Quantitative structure-toxicity relationships

Ridings JE, Manallack DT, Saunders MR, Baldwin JA, Livingstone DJ. Multivariate quantitative structure-toxicity relationships in a series of dopamine mimetics. Toxicol 1992 76 209-17. 

Besides the applications of the electrophilicity index mentioned in the review article [40], following recent applications and developments have been observed, including relationship between basicity and nucleophilicity [64], 3D-quantitative structure activity analysis [65], Quantitative Structure-Toxicity Relationship (QSTR) [66], redox potential [67,68], Woodward-Hoffmann rules [69], Michael-type reactions [70], Sn2 reactions [71], multiphilic descriptions [72], etc. Molecular systems include silylenes [73], heterocyclohexanones [74], pyrido-di-indoles [65], bipyridine [75], aromatic and heterocyclic sulfonamides [76], substituted nitrenes and phosphi-nidenes [77], first-row transition metal ions [67], triruthenium ring core structures [78], benzhydryl derivatives [79], multivalent superatoms [80], nitrobenzodifuroxan [70], dialkylpyridinium ions [81], dioxins [82], arsenosugars and thioarsenicals [83], dynamic properties of clusters and nanostructures [84], porphyrin compounds [85-87], and so on. 

Such essential limitations may markedly decrease the reliability and predictive capacity of quantitative structure-toxicity relationships (STRs) in haloalkenes and all other classes of toxic xenobiotics, but recognition of limitations does not suppress the need for predictive tools. In fact, any approach, empirical or mechanistic, that is able to uncover qualitative STR trends and to assign a priori labels of potential toxicity is certainly welcome. 

TOPKAT Quantitative structure toxicity relationship (QSTR) models for assessing various measures of toxicity... 

A number of approaches are available or under development to predict metabolism, including expert systems such as MetabolExpert (Compudrug), Meteor (Lhasa), MetaFore [42] and the databases Metabolite (MDL) and Metabolism (Synopsys) [43]. Ultimately such programs may be linked to computer-aided toxicity prediction based on quantitative structure-toxicity relationships and expert systems for toxicity evaluation such as DEREK (Lhasa) (see also Chapter 8) [44]. 

P.J. (2005) Application of quantitative structure-toxicity relationships for acute NSAID cytotoxicity in rat hepatocytes. Chem.-Biol. Interact., 152, 177-191. 

No quantitative structure-toxicity relationship could be determined, but the MOA and the mechanism of toxicity (MOT) were not identical and it, therefore, was possible to develop high-potency, low-toxicity antimalarials. 

Nendza, M., Seydel, J.K. (1988) Quantitative structure-toxicity relationship for ecotoxicologically relevant biotest systems and chemicals. Chemosphere 17, 1585-1602. 

Sixt S, Altschuh J, Briiggemann R (1995) Quantitative structure-toxicity relationships for 80 chlorinated compounds using quantum chemical descriptors. Chemosphere 30 2397-2414... 

Gombar, V.K., Enslein, K. and Blake, B.W. (1995). Assessment of Developmental Toxicity Potential of Chemicals by Quantitative Structure-Toxicity Relationship Models. Chemosphere, 31, 2499-2510. 

Norinder, U. (1992). Experimental Design Based Quantitative Structure Toxicity Relationship of Some Local Anesthetics Using the Pis Method. J.Appl. Toxicol, 12,143-147. 

Ridings, J.E., ManaUack, D.T., Saunders, M.R., Baldwin, J.A. and Livingstone, D.J. (1992). Multivariate Quantitative Structure-Toxicity Relationships in a Series of Dopamine Mimetics. Toxicology, 76, 209-217. 

Sabljic, A. (1983). Quantitative Structure-Toxicity Relationship of Chlorinated Compounds A Molecular Connectivity Investigation. Bull.Environ.Contam.ToxicoL, 30,80-83. 

Sixt, S., Altschuh, J. and Brtiggemann, R. (1995). Quantitative Structure-Toxicity Relationships for 80 Chlorinated Compounds Using Quantum Chemical Descriptors. Chemosphere, 30, 2397-2414. 

Siraki AG, Chevaldina T, Moridani MY, O Brien PJ. Quantitative structure-toxicity relationships by accelerated cytotoxicity mechanism screening. Curr Opin Drug Discov Devel 2004 7 118-25. 

Panaye A, Fan BT, Doucet JP, Yao XJ, Zhang RS, et al. Quantitative structure-toxicity relationships (QSTRs) A comparative study of various nonlinear methods. General regression neural network, radial basis function neural network and support vector machine in predicting toxicity of nitro- and cyano- aromatics to Tetrahymena pyriformis. SAR QSAR Environ Res 2006 17 75-91. 

Gombar VK, Enslein K, Blake BW. Assessment of developmental toxicity potential of chemicals by quantitative structure-toxicity relationship models. Chemo-sphere 1995 31 2499-510. 

Estrada, E., Molina, E. and Uriarte, E. (2001h) Quantitative structure-toxicity relationships using... 

Estrada, E., Uriarte, E., Gutierrez, Y. and Gonzalez, H. (2003) Quantitative structure-toxicity relationships using TOPS-MODE. 3. Structural factors influencing the permeability of commercial solvents through living human skin. SAR el QSAR Environ. Res., 14, 145-163. 

Katritzky, A.R., Tatham, D.B. and Maran, U. (2001) Theoretical descriptors for the correlation of aquatic toxicity of environmental pollutants by quantitative structure-toxicity relationships. 

Normder, U. (1992) Experimental design based quantitative structure toxicity relationship of some local anesthetics using the PLS method. J. Appl Toxicol, 12, 143-147. 

Warne, M.S., Osborn, D., Lindon, J.C. and Nicholson, J.K. (1999) Quantitative structure-toxicity relationships for halogenated substituted-benzenes to Vibrio jischeri, using atom-based semi-empirical molecular-orbital descriptors. Chemosphere, 38, 3357-3382. 

Girones X, Amat L, Carbo-Dorca R. Using molecular quantum similarity measures as descriptors in quantitative structure-toxicity relationships. SAR QSAR Environ Res 1999 10 545-556. 

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