In silico methods for physiologically based biokinetic models describing bioactivation and detoxification of coumarin and estragole: Implications for risk assessment

2009 ◽  
Vol 54 (2) ◽  
pp. 195-207 ◽  
Author(s):  
Ivonne M. C. M. Rietjens ◽  
Ans Punt ◽  
Benoît Schilter ◽  
Gabriele Scholz ◽  
Thierry Delatour ◽  
...  
Keyword(s):  
Risk Assessment ◽  
In Silico ◽  
Physiologically Based ◽  
In Silico Methods

scholarly journals Comparison of Seven in Silico methods for Evaluating of Ecotoxicological Acute Toxicity of Daphnia magna and Pimephales promelas: Case study on Chinese Priority Controlled Chemicals

2019 ◽  
Author(s):  
Linjun Zhou ◽  
Deling Fan ◽  
Wei Yin ◽  
Wen Gu ◽  
Zhen Wang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Acute Toxicity ◽  
Daphnia Magna ◽  
In Silico ◽  
Aquatic Toxicity ◽  
Pimephales Promelas ◽  
Chemical Screening ◽  
Structure Activity ◽  
Acute Aquatic Toxicity ◽  
In Silico Methods

Abstract Background: The acute toxicity on aquatic organisms are indispensable parameters in the ecological risk assessment priority chemical screening process (e.g. persistent, bioaccumulative and toxic chemicals). Currently, a number of predictive models for aquatic toxicity are available, however, the accuracy of in silico tools in priority assessment and risk assessment still remains to be further studied. Herein, this study evaluated the performance of seven Quantitative Structure–Activity Relationship (QSAR) in silico methods (Danish QSAR Database, Ecological Structure Activity Relationships, KAshinhou Tool for Ecotoxicity on PAS, Toxicity Estimation Software Tool, QSAR Toolbox, Read Across, and Virtual models for property Evaluation of chemicals within a Global Architecture) for assessing acute aquatic toxicity to Daphnia magna and Pimephales promelas using the first batch list of Priority Controlled Chemicals in China. Results: Based on the values for the median lethal dose and the US Environmental Protection Agency’s acute aquatic toxicity categories of concern, the acute toxicity grade was classified into six categories. According to the comparative prediction results, the accuracy of the Daphnia magna toxicity categories prediction was 25%–56%, the correlation coefficient ranged from 0.1236 to 0.6349, and the correlation coefficients of the applicability domain were 0.040 and 0.5148. The corresponding values for the Pimephales promelas toxicity categories prediction were 22%–44%, 0.1495–0.4144, 0.2156 and 0.6793. Conclusion: As the structure of chemicals of first batch list of Priority Controlled Chemicals in China are complex, the accuracy of model prediction is low, which depends on the quality of the constructed model and application domain. Although in silico methods can be used to preliminarily estimate aquatic toxicity, experimental data validation is still required for prioritizing environmental hazards assessments and risk assessments.

Elucidation of Phosphodiesterase-1 Inhibitory Effect of Some Selected Natural Polyphenolics Using In Vitro and In Silico Methods

2016 ◽  
Vol 17 (4) ◽  
pp. 412-417 ◽  
Author(s):  
Abdur Rauf ◽  
Ilkay Erdogan Orhan ◽  
Abdulselam Ertas ◽  
Hamdi Temel ◽  
Taibi Ben Hadda ◽  
...  
Keyword(s):  
In Silico ◽  
Inhibitory Effect ◽  
In Silico Methods

Prediction of Drug-Drug Interactions Related to Inhibition or Induction of Drug-Metabolizing Enzymes

2019 ◽  
Vol 19 (5) ◽  
pp. 319-336 ◽  
Author(s):  
Alexander V. Dmitriev ◽  
Alexey A. Lagunin ◽  
Dmitry А. Karasev ◽  
Anastasia V. Rudik ◽  
Pavel V. Pogodin ◽  
...  
Keyword(s):  
In Silico ◽  
Computational Models ◽  
Field Analysis ◽  
Pharmaceutical Chemistry ◽  
Sources Of Information ◽  
Metabolizing Enzymes ◽  
Physiologically Based Pharmacokinetic ◽  
Pharmacophore Models ◽  
Drug Metabolising Enzymes ◽  
In Silico Methods

Drug-drug interaction (DDI) is the phenomenon of alteration of the pharmacological activity of a drug(s) when another drug(s) is co-administered in cases of so-called polypharmacy. There are three types of DDIs: pharmacokinetic (PK), pharmacodynamic, and pharmaceutical. PK is the most frequent type of DDI, which often appears as a result of the inhibition or induction of drug-metabolising enzymes (DME). In this review, we summarise in silico methods that may be applied for the prediction of the inhibition or induction of DMEs and describe appropriate computational methods for DDI prediction, showing the current situation and perspectives of these approaches in medicinal and pharmaceutical chemistry. We review sources of information on DDI, which can be used in pharmaceutical investigations and medicinal practice and/or for the creation of computational models. The problem of the inaccuracy and redundancy of these data are discussed. We provide information on the state-of-the-art physiologically- based pharmacokinetic modelling (PBPK) approaches and DME-based in silico methods. In the section on ligand-based methods, we describe pharmacophore models, molecular field analysis, quantitative structure-activity relationships (QSAR), and similarity analysis applied to the prediction of DDI related to the inhibition or induction of DME. In conclusion, we discuss the problems of DDI severity assessment, mention factors that influence severity, and highlight the issues, perspectives and practical using of in silico methods.

scholarly journals Energetics of LOHC: Structure-Property Relationships from Network of Thermochemical Experiments and in Silico Methods

Hydrogen ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 101-121
Author(s):  
Sergey P. Verevkin ◽  
Vladimir N. Emel’yanenko ◽  
Riko Siewert ◽  
Aleksey A. Pimerzin
Keyword(s):  
In Silico ◽  
Quantum Chemical ◽  
Structure Property ◽  
Chemical Methods ◽  
Key Technology ◽  
Structure Property Relationships ◽  
Quantum Chemical Methods ◽  
Dehydrogenation Reactions ◽  
Storage Technologies ◽  
In Silico Methods

The storage of hydrogen is the key technology for a sustainable future. We developed an in silico procedure, which is based on the combination of experimental and quantum-chemical methods. This method was used to evaluate energetic parameters for hydrogenation/dehydrogenation reactions of various pyrazine derivatives as a seminal liquid organic hydrogen carriers (LOHC), that are involved in the hydrogen storage technologies. With this in silico tool, the tempo of the reliable search for suitable LOHC candidates will accelerate dramatically, leading to the design and development of efficient materials for various niche applications.

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