Environ. Sci. Techno/. 1995,29, 3044-3048
Prediction of Partition Coefficient and Toxicity for Phenylthio, Phenylsulfinyl, and Phenylsulfonyl H U I HONG, SHUOKUI HAN, XIAORONG WANG, AND LIANSHENG WANG* Department of Environmental Science and Engineering, Nanjing University, Yanjing, People's Republic of China 210093 ZHENG ZHANG AND GONGWEI ZOU Department of Chemisty, Nanjing University, h'nnjing, People's Republic of China 210093
~~~~~~
~
The log KO, values of 27 phenylthio, phenylsulfinyl, and phenylsulfonyl acetates were determined by the shake-flask method. Their capacity factors were determined by RP-HPLC with C18 column and methanolwater eluent. Partial molecular connectivity indices were calculated for these compounds and used to describe their log KO, values and toxicities to Photobacterium phosphoreum. Res uIts demonstrated that while both the HPLC results and the molecular connectivity indices (MCls) could be used to predict the KO, for all of the compounds, the MCI method was more accurate. The correlation between toxicity and molecular connectivity index was also significant, and the correlation was better than a previous o and E, analysis.
Introduction With the development of industry, the use of sulfurcontaining compounds, especiallythe aromatic substances, is more extensive. However there has been only limited investigation of their environmental behavior and physicochemical properties. Twenty-eight phenylthio, phenylsulfinyl, and phenylsulfonyl acetates have been newly synthesized in our laboratory. Han et al. ( 1 ) have studied the hydrolysis of these compounds, and Wang et al. (2) have investigated their toxicity to Photobacterium phosphoreum. Partitioning is a fundamental process of chemicals in the environment; many properties, such as water solubility (S,) (31,the adsorption coefficient for soils and sediments (KJ ( 4 ) ,and the bioconcentration factor (BCF) (3,are correlated with the octanol/water partition coefficient (KO\,) of a chemical. KO,, also serves as basic information that can be correlated with biological activity ( 6 ) . In this paper, the octanol/water partition coefficient (K,,,,) determined by the shake-flask method and the RPHPLC capacity factors (K)of 27 aromatic sulfur-containing compounds are reported.
3044 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 29, NO 12, 1995
These compounds are relatively new, and selecting appropriate descriptors to describe their physicochemical and biological properties tends to be difficult. The molecular connectivity indices (MCIs),originally proposed as a branching index by Randic (7) and extensively developed and formalized by Kier and Hall (81, are important molecular descriptors. MCIs are basedon bond counting, from which topological indexes can be derived from chemical structures. For a given molecular structure, several types and orders of molecular connectivity indices can be calculated. The order refers to the number of bonds in the skeletal substructure or fragment used in computing the index: zero order defines individual atoms, first order uses individual bond lengths, second order uses two adjacent bond combinations, and so on. The type refers to the structural fragment (path, cluster, path/cluster, or chain) used in computing the index. Information on molecular size, branching, cyclization, unsaturation, and heteroatom content of a molecule is encoded in these various indices (8). A large number of studies have demonstrated that many physicochemical and biological properties, such as water solubility (9),KO, (IO),BCF ( I ] ) , KO,(12), solute retention in HPLC (13, 14), and biological activity (15, 16), depend on the topology of a molecule. This may be related to the connectivity index. In this study, the log KO,vand the log l/ECso, which is the concentration of a chemical to give 50% inhibition of Photobacterium phosphoreum, were estimated by MCIs. The factors determining these properties are discussed and compared.
Materials and Methods Instruments. The HPLC system (Shimadzu, Japan) consisted of a SCL-8A system monitor, a LC-8Apump, a C-R4A integrator, and a SPD-6AV ultraviolet spectrophotometer as the detector. Reagents. Methanol (analyticalreagent and redistilled); doubly distilled water; sodium nitrate (analytical reagent): octanol (analytical reagent). Samples. Twenty-eight phenylthio, phenylsulfinyl,and phenylsulfonyl acetates were synthesized in our laboratory (17, 18). Their purities were monitored by HPLC to assure purity. The structures of the chemicals are listed in Table 1. Calculation of MCIs. The MCIs were calculated according to the method outlined by Kier and Hall (8). The calculation was performed on an AST 386 computer. The calculated values of MCIs are shown in Table 2. Determinationof Capacity Factors. A Nucleusil7 C- 18 column, 15 cm x 4.6 mm i.d. (made by Dalian Institute of Chemicalphysics, Academic Sinica) was used. Mobile phases were made by mixing methanol with water in the proportions 100:0,90:10, 85:15,80:20, 75:25, and 70:30 (vi v). The flow rate was 0.8 mL/min. Aqueous solution of sodium nitrate was used for the measurement of dead time. All measurements were at least duplicated. The average reproducibility of each determination was better than 1.0% relative. The capacity factors at the eluent composition of methanol 60% are shown in Table 2. Determinationof Partition Coefficients. The octanol/ water partition coefficients were determined by the shakeflask method as described by the OECD Guideline for
0013-936X/95/0929-3044$09.00/0
d 1995 American Chemical Society
Testing of Chemicals (19)at 25 “C, followed by centrifuging and analysis of chemical in the aqueous phase with a W spectrophotometer against water blank. The regression analysis was performed using the “Statgraphics” program (STSC,Inc.; 1987). The toxicitydata of these aromaticsulfurcontaining compounds to P. phosphoreum were taken from Wang et al. (2).
TABLE 1
Chemical Structures
Results and Discussion
no.
Prediction of Log &, from HPLC Capacity Factor (Log IC). The relationship between log K and methanol concentration in mobile phase given by Snyder et al. (20) is
la lb
(1)
log IC = log IC, - SPCH,OH
where K , represents the K value for a compound if pure water is used as eluent, sis the slope of the regression curve, and C ~ C H ~ OisH the volume percentage of methanol in the eluent. The regression coefficients for the studied compounds are all above 0.99. Alot of studies have shown that capacityfactors obtained by RP-HPLC correlate well with KO, (21-24), and using HPLC for determining KO, has become a formal method (2.9,
The determined KO,values of the 27 compounds by the shake-flaskmethod were correlatedwith the experimentally determined HPLC capacity factors. As can be seen in eq 2, a good linear relationship between log KO, and log K was obtained at the methanol-water eluent of composition 60: 40 (v/v) (extrapolated): log KO, = 1.654 (0.087) log IC,,
r = 0.967
s = 0.192
+ 1.190 (0.050)
F = 362.78
(2)
S S S S S S S S S S
IC
Id le If lg lh li li 2a 2b 2c 2d 2e
so so so so so so so so so so so2
2f 2g 2h 2i 2i 3a 3b 3c 3d 3e 3f 39 3h
so2 so2 so2 so2 so2 so2 so2
n = 27
where r is the correlation coefficient, s is the standard error, F is the F statistic, and n is the number of observations. The statistical significance of the equation is indicated by the fact that the calculated Fvalue exceeds the tabulated value at the 99% confidence level: F = 362.78 > F (1,25, 0.01) = 7.77. From eq 2, it appears that Kowcanbe predicted by the HPLC capacity factor. The determined, calculated, and residual log KO, values are shown in Table 3. Prediction of Log &, from Molecular Connectivity Indices (MCIs). The molecular connectivity index is a powerful tool in predicting both physicochemical properties and biological activities. In the calculation of molecular connectivity indices, if the studied compounds have a common parent structure, molecular fragment connectivity indices can be calculated instead. Kier and Hall (26) and Kaliszan (27) have used this sort of partial molecular connectivity indices in their work and have successfully obtained the correlation between activity and MCIs and between chromatography retention and MCIs, respectively. The structures of the compounds investigated in this study are shown in Table 1. An examination of the general structure suggests two areas of interest. The ester alkyl of CH3or CH(CH3)2is certainly an area of interest because of its great influence on the hydrophobicity. The other area is the substitution pattern of R1, Rz, and R3 on the benzene ring. Since the two areas occupy sites at opposite ends of the molecule, it would not be surprising if these two parts exert independent influences on the physicochemical properties and biological activities. For this reason, molecular connectivity indices were calculated for truncated
portions of the molecule. For the ester alkyl group R4, the was calculated. It was simple zero-order index Ox(&) enough by using Ox(&) to discriminate CH3and CH(CH3)2. Forthe substitutedphenylpartPh, OX(Ph),lX(Ph),andsimple path indexes 2 ~ ( P h ) - 7 ~ p ( Psimple h), third-order cluster index 3 ~ c ( P hsimple ), forth and fifth-order path/cluster indexes *xpc(Ph)and 5 ~ p c ( Pas h )well as the corresponding valence indexes were calculated. All the 23 calculated connectivity indexes were stored as variables in the data file. By stepwise linear regression, the statistically significant variables were chosen for log KO,, The first variable that entered the equation was Ox(R4), the second variable was 3~vC(Ph). The Ox(&) index reflects the volume of the ester alkyl, and the 3~vc(Ph) index encodes information about the count and type of branches on the benzene ring. The following high-quality regression equation was obtained:
+
log KO, = 0.568 (0.O36)Ox(R4) 22.953
+
(1.275)3~vc(Ph) - 6.878 (0.479)*xV(Ph)
+
1.549 (0.325)5~p,(Ph) 8.698(0.639) (3)
r = 0.980
s = 0.146
F = 162.90
n = 27
Equation 3 is highly significant at the level better than 0.01: F = 162.90 > F (4, 22, 0.01) = 4.31. The student t values for each coefficient also are very large compared to the significant level of 0.05: 15.897, 18.009, -14.356, and 4.761. The calculated and residual values of log KO, as determined by eq 3 are listed in Table 3. VOL. 29, NO. 12.1995 / ENVIRONMENTAL SCIENCE & T E C H N O L O G Y
3045
TABLE 2
HPLC Capacity Factors and Selected Molecular Connectivity Indices for Studied Compounds no. log
la lb IC Id le If lg lh li lj 2a 2b 2c 2d 2e 2f 29 2h 2i 2j 3a 3b 3c 3d 3e 3f 39 3h
K60a
0.8897 0.8867 1.2654 0.3310 0.7232 0.7886 1.1757 0.5370 0.9251 -0.3134 0.1198 0.0817 0.5114 -0.2731 0.2214 0.1337 0.5580 --0.2462 0.1912 -0.0354 0.3731 0.1952 0.5720 -0.2329 0.2591 0.2556 0.6407
odR4)b3;C'c(Ph)bZ;C'(Ph)b7 ~ p ( P h )4~pc(Ph)b b S~pc(Ph)b 2.5774 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774 1.0000 2.5774
0.2787 0.2787 0.4185 0.4185 0.2459 0.2459 0.4347 0.4347 0.3480 0.3480 0.2466 0.2466 0.3906 0.3906 0.2181 0.2181 0.4068 0.4068 0.3202 0.3202 0.2551 0.2551 0.4048 0.4048 0.2323 0.2323 0.4210 0.4210
2.0824 2.0824 2.5843 2.5843 2.0325 2.0325 2.6123 2.6123 2.4290 2.4290 2.1480 2.1480 2.6574 2.6574 2.1056 2.1056 2.6854 2.6854 2.5021 2.5021 2.1756 2.1756 2.6949 2.6949 2.1430 2.1430 2.7229 2.7229
0.0351 0.0351 0.0738 0.0738 0.0439 0.0439 0.0644 0.0644 0.0920 0.0920 0.0920 0.0920 0.1206 0.1206 0.0610 0.0610 0.0792 0.0792 0.1416 0.1416 0.1281 0.1281 0.1512 0.1512 0.0723 0.0723 0.0890 0.0890
0.4567 0.4567 0.7923 0.7923 0.4954 0.4954 0.6700 0.6700 0.8052 0.8052 0.4757 0.4757 0.7490 0.7490 0.4852 0.4852 0.6598 0.6598 0.7950 0.7950 0.6132 0.6132 0.8495 0.8495 0.6003 0.6003 0.7749 0.7749
Obtained at the methanoliwater composition of 60:40 trapolated). See text for definition.
0.3715 0.3715 0.6487 0.6487 0.5629 0.5629 0.7399 0.7399 0.8083 0.8083 0.4081 0.4081 0.7502 0.7502 0.5727 0.5727 0.7534 0.7534 0.8219 0.8219 0.5052 0.5052 0.9403 0.9403 0.6833 0.6833 0.8656 0.8656 (VIV)
(ex-
To test the robustness of eq 3, we performed a jacknife test; about 10% (three) of the observations were randomly deleted, and the regression was rerun for the remaining 24 observations. The procedure was repeated 30 times, and all of the regression statistics were averaged. The overall results of the deletion study are summarized in Table 4. It is seen that the equation is quite 'robust'. None of the regression parameters for the diminished data sets is significantly different from those for the full data set. In this study, each observation was deleted at least once, no observation was deleted more than 4 times, and most observations were deleted 3 or 4 times. Furthermore, when an observation was deleted, the predicted value of the deleted observation was computed. Thus, the residuals for the deleted observations could be calculated. The average absolute value of the residuals for the deleted observations is 0.118, about the same (0.097) as for the residuals for all 27 observations based on eq 3. This aspect of the study tests the predictive quality of the model, and the results demonstrate that the eq 3 has high predictive abiliq.
As is seen from eq 2, eq 3, and Table 3, the logK,,values of the phenylthio, phenylsulfinyl, and phenylsulfonyl compounds can be predicted simultaneously by one single equation, either eq 2 or eq 3. A comparison between the regression coefficients and the standard errors of eqs 2 and 3 shows that the MCI method is more accurate than the HPLC method for K,,, prediction of these studied compounds. In addition, the MCIs can be calculated quickly and accurately from chemical structures. Using molecular connectivity indices to predict log K,, is remarkably promising. 3046
E N V I R O N M E N T A L SCIENCE & T E C H N O L O G Y
VOL 29. NO 12, 1995
Prediction of Log 1/EC50 by Molecular Connectivity Indices (MCIs). The toxicities of the compounds to p . phosphoreum were investigated by Wang et al. (2). The results demonstrated that the toxicities of these compounds to p . phosphoreum were not related to K&, with a correlation between log 1/EC50and log KO,of -0.322. The hydrophobic properties of the compounds relate little to their toxicities, whie their electronic properties contribute a great deal. For these reactive toxic chemicals, it is hard to select proper physicochemical parameters to describe their activities. Here, the molecular connectivity index method shows its advantages. MCIs can be easily calculated for any compound with a definite structure, yielding unequivocal values. The selected MCIs can then give suggestive information of a structure-activity relationship. The log 1/EC5" values of the studied compounds to P. phosphoreum were taken to the stepwise regression with the 23 MCIs as variables, and eq 4 was obtained:
+
log l/EC,, = -0.178 (0.O53)Ox(R4) 4.694
+
(1.853)'xP(Ph) - 2.012 (0.927)3~"c(Ph) 2.433 (0.696)'xPc(Ph)
r = 0.872
s = 0.219
+ 0.525 (0.225)
F = 22.39
(4)
n = 28
Equation 4 is also statistically significant at the level better than 0.01: F = 22.39 > F (4, 23, 0.01) = 4.26. The student tvalues for each variable are large compared to the significant level of 0.05: -3.398, 2.532, -2.170, and 3.497. The calculated and residual values of log 1/EC5" are shown in Table 3. To test the robustness of eq 4, we also performed a jacknife test similar to the one performed for log K,, and found that the equation is quite 'robust'. The overall results of the deletion study are summarized in Table 5. We also calculated the residuals for the deleted observations. The average absolute value of the residuals for the deleted observations of 0.205. This value also compares favorably to the value (0.172) of the residuals for all 28 observations based on eq 4. These resutls seem to demonstrate the applicability of eq 4 in predicting the toxicities of the structure similar compounds. Wang et al. (2) had used 0 and Es to analyze the log l / E G o data and obtained the following equation: log l/EC,, = 1.10
r = 0.837
+ 0.617Es + 1 . 3 7 0 , ~ ~
s = 0.248
F = 33.68
(5)
n = 29
where Es is the Taft's steric parameter for R4, and 0102stands for the electronic distribution of R1, R2, and R:, in the benzene ring. A comparison between eqs 4 and 5 shows that eq 4, developed by using MCIs, has a significantly higher predictive ability than eq 5. This is shown by the larger r value and the smaller s value. The fitted and residual values of log l/ECso as calculated by eq 5 are listed in Table 3. From eq 5, it can be seen that the more average the electronic distribution is, the more toxic the compound is. This can be seen in Table 3 by the 'a' and 'c' compounds showing a more toxic effect than the corresponding 'e' and 'g' compounds, respectively. In the stepwise linear regression for log l/ECSo, the first and the second variable that entered the equation was
TABLE 3
Experimental and Calculated log KO, and Log log L
w
log 1iE& (mmoiA)
by eq 2
compd la lb IC
Id le If lg Ih li
li
2a 2b 2c 2d 2e 2f 29 2h 2i
2i 3a 3b 3c 3d 3e 3f 39 3h
for Studied Compounds
l/EC50
by eq 4
by eq 3
by eq 5
exptl'
calcd
diff
calcd
diff
exptlb
calcd
diff
calcd
diff
2.79 2.26 3.20 1.88 2.76 2.24 3.00 2.05 2.81 0.80 1.64 1.35 2.01 0.74 1.59 1.29 2.22 0.63 1.61 0.78 1.80 1.45 2.40 0.78 1.72 1.30 2.45
2.66 2.66 3.28 1.74 2.39 2.49 3.13 2.08 2.72 0.67 1.39 1.33 2.04 0.74 1.56 1.41 2.1 1 0.78 1.51 1.13 1.81 1.51 2.14 0.80 1.62 1.61 2.25
0.13 -0.40 -0.08 0.14 0.37 -0.25 -0.13 -0.03 0.09 0.13 0.25 0.03 -0.03 0.00 0.03 -0.12 0.11 -0.15 0.10 -0.35 -0.01 -0.06 0.26 -0.02 0.10 -0.31 0.20
2.81 2.10 3.00 1.80 2.70 2.42 3.32 1.80 2.69 0.78 1.68 1.12 2.01 0.68 1.57 1.30 2.19 0.68 1.57 0.94 1.83 1.48 2.37 0.92 1.81 1.54 2.44
-0.02 0.16 0.20 0.08 0.06 -0.18 -0.32 0.25 0.12 0.02 -0.04 0.23 0.00 0.06 0.02 -0.01 0.03 -0.05 0.04 -0.16 -0.03 -0.03 0.03 -0.14 -0.09 -0.24 0.01
1.45 1.02 1.76 1.13 1.33 1.03 1.51 1.41 2.21 1.72 1.37 0.93 2.20 1.93 1.18 1.32 1.43 1.12 2.65 2.19 1.71 1.72 2.56 1.87 1.51 1.66 1.67 1.55
1.11 0.83 1.83 1.55 1.31 1.03 1.45 1.17 2.09 1.81 1.49 1.21 2.00 1.72 1.43 1.14 1.56 1.27 2.35 2.07 1.98 1.70 2.36 2.08 1.73 1.45 1.85 1.57
0.34 0.19 -0.07 -0.42 0.02 0.00 0.06 0.24 0.12 -0.09 -0.12 -0.28 0.20 0.21 -0.25 0.18 -0.13 -0.15 0.30 0.12 -0.27 0.02 0.20 -0.21 -0.22 0.21 -0.18 -0.02
1.39 1.10 1.59 1.30 1.37 1.08 1.58 1.29 2.06 1.77 1.80 1.51 1.99 1.70 1.37 1.08 1.69 1.40 2.47 2.18 1.97 1.68 2.17 1.88 1.37 1.08 1.74 1.45
0.06 -0.08 0.17 -0.17 -0.04 -0.05 -0.07 0.12 0.15 -0.05 -0.43 -0.58 0.21 0.23 -0.19 0.24 -0.26 -0.28 0.18 0.01 -0.26 0.04 0.39 -0.01 0.14 0.58 -0.07 0.10
Determined by shake-flask method. *Taken from ref 2.
TABLE 4
Comparison of Regression Parameters for Diminished and Full KO, Data Sets coefficients data set
constant
OXcRd
3fc(Ph)
diminisheda fullb
8.690 (0.687) 8.698 (0.639)
0.567 (0.038) 0.568 (0.036)
22.904 (1.334) 22.953 (1.275)
regression parameters *f(W -6.875 (0.543) -6.878 (0.479)
'xpc(ph)
r
S
1.550 (0.352) 1.549 (0.325)
0.980 0.980
0.146 0.146
a See text for definition. Values are averages of 30 separate runs, and the standard error in the coefficient estimates are given in parentheses. From eq 3.
TABLE 5
Comparison of Regression Parameters for Diminished and Full log l/ECso Data Sets coefficients
regression parameters
data set
constant
0X(R4)
3fc(Ph)
'Xp(Ph)
'XpcPhl
r
S
diminisheda fullb
0.586 (0.246) 0.525 (0.225)
-0.180 (0.056) -0.178 (0.053)
-1.980 (0.996) -2.012 (0.927)
4.686 (2.002) 4.694 (1.853)
2.409 (0.747) 2.433 (0.696)
0.870 0.872
0.220 0.219
* Seetextfordefinition. Valuesareaveragesof3Oseparateruns,andthestandard error inthecoefficientestimatesaregiven in parenthesesb From eq 4.
7 ~ p ( P and h ) Ox(&), respectively. It shows that 7xp(Ph)plays an important role in toxicity while 3~vc(Ph) is important in the octanol-water partitioning process. This implies that different structure features are important to toxicity and partitioning. Ox(&) describes the size or the volume of the ester alkyl group. It is not unexpected that the hydrophobicity of the compound increases with the change of the ester alkyl from -CH3 to -CH(CH3Ip. This is also suggested by the positive coefficient on Ox(&) in eq 3. But we can see that in eq 4 the coefficient on Ox(&) is negative, which suggests that
the toxicity of the compound decreases with the change of the ester alkyl from -CH3 to -CH(CH3)2. Since the ester alkyl groups of these studied compounds are of only two kinds, -CH3 and -CH(CH&, it is difficult to explain the exact effects of the ester alkyl group on the toxicity. 7~p(Ph was ) used to correlate with aluz, yielding an r of 0.898. This shows the 7 ~ p ( P h index ) includes the information on the electronic distribution around the benzene ring. Kier and Hall (26)pointed out that the long path indexes were sensitiveto the substitution pattern around a benzene ring. A n examination of the long path index 'xp(Ph) from VOL. 29, NO. 12, 1995 / ENVIRONMENTAL SCIENCE &TECHNOLOGY
3047
the topological point of view shows that compared with the other indices, only this one wholly includes the information of RI, Rz, and R3 and thus illustrates the interrelation of the three substituents. This reveals that the coaction of the three substituents in the benzene ring has a significant effect on the toxicity.
Summary and Conclusion In this investigation, a range of aromatic sulfur-containing compounds was studied for their octanol/water partition coefficients (Kow)and toxicities to P.phosphoreum. HPLC is a fast and accurate method for determining the Kowvalues, and the HPLC model can be used to predict values of KO,.+ Statistically significant models, based on the molecular connectivity indices (MCIs), have been developed. The MCI models are such accurate, simple, and fast nonempirical models that they can be used to predict KO, and toxicity for other structure similar sulfur-containing compounds. They also are predictive tools for ranking potentially hazardous chemicals and for creating priority lists for testingthem. Furthermore, direct correspondence between molecular structure and topologicalindex makes it possible to locate structure features responsible for environmental behavior.
Acknowledgments This project was funded by the National Natural Foundation of the People’s Republic of China.
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(5) Neely, W. B.; Branson, D. R.; Blau, G. E. Environ. Sci. Technol. 1974, 8, 1113. (6) Hansch, C.; Leo, A. Substitutent Constantsfor CorrelationAnalysis in Chemistry a n d Biology; John Wiley & Sons: New York, 1979. (7) Randic, M. 1. Am. Chem. SOC. 1975, 17, 6609. (8) Kier, L. B.; Hall, L. H. Molecular Connectivity in Chemistry and Drug Research; Academic Press: New York, 1976. (9) Nirmalakhandan, N. N.; Speece, R. E. Environ. Sci. Technol. 1989, 23, 708. (10) Murray, W. J.; Hall, L. H. J. Pharm. Sci. 1975, 64, 1978. (11) Connell, D. W.; Schuurmann, G. Ecotoxicol. Environ. Sa$ 1988, 15, 324. (12) Sabljic, A. Environ. Sci. Technol. 1987, 21, 358. (13) Bojarski, J.; Ekiert, L. Chromatographia 1982, 15, 172. (14) Jinno, K.; Kawasaki, K. Chromatographia 1984, 18, 90. (15) Blum, D. J. W.; Speece, R. E. Ecotoxicol. Environ. Saf 1991, 22, 198. (16) Hall, L. H.; Kier, L. B. 1. Pharm. Sci. 1978, 67, 1743. (17) Xu, X.; Zhou, W.; Zhang, Z. Chem. J. Chin. UniiJ. 1992, 13, 490 (in Chinese). (18) Xu, X.; Zhou, W.; Zhang, Z. J. Nanjing Univ. 1991, 27, 483 (in Chinese). (19) OECD Guideline for Testing of Chemicals: OECD: Paris, 1981. (20) Snyder, L. R.; Dolan, J. W.: Gant, J. R. J. Chromatogr. 1979, 165, 3. (21) Tomlinson, E. J. Chromatogr. 1975, 113, 1. (22) Kaliszan, R. Quantitative-Structure Chromatographic Retention Relationships; John Wiley & Sons: New York, 1987. (23) Doucette, W. J.: Andren, A. ‘CV. Chemosphere 1988, 1 7, 345. (24) Valko, K. 1. Liq. Chromatogr. 1984, 7, 1405. (251 Klein, W.: Kordel, LV.; Weib, M.; Poremski, H. J. Chemosphere 1988, 17, 361. (26) Kier, L. B.; Hall, L. H. Molecular Connectivity in Structure-Activity Analysis; Research Studies PressiJohn Wiley & Sons: New York, 1986. (27) Kaliszan, R.; Foks, H. Chromatographia 1977, 10, 346.
Received for review April 7, 1995. