• Toxicological Research
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• 제32권1호
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• pp.5-8
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• 2016

Risk assessment is the process of quantifying the probability of a harmful effect to individuals or populations from human activities. Mechanistic approaches to risk assessment have been generally referred to as systems toxicology. Systems toxicology makes use of advanced analytical and computational tools to integrate classical toxicology and quantitative analysis of large networks of molecular and functional changes occurring across multiple levels of biological organization. Three presentations including two case studies involving both in vitro and in vivo approaches described the current state of systems toxicology and the potential for its future application in chemical risk assessment.

• 한국동물위생학회지
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• 제42권2호
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• pp.73-83
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• 2019

Foot-and-Mouth Disease (FMD) is a highly contagious trans-boundary viral disease caused by FMD virus, which causes huge economic losses. FMDV infects cloven hoofed (two-toed) mammals such as cattle, sheep, goats, pigs and various wildlife species. To control the FMDV, it is necessary to understand the life cycle and the pathogenesis of FMDV in host. Especially, the protein-protein interaction between FMDV and host will help to understand the survival cycle of viruses in host cell and establish new therapeutic strategies. However, the computational approach for protein-protein interaction between FMDV and pig hosts have not been applied to studies of the onset mechanism of FMDV. In the present work, we have performed the prediction of the pig's proteins which interact with FMDV based on RNA-Seq data, protein sequence, and structure information. After identifying the virus-host interaction, we looked for meaningful pathways and anticipated changes in the host caused by infection with FMDV. A total of 78 proteins of pig were predicted as interacting with FMDV. The 156 interactions include 94 interactions predicted by sequence-based method and the 62 interactions predicted by structure-based method using domain information. The protein interaction network contained integrin as well as STYK1, VTCN1, IDO1, CDH3, SLA-DQB1, FER, and FGFR2 which were related to the up-regulation of inflammation and the down-regulation of cell adhesion and host defense systems such as macrophage and leukocytes. These results provide clues to the knowledge and mechanism of how FMDV affects the host cell.

• 한국독성학회:학술대회논문집
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• 한국독성학회 2005년도 춘계 국제심포지엄 및 학술대회
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• pp.193-193
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• 2005

• Molecular & Cellular Toxicology
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• 제3권sup4호
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• pp.35.4-35.4
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• 2007

• Environmental Analysis Health and Toxicology
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• 제23권4호
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• pp.231-245
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• 2008

Various methods for detecting changes in response behaviors of indicator specimens are presented for monitoring effects of toxic treatments. The movement patterns of individuals are quantitatively characterized by statistical (i.e., ANOVA, multivariate analysis) and computational (i.e., fractal dimension, Fourier transform) methods. Extraction of information in complex behavioral data is further illustrated by techniques in ecological informatics. Multi-Layer Perceptron and Self-Organizing Map are applied for detection and patterning of response behaviors of indicator specimens. The recent techniques of Wavelet analysis and line detection by Recurrent Self-Organizing Map are additionally discussed as an efficient tool for checking time-series movement data. Behavioral monitoring could be established as new methodology in integrative ecological assessment, tilling the gap between large-scale (e.g., community structure) and small-scale (e.g., molecular response) measurements.

• 한국환경독성학회:학술대회논문집
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• 한국환경독성학회 2000년도 추계심포지움 및 학술발표회:바이오모니터링 기법을 이용한 환경위해성 평가
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• pp.12-19
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• 2000

• 한국환경보건학회지
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• 제50권2호
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• pp.113-124
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• 2024

Background: The increasing need to minimize animal testing has sparked interest in alternative methods with more humane, cost-effective, and time-saving attributes. In particular, in silico-based computational toxicology is gaining prominence. Adverse outcome pathway (AOP) is a biological map depicting toxicological mechanisms, composed of molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). To understand toxicological mechanisms, predictive models are essential for AOP components in computational toxicology, including molecular structures. Objectives: This study reviewed the literature and investigated previous research cases related to AOP and in silico methodologies. We describe the results obtained from the analysis, including predictive techniques and approaches that can be used for future in silico-based alternative methods to animal testing using AOP. Methods: We analyzed in silico methods and databases used in the literature to identify trends in research on in silico prediction models. Results: We reviewed 26 studies related to AOP and in silico methodologies. The ToxCast/Tox21 database was commonly used for toxicity studies, and MIE was the most frequently used predictive factor among the AOP components. Machine learning was most widely used among prediction techniques, and various in silico methods, such as deep learning, molecular docking, and molecular dynamics, were also utilized. Conclusions: We analyzed the current research trends regarding in silico-based alternative methods for animal testing using AOPs. Developing predictive techniques that reflect toxicological mechanisms will be essential to replace animal testing with in silico methods. In the future, since the applicability of various predictive techniques is increasing, it will be necessary to continue monitoring the trend of predictive techniques and in silico-based approaches.

• Toxicological Research
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• 제32권1호
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• pp.9-14
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• 2016

The National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM) provides validation support for US Federal agencies and the US Tox21 interagency consortium, an interagency collaboration that is using high throughput screening (HTS) and other advanced approaches to better understand and predict chemical hazards to humans and the environment. The use of HTS data from assays relevant to the estrogen receptor signaling data pathway is used as an example of how HTS data can be combined with computational modeling to meet the needs of US agencies. As brief summary of US efforts in the areas of biologics testing, acute toxicity, and skin sensitization will also be provided.

• Molecular & Cellular Toxicology
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• 제3권2호
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• pp.145-149
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• 2007

Studies of relationship between structure and toxicity of azo dyes have been performed with comparative molecular field analysis (CoMFA) techniques. 3D QSTR analyses indicate that the steric and electrostatic interactions are important. The steric field based model gives strong correlation ($q^2$=0.57, $r^2$= 0.92). The steric field in conjunction with electrostatic field give more strong correlation ($q^2$=0.57, $r^2$=0.95). All study indicates that a bulky and electronegative group at benzene ring and a small group at position 3 of aniline ring might be significant to reduce the mutagenicity.

• Molecular & Cellular Toxicology
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• 제3권3호
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• pp.159-164
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• 2007

Stimulation of epidermal growth factor receptor (EGFR) is essential in signaling pathway of tumor cells. Thus, EGFR has intensely studied as an anticancer target. We developed hologram quantitative structure activity relationship (HQSAR) models for data set which consists of tricyclic azepine derivatives showing inhibitory activities for EGFR. The optimal HQSAR model was generated with fragment size of 6 to 7 while differentiating fragments having different atom and connectivity. The model showed cross-validated $q^2$ value of 0.61 and non-cross-validated $r^2$ value of 0.93. When the model was validated with an external set excluding one outlier, it gave predictive $r^2$ value of 0.43. The contribution maps generated from this model were used to interpret the atomic contribution of each atom to the overall inhibition activity. This can be used to find more efficient EGFR inhibitors.