf9 cells via inducing apoptosis in which the mitochondrial apoptotic pathway plays a crucial role. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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Review

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14 pages, 415 KiB

Open AccessReview

Biotherapeutics: Challenges and Opportunities for Predictive Toxicology of Monoclonal Antibodies

by Dale E. Johnson

Int. J. Mol. Sci. 2018, 19(11), 3685; https://doi.org/10.3390/ijms19113685 - 21 Nov 2018

Cited by 36 | Viewed by 7460

Abstract

Biotherapeutics are a rapidly growing portion of the total pharmaceutical market accounting for almost one-half of recent new drug approvals. A major portion of these approvals each year are monoclonal antibodies (mAbs). During development, non-clinical pharmacology and toxicology testing of mAbs differs from that done with chemical entities since these biotherapeutics are derived from a biological source and therefore the animal models must share the same epitopes (targets) as humans to elicit a pharmacological response. Mechanisms of toxicity of mAbs are both pharmacological and non-pharmacological in nature; however, standard in silico predictive toxicological methods used in research and development of chemical entities currently do not apply to these biotherapeutics. Challenges and potential opportunities exist for new methodologies to provide a more predictive program to assess and monitor potential adverse drug reactions of mAbs for specific patients before and during clinical trials and after market approval. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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20 pages, 2087 KiB

Open AccessReview

Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis

by Yunyi Wu and Guanyu Wang

Int. J. Mol. Sci. 2018, 19(8), 2358; https://doi.org/10.3390/ijms19082358 - 10 Aug 2018

Cited by 141 | Viewed by 17507

Abstract

Toxicity prediction is very important to public health. Among its many applications, toxicity prediction is essential to reduce the cost and labor of a drug’s preclinical and clinical trials, because a lot of drug evaluations (cellular, animal, and clinical) can be spared due to the predicted toxicity. In the era of Big Data and artificial intelligence, toxicity prediction can benefit from machine learning, which has been widely used in many fields such as natural language processing, speech recognition, image recognition, computational chemistry, and bioinformatics, with excellent performance. In this article, we review machine learning methods that have been applied to toxicity prediction, including deep learning, random forests, k-nearest neighbors, and support vector machines. We also discuss the input parameter to the machine learning algorithm, especially its shift from chemical structural description only to that combined with human transcriptome data analysis, which can greatly enhance prediction accuracy. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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20 pages, 607 KiB

Open AccessReview

Regulation of Organic Anion Transporting Polypeptides (OATP) 1B1- and OATP1B3-Mediated Transport: An Updated Review in the Context of OATP-Mediated Drug-Drug Interactions

by Khondoker Alam, Alexandra Crowe, Xueying Wang, Pengyue Zhang, Kai Ding, Lang Li and Wei Yue

Int. J. Mol. Sci. 2018, 19(3), 855; https://doi.org/10.3390/ijms19030855 - 14 Mar 2018

Cited by 73 | Viewed by 8442

Abstract

Organic anion transporting polypeptides (OATP) 1B1 and OATP1B3 are important hepatic transporters that mediate the uptake of many clinically important drugs, including statins from the blood into the liver. Reduced transport function of OATP1B1 and OATP1B3 can lead to clinically relevant drug-drug interactions (DDIs). Considering the importance of OATP1B1 and OATP1B3 in hepatic drug disposition, substantial efforts have been given on evaluating OATP1B1/1B3-mediated DDIs in order to avoid unwanted adverse effects of drugs that are OATP substrates due to their altered pharmacokinetics. Growing evidences suggest that the transport function of OATP1B1 and OATP1B3 can be regulated at various levels such as genetic variation, transcriptional and post-translational regulation. The present review summarizes the up to date information on the regulation of OATP1B1 and OATP1B3 transport function at different levels with a focus on potential impact on OATP-mediated DDIs. Full article

(This article belongs to the Special Issue Frontiers in Drug Toxicity Prediction)

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