610
Chem. Res. Toxicol. 1996, 9, 610-613
Toxicity of Organic Chemicals to Fathead Minnow: A United Quantitative Structure-Activity Relationship Model and Its Application Liu Feng, Shuokui Han, Yuanhui Zhao, Liangsheng Wang,* and Jingwen Chen Department of Environmental Science and Engineering, Nanjing University, Nanjing 210093, P. R. China Received September 25, 1995X
A general and practical relation has been established between structure and activity of organic chemicals based on target theory. This relation was tested by examining the correlations between the acute toxicity and the physicochemical properties for fathead minnow, which showed that this relation can explain the observed toxicity data and phenomena successfully. The equations are then used to estimated the acute toxicity data of organic chemicals, and the predicted values are close to observed values.
Introduction As repeatedly shown, there are two types of toxicological mechanisms: reactive toxicity and nonreactive toxicity. Reactive toxicity is associated with a specific reaction such as a chemical reaction with an enzyme or inhibition of a metabolic pathway (1, 2). The mechanism by which a large class of organic chemicals exert toxic effects on aquatic organisms has been described as a nonreactive toxicity behavior, wherein toxic effects can be shown by any organic nonelectrolyte if present in sufficient concentration, and pharmacokinetics factors like transport and partitioning are rate controlling. As most nonreactive toxicological quantitative structure-activity relationships (QSARs)1 of simple molecules showed (3), it is usually considered to involve inhibition of physiological activity by saturation of lipophilic membranes, leading to hindrance of electrolyte transport across those membranes, and hence to anesthesia, narcosis, and in the extreme, death. Based on this hypothesis, the solvatochromic method developed by Kamlet et al. has been used successfully to describe the acute toxicity of organic chemicals to different aquatic organisms (4, 5). However, an opposing view has also been proposed by other workers (6, 7), which suggested that toxicity occurs as a result of a toxicant binding to specific receptor sites, of specific dimensions, that are located in hydrophobic regions of proteins found in nerve membranes. As the well-known Hansch equation showed (6), the biological response was related to the transport of the chemicals from water phase to biophase alternatively and the transaction between the chemicals and the specific receptor sites. Recently, the research on toxicokinetics gave strong evidence for this theory (8). Based on this theory, we have established a theoretical equation to explain the toxicity mechanism successfully (9). Here, a followed work was presented, which gave a clear physical implica* Address correspondence to this author at the Department of Environmental Science and Engineering, Nanjing University, Nanjing 210093, P. R. China. FAX: 0086-025-3317761; e-mail: Postche1@nju. edu.cn. X Abstract published in Advance ACS Abstracts, March 15, 1996. 1 Abbreviations: QSAR(s), quantitative structure-activity relationship(s); HBD, hydrogen bond donor; HBA, hydrogen bond acceptor; LSER, linear solvation energy relationship.
0893-228x/96/2709-0610$12.00/0
tion for the reaction equilibrium constant and proposed a general and practical model for the toxicity to aquatic organism.
Materials and Methods A total of 54 organic chemicals were used as the probe compounds for the QSAR model proposed in this paper, including alkylbenzenes, chlorobenzenes, phenols, ketones, and others. They are listed in Table 1 together with their physicochemical parameters. The octanol-water partition coefficients (10, 11) and the solvatochromic parameters (10) were collected from the literature. The acute toxicities (96hr-LC50, mol/L) of these chemicals to fathead minnow (Pimephales promelas) were considered, which were obtained from Veith et al. (12) and Hall et al. (13), and are summarized in Table 1. A detailed description for the experimental procedures to determine these toxicity data have been done by Veith and Hall (12, 13). Only the compounds whose solvatochromic parameters were available were selected. Statistical analyses were conducted using the STATGRAPHICS program on a PC AST-386 computer. A stepwise linear regression analysis (F-enter ) 2.89, F-remove ) 2.88) was used at the confidence level of 95%.
