QSAR-Models, Validation, and IIC-Paradox for Drug Toxicity
暂无分享,去创建一个
[1] O. Raevsky,et al. Acute toxicity evaluation upon intravenous injection into mice: interspecies correlations, lipophilicity parameters, and physicochemical descriptors , 2012, Pharmaceutical Chemistry Journal.
[2] Ivan Rusyn,et al. Modeling liver-related adverse effects of drugs using knearest neighbor quantitative structure-activity relationship method. , 2010, Chemical research in toxicology.
[3] Edwin J Matthews,et al. Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential. , 2015, Regulatory toxicology and pharmacology : RTP.
[4] Shadi Shayanfar,et al. Is regression through origin useful in external validation of QSAR models? , 2014, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.
[5] Ferran Sanz,et al. A Multiscale Simulation System for the Prediction of Drug-Induced Cardiotoxicity , 2011, J. Chem. Inf. Model..
[6] L. Lin. Assay Validation Using the Concordance Correlation Coefficient , 1992 .
[7] Emilio Benfenati,et al. The application of new HARD-descriptor available from the CORAL software to building up NOAEL models. , 2017, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.
[8] M. Gobbi,et al. Monte Carlo method for predicting of cardiac toxicity: hERG blocker compounds. , 2016, Toxicology letters.
[9] T. Khayamian,et al. Mechanistic‐Based Descriptors for QSAR Study of Psychotropic Drug Toxicity , 2008, Chemical biology & drug design.
[10] Andrey A Toropov,et al. The index of ideality of correlation: A criterion of predictive potential of QSPR/QSAR models? , 2017, Mutation research.
[11] Stephan Krähenbühl,et al. The hepatotoxic potential of protein kinase inhibitors predicted with Random Forest and Artificial Neural Networks. , 2018, Toxicology letters.
[13] Giuseppina C. Gini,et al. CORAL: Quantitative structure–activity relationship models for estimating toxicity of organic compounds in rats , 2011, J. Comput. Chem..
[14] Andrey A Toropov,et al. CORAL software: prediction of carcinogenicity of drugs by means of the Monte Carlo method. , 2014, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.
[15] Jerzy Leszczynski,et al. Comprehension of drug toxicity: Software and databases , 2014, Comput. Biol. Medicine.
[16] K. Roy,et al. Predictive toxicity modelling of benzodiazepine drugs using multiple in silico approaches: descriptor-based QSTR, group-based QSTR and 3D-toxicophore mapping , 2015 .
[17] Bernd Beck,et al. Industrial applications of in silico ADMET , 2014, Journal of Molecular Modeling.
[18] G. Gini,et al. CORAL: binary classifications (active/inactive) for Liver-Related Adverse Effects of Drugs. , 2012, Current drug safety.
[19] Feixiong Cheng,et al. In silico ADMET prediction: recent advances, current challenges and future trends. , 2013, Current topics in medicinal chemistry.
[20] J. Wong,et al. Hepatitis C , 2012, PharmacoEconomics.
[21] Matthew D. Segall,et al. ADMET Property Prediction: The State of the Art and Current Challenges , 2006 .
[22] Quantitative structure–retention relationship study of analgesic drugs by application of combined data splitting-feature selection strategy and genetic algorithm-partial least square , 2012, Journal of the Iranian Chemical Society.
[23] John C Dearden,et al. In silico prediction of ADMET properties: how far have we come? , 2007, Expert opinion on drug metabolism & toxicology.
[24] Kunal Roy,et al. The rm2 metrics and regression through origin approach: reliable and useful validation tools for predictive QSAR models (Commentary on 'Is regression through origin useful in external validation of QSAR models?'). , 2014, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.
[25] Ralph Kühne,et al. Quantitative and qualitative models for carcinogenicity prediction for non-congeneric chemicals using CP ANN method for regulatory uses , 2010, Molecular Diversity.
[26] F. Sun,et al. Metabolic changes in rat serum after administration of suberoylanilide hydroxamic acid and discriminated by SVM , 2017, Human & experimental toxicology.
[27] Kunal Roy,et al. Electrotopological state atom (E-state) index in drug design, QSAR, property prediction and toxicity assessment. , 2012, Current computer-aided drug design.
[28] S. Gayen,et al. Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization , 2017, SAR and QSAR in environmental research.
[29] Yu Li,et al. Modified neonicotinoid insecticide with bi-directional selective toxicity and drug resistance. , 2018, Ecotoxicology and environmental safety.
[30] Arctic Teleost Fishes with Canceled Accelerated Senescence Program Are a Potential Source of Stress Protectors and Cancer Drugs , 2005, Biology Bulletin.
[31] E. Matthews,et al. Prediction of drug-related cardiac adverse effects in humans--B: use of QSAR programs for early detection of drug-induced cardiac toxicities. , 2010, Regulatory toxicology and pharmacology : RTP.
[32] Sebastian Hoffmann,et al. Food for thought ... on in silico methods in toxicology. , 2009, ALTEX.
[33] A. Tropsha,et al. Beware of q2! , 2002, Journal of molecular graphics & modelling.
[34] David Weininger,et al. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules , 1988, J. Chem. Inf. Comput. Sci..
[35] A. Toropova,et al. The Monte Carlo technique as a tool to predict LOAEL. , 2016, European journal of medicinal chemistry.
[36] A A Toropov,et al. Aconitum and Delphinium Diterpenoid Alkaloids of Local Anesthetic Activity: Comparative QSAR Analysis Based on GA-MLRA/PLS and Optimal Descriptors Approach , 2014, Journal of environmental science and health. Part C, Environmental carcinogenesis & ecotoxicology reviews.
[37] Dennis H. Rouvray,et al. Similarity studies. 1. The necessity of analogies in the development of science , 1994, J. Chem. Inf. Comput. Sci..
[38] M. Çetin,et al. Protective effects of cytokine combinations against the apoptotic activity of glucocorticoids on CD34+ hematopoietic stem/progenitor cells , 2019, Cytotechnology.
[39] A. Gómez-Lumbreras,et al. Psychotropic Drugs and Liver Toxicity. , 2017, American journal of therapeutics.
[40] Shivani Patel,et al. Molecular docking, QSAR and ADMET based mining of natural compounds against prime targets of HIV , 2019, Journal of biomolecular structure & dynamics.
[41] Kunal Roy,et al. Development and validation of a robust QSAR model for prediction of carcinogenicity of drugs. , 2011, Indian journal of biochemistry & biophysics.
[42] J. Holopainen,et al. Pure Glaucoma Drugs Are Toxic to Immortalized Human Corneal Epithelial Cells, but They Do Not Destabilize Lipid Membranes , 2017, Cornea.
[43] Hui Zhang,et al. Applications of Machine Learning Methods in Drug Toxicity Prediction. , 2018, Current topics in medicinal chemistry.
[44] M. Bouachrine,et al. Antibacterial study of 3-(2-amino-6-phenylpyrimidin-4-yl)-N-cyclopropyl-1-methyl-1H-indole-2-carboxamide derivatives: CoMFA, CoMSIA analyses, molecular docking and ADMET properties prediction , 2019, Journal of Molecular Structure.
[45] Paola Gramatica,et al. Real External Predictivity of QSAR Models: How To Evaluate It? Comparison of Different Validation Criteria and Proposal of Using the Concordance Correlation Coefficient , 2011, J. Chem. Inf. Model..