Structure-activity correlations toxicity

Leo, A.J. (1975) Calculation of partition coefficients useful in the evaluation of relative hazards of various chemicals in the environment. In Symposium on Structure-Activity Correlations in Studies of Toxicity and Bioconcentration with Aquatic Organisms. G.D. Veith and D.E. Konasewich, Editors, International Joint Commission, Ontario, Canada. 

Kimerle, R.A., R.D. Swisher, and R.M. Schroeder-Comotto. 1975. Surfactant structure and aquatic toxicity. In Proc. IJC Symposium on Structure Activity Correlations in Studies on Toxicity and Bioconcentration with Aquatic Organisms, pp. 22-25, March 11-13, 1975. 

Structure-activity correlation studies have shown that polarity is not important for the toxicity of pyrethroids, while receptor-substrate interactions due to molecular size, shape and electronic effects are important and gave good correlation with bioactivity values (Briggs et al., 1976 Lee, 1976). 

Inter-laboratory toxicity data give structure-activity correlations of sufficient precision to classify mechanism and indicate the mode of death. Stronger correlations would be expected by using indicator variables for gender, age, size, etc., but these are unlikely to enhance the mechanistic description. Good analyses were achieved... 

Acute toxicity in fish, bioconcentration in fish, chlorinated hydrocarbons, chlorinated phenols, molecular connectivity indices, molecular topology, nonempirical quantitative modelling of environmental properties, polycyclic aromatic hydrocarbons, quantitative structure activity correlations, soil sorption, Pimephales promelas, fathead minnow, connectivity indices, sheepshead minnows, Cyprinodon variegatus. 

Structure activity correlations for analogs of batrachotoxin have been studied to a limited extent. Toxicity in white mice (Table 4 at the end of this section) (251), effects on nerve-striated muscle preparations (268), cardiac preparations (233), ATPase (79), and eel electroplax (cited in 5) show similar profiles with the different analogs. The substitution pattern on the pyrrole moiety is important. The relative order of activity of certain substituted pyrrole carboxylates in a neuromuscular preparation as depolarizing agents was as follows Batrachotoxin > homobatrachotoxin =... 

In 1868 two Scottish scientists, Crum Brown and Fraser [4] recognized that a relation exists between the physiological action of a substance and its chemical composition and constitution. That recognition was in effect the birth of the science that has come to be known as quantitative structure-activity relationship (QSAR) studies a QSAR is a mathematical equation that relates a biological or other property to structural and/or physicochemical properties of a series of (usually) related compounds. Shortly afterwards, Richardson [5] showed that the narcotic effect of primary aliphatic alcohols varied with their molecular weight, and in 1893 Richet [6] observed that the toxicities of a variety of simple polar chemicals such as alcohols, ethers, and ketones were inversely correlated with their aqueous solubilities. Probably the best known of the very early work in the field was that of Overton [7] and Meyer [8], who found that the narcotic effect of simple chemicals increased with their oil-water partition coefficient and postulated that this reflected the partitioning of a chemical between the aqueous exobiophase and a lipophilic receptor. This, as it turned out, was most prescient, for about 70% of published QSARs contain a term relating to partition coefficient [9]. 

OASIS (optimized approach based on structural indices set) has been developed by Mekenyan and co-workers [87]. Given the activities or toxicities of a set of compounds, it generates large numbers of structural indices for each and develops QSAR correlations. The approach has been used to model the acute toxicity of industrial chemicals [88]. It is claimed [89] that the method can be of use in elucidating mechanisms of action. 

Govers, H., Ruepert, C., Aiking, H. (1984) Quantitative structure-activity relationships for polycyclic aromatic hydrocarbons Correlation between molecular connectivity, physico-chemical properties, bioconcentration and toxicity in Daphnia pulex. Chemosphere 13, 227-236. 