Results and Discussion Quantitative Structure-Activity Relationship Model. The toxicity mechanism to organisms remains unclear. Target theory has been accepted extensively, considering that toxicity occurs as a result of the toxicants binding to the specific receptor sites-target molecules in a target cell (6). Two basic assumptions are included in this theory: (i) most toxicants react reversibly with target molecules; and (ii) the biological effect is directly proportional to the number of target molecules binding by organic chemicals. Based on this theory, we have developed a theoretical equation for small molecules in recent work (9):
log (1/[A]w) ) log (BCF) + log K + d
(1)
where [A]w is the lethal concentration in water, generally expressed by EC50 or LC50. BCF is the bioconcentration factor on organisms; K is equilibrium constant of the receptor site-organic chemical reaction in the reactive medium (here is the hydrophobic region of proteins in nerve membranes of organisms). It was suggested from © 1996 American Chemical Society
A QSAR Model and Its Application
Chem. Res. Toxicol., Vol. 9, No. 3, 1996 611
Table 1. Tested Chemicals and Their Physicochemical Parameters log(1/LC50) (mol/L) chemicals
log Kow
R
πH
RH
βH
ref 12
1,2-dichloroethane 1,1,2-trichloroethane 1,1,2,2-tetrachloroethane pentachloroethane hexachloroethane trichloroethene diisopropyl ether di-n-butyl ether 5-methyl-2-hexanone 2-octanone 5-nonanone 2-decanone 4-methyl-2-pentanone cyclohexanone 3-pentanone 3-methyl-2-butanone tetrahydrofuron 2-methyl-1-propanol cyclohexanol benzene toluene 1,2-xylene 1,4-xylene 3-chlorotoluene 4-chlorotoluene 1,4-dimethoxybenzene 2-nitrotoluene 3-nitrotoluene 4-nitrotoluene benzophenone chlorobenzene bromobenzene 1,3-dichlorobenzene tetrachloroethene 1,2-dichlorobenzene 1,4-dichlorobenzene 1,2,4-trichlorobenzene 1,2,3-trichlorobenzene 1,3,5-trichlorobenzene 1,2,4,5-tetrachlorobenzene 1,2,3,4-tetrachlorobenzene phenol 2-cresol 3-cresol 4-cresol 2,4-dimethylphenol 2,6-dimethylphenol 3,4-dimethylphenol 2-chlorophenol 3-methoxyphenol 4-nitrophenol 4-chloro-3-methylphenol aniline 2-chloroaniline
1.48 1.89 2.39 3.22 4.14 2.42 1.56 3.21 1.88 2.37 2.88 3.73 1.31 0.81 0.82 0.84 0.46 0.76 1.23 2.13 2.73 3.12 3.15 3.28 3.33 2.03 2.30 2.42 2.53 3.18 2.89 2.99 3.38 3.40 3.55 3.59 4.02 4.05 4.19 4.60 4.64 1.46 1.98 1.98 1.97 2.30 2.36 2.23 2.20 1.58 1.91 2.78 0.98 1.81
0.416 0.499 0.595 0.648 0.680 0.524 0 0 0.114 0.108 0.103 0.108 0.111 0.403 0.154 0.134 0.289 0.217 0.460 0.610 0.601 0.663 0.613 0.736 0.705 0.806 0.866 0.874 0.870 1.447 0.718 0.882 0.847 0.639 0.872 0.825 0.980 1.030 0.980 1.160 1.180 0.805 0.840 0.822 0.820 0.843 0.860 0.830 0.853 0.879 1.070 0.920 0.955 1.033
0.64 0.68 0.76 0.66 0.22 0.37 0.19 0.25 0.65 0.68 0.66 0.68 0.65 0.86 0.66 0.65 0.52 0.39 0.54 0.52 0.52 0.56 0.52 0.67 0.67 1.00 1.11 1.10 1.11 1.50 0.65 0.73 0.73 0.44 0.78 0.75 0.81 0.86 0.73 0.86 0.92 0.89 0.86 0.88 0.87 0.80 0.79 0.86 0.88 1.17 1.72 1.02 0.96 0.92
