Computational Toxicology Methods and Protocols
Computational Toxicology Methods and Protocols
edited by Orazio Nicolotti.
- 1st edition 2018
- 1 recurso en línea (XVI, 587 páginas) 177 ilustraciones, 115 ilustraciones a color
- Methods in Molecular Biology 1800 1940-6029 .
Molecular Descriptors For Structure-Activity Applications: A Hands-On Approach -- The OECD QSAR Toolbox Starts Its Second Decade -- QSAR: What Else? -- (Q)SARs as Adaptations to REACH Information Requirements -- Machine Learning Methods In Computational Toxicology -- Applicability Domain: A Step Toward Confident Predictions And Decidability for QSAR Modeling -- Molecular Similarity In Computational Toxicology -- Molecular Docking for Predictive Toxicology -- Criteria and Application on the use of Non-Testing Methods within a Weight of Evidence Strategy -- Characterization and Management of Uncertainties in Toxicological Risk Assessment: Examples from the Opinions of the European Food Safety Authority -- Computational Toxicology and Drug Discovery -- Approaching Pharmacological Space: Events and Components -- Computational Toxicology Methods in Chemical Library Design and High-Throughput Screening Hit Validation -- Enalos Suite: New Cheminformatics Platform for Drug Discovery and Computational Toxicology -- Ion Channels In Drug Discovery and Safety Pharmacology -- Computational Approaches in Multi-Target Drug Discovery -- Nano-Formulations for Drug Delivery: Safety, Toxicity, and Efficacy -- Toxicity Potential Of Nutraceuticals -- Impact of Pharmaceuticals on the Environment: Risk Assessment using QSAR Modeling Approach -- (Q)SAR Methods for Predicting Genotoxicity and Carcinogenicity: Scientific Rationale and Regulatory Frameworks -- Stem Cell-Based Methods to Predict Developmental Chemical Toxicity -- Predicting Chemically-Induced Skin Sensitisation by using In Chemico/In Vitro Methods -- Hepatotoxicity Prediction by Systems Biology Modeling of Disturbed Metabolic Pathways using Gene Expression Data -- Non-Test Methods to Predict Acute Toxicity: State of Art for Applications of In Silico Methods -- Predictive Systems Toxicology -- Chemoinformatic Approach to Assess Toxicity of Ionic Liquids -- Prediction of Biochemical Endpoints by the CORAL Software: Prejudices, Paradoxes, and Results.
This volume explores techniques that are currently used to understand solid target-specific models in computational toxicology. The chapters are divided into four sections and discuss topics such as molecular descriptors, QSAR and read-across; molecular and data modeling techniques to comply both with scientific and regulatory sides; computational toxicology in drug discovery; and strategies on how to predict various human-health toxicology endpoints. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the methods and software tools used, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, Computational Toxicology: Methods and Protocols is a valuable resource for researchers who are interested in learning more about this expanding field.
9781493978991
10.1007/978-1-4939-7899-1 doi
Molecular Descriptors For Structure-Activity Applications: A Hands-On Approach -- The OECD QSAR Toolbox Starts Its Second Decade -- QSAR: What Else? -- (Q)SARs as Adaptations to REACH Information Requirements -- Machine Learning Methods In Computational Toxicology -- Applicability Domain: A Step Toward Confident Predictions And Decidability for QSAR Modeling -- Molecular Similarity In Computational Toxicology -- Molecular Docking for Predictive Toxicology -- Criteria and Application on the use of Non-Testing Methods within a Weight of Evidence Strategy -- Characterization and Management of Uncertainties in Toxicological Risk Assessment: Examples from the Opinions of the European Food Safety Authority -- Computational Toxicology and Drug Discovery -- Approaching Pharmacological Space: Events and Components -- Computational Toxicology Methods in Chemical Library Design and High-Throughput Screening Hit Validation -- Enalos Suite: New Cheminformatics Platform for Drug Discovery and Computational Toxicology -- Ion Channels In Drug Discovery and Safety Pharmacology -- Computational Approaches in Multi-Target Drug Discovery -- Nano-Formulations for Drug Delivery: Safety, Toxicity, and Efficacy -- Toxicity Potential Of Nutraceuticals -- Impact of Pharmaceuticals on the Environment: Risk Assessment using QSAR Modeling Approach -- (Q)SAR Methods for Predicting Genotoxicity and Carcinogenicity: Scientific Rationale and Regulatory Frameworks -- Stem Cell-Based Methods to Predict Developmental Chemical Toxicity -- Predicting Chemically-Induced Skin Sensitisation by using In Chemico/In Vitro Methods -- Hepatotoxicity Prediction by Systems Biology Modeling of Disturbed Metabolic Pathways using Gene Expression Data -- Non-Test Methods to Predict Acute Toxicity: State of Art for Applications of In Silico Methods -- Predictive Systems Toxicology -- Chemoinformatic Approach to Assess Toxicity of Ionic Liquids -- Prediction of Biochemical Endpoints by the CORAL Software: Prejudices, Paradoxes, and Results.
This volume explores techniques that are currently used to understand solid target-specific models in computational toxicology. The chapters are divided into four sections and discuss topics such as molecular descriptors, QSAR and read-across; molecular and data modeling techniques to comply both with scientific and regulatory sides; computational toxicology in drug discovery; and strategies on how to predict various human-health toxicology endpoints. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the methods and software tools used, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, Computational Toxicology: Methods and Protocols is a valuable resource for researchers who are interested in learning more about this expanding field.
9781493978991
10.1007/978-1-4939-7899-1 doi