The applicability of Eq. (45) to a broad range of biological (i.e., toxic, geno-toxic) structure-activity relationships has been demonstrated convincingly by Hansch and associates and many others in the years since 1964 [60-62, 80, 120-122, 160, 161, 195, 204-208, 281-285, 289, 296-298]. The success of this model led to its generalization to include additional parameters in attempts to minimize residual variance in such correlations, a wide variety of physicochemical parameters and properties, structural and topological features, molecular orbital indices, and for constant but for theoretically unaccountable features, indicator or dummy variables (1 or 0) have been employed. A widespread use of Eq. (45) has provided an important stimulus for the review and extension of established scales of substituent effects, and even for the development of new ones. It should be cautioned here, however, that the general validity or indeed the need for these latter scales has not been established. 

Reasonably good testing methods exist for acute toxicity. The tests use surrogate animals, and the correlation to humans is the weakest element. The quality of predictive modehng for acute effects based on SAR (Structure Activity Relationships), is only modest. For chronic effects, testing with surrogates for humans is modestly good, particularly for cancer. Tests for chronic toxicity in animals are only fair and for... 

The toxicology of a solvent is determined by many factors, such as bioavailabihty, metabolism, and the presence of structural features that may attenuate or enhance the reactivity of the parent molecule. Despite the structure-activity data available for many classes of commercial chemical substances, chemists have not recognized the use of structure-activity relations as a rational approach for choosing or designing new, less toxic commercial chemical substances. With qualitative structure-activity relationships, comparing the structures of the substances in the series with corresponding effects on the toxicity makes the correlation between toxic effect and structure. Through these, it may then be possible to predict a relationship between structure and toxicity... 

With qualitative structure-activity relationships (SARs), the correlation of toxic effect with structure is made by visual comparison of the structures of the chemicals in a series of congeneric substances and the corresponding effects their structural differences have on toxic potency, for example, as represented by their LD50 values. From qualitative examination of structure-activity data the chemist may be able to see a relationship between structure and toxicity, and identify the least toxic members of the class as possible commercial alternatives to the more toxic members. 

Miller, K.A., Suresh Kumar, E.V.K., Wood, S.J., Cromer, J.R., Datta, A., David, S.A. Lipopolysaccharide sequestrants structural correlates of activity and toxicity in novel acyl-homospermines. J Med Chem 48 (2005) 2589-2599. 

Another approach to predict toxicity is basing on structure-activity-relationship (SAR), which means the qualitative relationship between a specific chemical structure and their biological/toxicological activity, e.g. the expert system DEREK is based on SAR prediction. In SAR the occurrence of specific substructures in a molecule are correlated to be responsible and necessary for a biological/toxicological activity. 

Toxicity, as with all forms of biological activity, is a result of the molecular structure of the chemical concerned. Given that fact, the computational chemist is presented with a problem that is, at least theoretically, soluble. The tools that have been applied so successfully to rationalizing biological activity in terms of chemical structure can also be used for correlating toxicity with various structural parameters.24 Such structural descriptors may be physicochemical values,25 functions of molecular size and shape, molecular connectivity, and numbers of atoms, or they may be quantum-chemical parameters relating to electronic distribution within the molecule.26-27... 

Based on the earlier work of Meyer and Overton, who showed that the narcotic effect of anesthetics was related to their oil/water partition coefficients, Hansch and his co-workers have demonstrated unequivocally the importance of hydrophobic parameters such as log P (where P is, usually, the octanol/water partition coefficient) in QSAR analysis.28 The so-called classical QSAR approach, pioneered by Hansch, involves stepwise multiple regression analysis (MRA) in the generation of activity correlations with structural descriptors, such as physicochemical parameters (log P, molar refractivity, etc.) or substituent constants such as ir, a, and Es (where these represent hydrophobic, electronic, and steric effects, respectively). The Hansch approach has been very successful in accurately predicting effects in many biological systems, some of which have been subsequently rationalized by inspection of the three-dimensional structures of receptor proteins.28 The use of log P (and its associated substituent parameter, tr) is very important in toxicity,29-32 as well as in other forms of bioactivity, because of the role of hydrophobicity in molecular transport across cell membranes and other biological barriers. 

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