0.10 0.13 0.16 0.17 0 0.08 0 0 0 0 0 0 0 0 0 0 0 0.37 0.32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.60 0.52 0.57 0.57 0.53 0.39 0.56 0.32 0.59 0.82 0.65 0.26 0.25
0.11 0.13 0.12 0.06 0.06 0.03 0.41 0.45 0.51 0.51 0.51 0.51 0.51 0.56 0.51 0.51 0.48 0.48 0.57 0.14 0.14 0.16 0.16 0.07 0.07 0.50 0.27 0.25 0.28 0.50 0.07 0.09 0.02 0 0.04 0.02 0 0 0 0 0 0.30 0.30 0.34 0.31 0.39 0.39 0.39 0.31 0.39 0.26 0.22 0.41 0.31
2.92 3.21 3.92 4.44 5.20 3.47 3.05 3.60 2.84 3.66 3.66 4.44 2.30 2.27 1.75 2.00 1.52 1.72 2.15
this equation that the toxicity of organic chemicals to aquatic organisms depended on two success processes: (1) organic chemicals transported from the water phase to the organism and achieved the target regions by partitioning, characterized by bioconcentration factors, which determined the local concentration of organic chemicals on the receptor sites; that is, the external factor of the acute toxicity to the organism; (2) organic chemicals interacted with the receptor sites, characterized by the equilibrium constant of the receptor site-organic chemical reaction; that is, the internal factor of the acute toxicity to the organism. Here, the receptor site-organic chemical reaction should be regarded as the interaction between organic chemicals and the receptors over various degrees in a broad sense, including weak molecular forces (dispersion, dipole-dipole, and dipole-induced dipole interactions), hydrogen-bond complexation, and others, except for the
ref 13
3.40 3.32 3.48 4.21 3.84 4.33 3.07 3.57 3.63 3.76 4.08 4.72 4.09 4.44 4.20
3.71
3.77 3.89 4.30 4.40 4.62 5.00 4.89 4.74 5.85 5.43 3.51 3.77 3.29 3.58 3.86 3.75 3.90 4.02 3.21 3.36 4.27 2.84 3.34
calc eq 7
dif
2.70 3.08 3.55 4.26 4.91 3.49 2.55 3.90 2.86 3.25 3.67 4.37 2.38 2.07 1.99 2.00 1.74 2.23 2.66 3.23 3.72 4.06 4.07 4.22 4.25 3.22 3.46 3.56 3.65 4.39 3.89 4.03 4.34 4.28 4.49 4.51 4.91 4.96 5.05 5.45 5.49 3.17 3.55 3.58 3.57 3.82 3.78 3.78 3.60 3.29 3.79 4.33 2.59 3.30
0.22 0.13 0.37 0.18 0.29 -0.02 0.50 -0.30 -0.02 0.41 -0.01 0.07 -0.08 0.20 -0.24 0.00 -0.22 -0.51 -0.51 0.17 0.40 -0.58 0.14 -0.38 0.08 -0.15 0.11 0.07 0.11 -0.31 -0.12 -0.14 -0.04 -0.19 -0.09 0.02 0.09 -0.07 -0.31 0.40 -0.06 0.34 0.22 -0.29 0.01 0.04 -0.03 0.12 0.42 -0.08 -0.43 -0.06 0.25 0.04
specific and irreversible reactions like Schiff-base formation. The equilibrium constant of the receptor siteorganic chemical reaction would be intended as a measure of the relative interaction strength. It was well recognized that the protein and lipid components of the biosystems are stronger hydrogen-bond donors or/and acceptors. For this reason, we suggested that the reaction might be taken mainly as hydrogen-bond complexation reaction, in the following form:
A-H(M) + B(M) H A-H‚‚‚B(M)
(2)
where A-H stands for the receptor sites, B stands for the toxicant, and M is the medium. Hydrogen-bond acidity and hydrogen-bond basicity, as two important solvatochromic parameters, have been used successfully for the equilibrium constant of a series of reactions in form 2 in tetrachloromethane at 298 K
612 Chem. Res. Toxicol., Vol. 9, No. 3, 1996
Feng et al.
(14). Here, based on the work by Kamlet, Taft, Abraham, et al. (10, 14-17), when the weak molecular forces were considered too, the equilibrium constant of the receptor site-organic chemical reaction, being a series of organic chemicals reacting with the same indicator (receptor site) in the same medium, might be expressed by the solvatochromic parameters of organic chemicals. It was given as
log K ) log K0 + rR + sπH + aRH + bβH
(3)
where R is the organic chemical excess molar refraction, πH is the organic chemical dipolarity/polarizability, RH and βH are the effective or summation organic chemical hydrogen-bond acidity and basicity, respectively, a detailed discussion of which has been done by Abraham (10). log K0 is the intercept. The terms rR, sπH, aRH, and bβH reflect the relative contribution of each interaction to the equilibrium constants, representing the difference of each interaction between the organic chemicalreceptor site and organic chemical-medium: respectively dispersion, dipole-dipole, or dipole-induced dipole plus some polarizability interactions, hydrogen-bonding interactions involving the receptor site or the medium as HBA and the organic chemical as HBD and the receptor site or the medium as HBD and the organic chemical as HBA (HBD ) hydrogen bond donor, HBA ) hydrogen bond acceptor). The constants in eq 3 are found by the method of multiple linear regression analysis and serve to characterize the differences between the phases, here are the receptor site and the reactive medium: r is the tendency of the phases to interact through π- and n-electron pairs, s is the phase dipolarity/polarizability, a is the phase hydrogen-bond basicity (because a basic phase will interact with an acidic phase), and b is the phase hydrogen-bond acidity. Bioconcentration factors were correlated directly to octanol-water partition coefficients (Kow) (18):
log (BCF) ) a1 log Kow + b1
(4)
From the above eqs 1, 3, and 4, we obtain a general equation as follows:
log (1/[A]w) ) k log Kow + rR + sπH + aRH + bβH + c (5) As pointed out by Abraham (10), the variables used are independent. For the particular data set, there might be collinearity among these variables that could be identified by using the correlation analysis. Comparison with Other Methodology. The linear solvation energy relationship (LSER) method and Hansch method have been used successfully in the studies of toxicity in environmental toxicology. It should be noted that our QSAR equation is similar to the LSER equation in form, especially when the octanol-water partition coefficients are expressed as toxicant solvatochromic parameters. They are different in studying toxicity. First, they are based on different toxicity mechanisms: as described in the previous section, the LSER method suggested that toxicity results from changes in the structure of lipid bilayers in nerve cell membranes due to an increase in volume caused by dissolved toxicant; the transport of organic chemicals from water phase to biophase is a rate control process and the unique crucial factor that determines the toxicity (4, 5). However, our QSAR model suggested that toxicity
occurs as a result of toxicant binding to specific receptor sites of the organism, and the transport of organic chemicals from water phase to biophase is a process that provides an effective local concentration of organic chemicals on the receptor sites; it is the premise of toxicity. Second, interactions between organic chemicals and the organism were involved in both two methods. In the LSER method, the organism was considered to be a total phase, and the interactions between the organic chemicals and different sections of the organism, especially between the receptor site and the local medium, are mixed. However, we suggested that there is some difference between them, which is able to be distinguished successfully in our method. According to the toxicity mechanism, our model is more similar to the Hansch model, shown by the well-known Hansch equation (6, 11, 19):
log(1/C) ) a(log Kow)2 + b log Kow + cσ + d(Es) + e (6) where C is the molar concentration that elicits a constant biological response, and Kow, σ, and Es are the octanolwater partition coefficient, the Hammett constant, and the Taft constant, respectively, measuring the hydrophobic, electronic, and steric effects of organic chemicals. a, b, c, d, and e are the regression constants. It has been used successfully in studies of environmental toxicology; its application might be limited for both classes of compounds, because it developed for the specific classes of compounds (6, 11, 19). Therefore, our QSAR equation may be more general due to its application without limitation of chemical group; furthermore, some handy estimation methods (10, 20) for these parameters used here may extend its application to a vast variety of possible organic chemicals. Model Application. Here, we analyze the acute toxicity of organic chemicals to fathead minnow (P. promelas) in the form of eq 6. Values of LC50 for four compounds are given by both Veith et al. and Hall et al., and the differences between the two sets of results ranged from 0.18 to 1.72 log units, except for 1,2,3,4-tetrachlorobenzene; the average values for these compounds were used in statics analysis. The average difference of 0.47 log unit for the other three common solutes gives an indication of the usual reproducibility of the measurements, and the conflicting result for 1,2,3,4-tetrachlorobenzene shows how vulnerable the calculational method is to the occasional very much out-of-line result. The result is given by eq 7. A plot of eq 7 is shown in Figure 1.
log(1/LC50) ) 1.263 + 0.823 log Kow + 0.705RH + 0.350R (7) (n ) 54, r ) 0.958, SD ) 0.259) Though the lower correlation coefficient of 0.958 for eq 7 represents unsatisfactory goodness of fit, the quality of the correlation is about as good as could be expected according to the standards usually applied to correlations of biological properties. The reason for lower coefficient is mainly due to the fact that the biological experiment itself has large error, and the fact that the data sets are collected from different sources. The predicted values are also listed in Table 1, which fit well in with the observed values respectively. The residuals range within the experiment error.
A QSAR Model and Its Application
Chem. Res. Toxicol., Vol. 9, No. 3, 1996 613
Acknowledgment. This project was funded by the National Natural Science Foundation of P. R. China.
References
Figure 1. Observed versus predicted toxicity of 54 organic chemicals to fathead minnow. Solid line corresponds to eq 7. Table 2. Matrix of Correlations among Physicochemical Properties (n ) 54) log Kow log Kow π* RH βH R
1.000
π*
RH
βH
R
-0.039 1.000
-0.348 0.424 1.000
-0.490 0.092 0.211 1.000
0.420 0.658 0.276 -0.488 1.000
Though the terms sπ* and bβ are stated to be important in eq 5, we find that they are not statistically significant and absent from eq 7. According to the correlation analysis among these variables (Table 2), it would not be due to the linear dependence of the various variables. As discussed above, the constants were used to characterize the difference of physical-chemical properties between the receptor and the medium, and we could conclude that the receptor site of fathead minnow is similar to its medium in HBD acidity and dipolarity/ polarizability. Furthermore, the receptor site is a rather stronger base and is rich in n- and/or π-electrons relative to its medium. The work by Kamlet et al. (4) and Franks (21, 22) supported our conclusion. It is clearly seen that increasing the toxicant octanolwater partition coefficient, which leads to an increased tendency of the toxicant to be concentrated by the organism, thus to a higher local concentration of the toxicant on the target regions, would exert a higher toxic effect to the organism for the toxicant with the similar reactivity. As we have observed, the toxicity of pchlorotoluene is a little stronger than that of chlorobenzene to fathead minnows due to its slightly larger octanol-water partition coefficient relative to the later. It is also seen that increasing the toxicant R, and RH, which leads to higher reactivity of the toxicant, and thus to stronger interactions between the organic chemical and the receptor site, would lead to a stronger toxic effect to fathead minnows. For example, the toxicity of 2-cresol is 5.0 times greater than that of 1,4-dimethoxybenzene, although they have similar octanol-water partition coefficients. This method is useful for us to understand the detailed toxicity mechanism for one organism and to find the relationship and differences in toxicity mechanisms for different organisms.
(1) Reid, W. D. (1972) Mechanism of alkyl alcohol-induced hepatic necrosis. Experientia 28, 1058-1061. (2) Lipnick, R. L., Johnson, D. E., Gilford, J. H., Bickings, C. K., and Newsome, L. D. (1985) Comparison of fish toxicity screening data for 55 alcohols with the quantitative structure-activity relationship predictions of minimum toxicity for nonreactive nonelectrolyte organic compounds. Environ. Toxicol. Chem. 4, 281-296. (3) Hansch, C., and Dunn, W. M. (1972) Linear relationship between lipophilic character and biological activity of drugs. J. Pharm. Sci. 61, 1-19. (4) Kamlet, M. J., Doherty, R. M., Velth, G. D., Taft, R. W., and Abraham, M. H. (1986) Solubility properties in polymers and biological media. 7. An analysis of toxicant properties that influence inhibition of bioluminescence in Photobacterium phosphoreum (The Microtox test). Environ. Sci. Technol. 20, 690695. (5) Kamlet, M. J., Doherty, R. M., Taft, R. W., Abraham, M. H., Veith, G. D., and Abraham, D. J. (1987) Solubility properties in polymers and biological media. 8. An analysis of the factors that influence toxicities of organic nonelectrolytes to the golden orfe fish (Leuciscus idus melanotus). Environ. Sci. Technol. 21, 149-155. (6) Hansch, C., and Fujita, T. (1964) F-σ-π Analysis. A method for the correlation of biological activity and chemical structure. J. Am. Chem. Soc. 86, 1616-1626. (7) Franks, N. P., and Lieb, W. R. (1984) Do general anesthetics act by competitive binding to specific receptors? Nature (London) 310, 599-601. (8) Van Hoogen, G., and Opperhuizen, A. (1988) Toxicokinetics of chlorobenzenes in fish. Environ. Toxicol. Chem. 7, 213-219. (9) Zhao, Y. H., Wang, L. S., Gao, H., and Zhang, Z. (1993) Quantitative structure-activity relationships: Relationship between toxicity of organic chemicals to fish and to Photobacterium phosphoreum. Chemosphere 26, 1971-1979. (10) Abraham, M. H. (1993) Scales of solute hydrogen-bonding: Their contribution and application to physicochemical and biochemical processes. Chem. Soc. Rev. 22, 73-83. (11) Hansch, C., and Leo, A. (1979) Substituent Constants for Correlation Analysis in Chemistry and Biology, Wiley-Interscience, New York. (12) Veith, R. C., Call, D. J., and Brook, L. T. (1983) Structure-toxicity relationships for the fathead minnow, pimephales premalas: narcotic industrial chemicals. Can. J. Fish Aquat. Sci. 40, 743748. (13) Hall, L. H., Maynard, E. L., and Kier, L. B. (1989) Structureactivity relationship studies on the toxicity of benzene derivatives: III. Prediction and extension to new substituents. Environ. Toxicol. Chem. 8, 431-436. (14) Abraham, M. H., Grellier, P. L., Prior, D. V., Taft, R. W., Morris, J. J., Tayor, P. J., Laurence, C., Berthelet, M., and Doherty, R. M. (1988) A general treatment of hydrogen bond complexation constants in tetrachloromethane. J. Am. Chem. Soc. 110, 85348536. (15) Kamlet, M. J., Abboud, J.-L. M., Abraham, M. H., and Taft, R. W. (1983) Linear solvation energy relationships. 23. A comprehensive collection of the solvatochromic parameters, π*, R, and β, and some methods for simplifying the generalized solvatochromic equation. J. Org. Chem. 48, 2877-2887. (16) Taft, R. W., Abboud, J.-L. M., Kamlet, M. J., and Abraham, M. H. (1985) Linear solvation energy relationships. J. Solution Chem. 14, 153-186. (17) Abraham, M. H., Grellier, P. L., Abboud, J.-L. M., Doherty, R. M., and Taft, R. W. (1988) Solvent effects in organic chemistrys Recent developments. Can. J. Chem. 66, 2673-2686. (18) Isnard, P., and Lambert, S. (1988) Estimating bioconcentration factors from octanol-water partition coefficient and aqueous solubility. Chemosphere 17, 21-34. (19) Hansch, C., and Clayton, J. M. (1973) Lipophilic character and biological activity of drugs. J. Pharm. Sci. 62, 1-21. (20) Hickey, J. P., and Passino-Reader, D. R. (1991) Linear solvation energy relationships: “Rules of thumb” for estimation of variable values. Environ. Sci. Technol. 25, 1753-1760. (21) Franks, N. P., and Lieb, W. R. (1978) Where do general anesthetics act? Nature 274, 339-342. (22) Franks, N. P., and Lieb, W. R. (1985) Mapping of general anaesthetic target sites provides a molecular basis for cuttoff effects. Nature 316, 349-352.
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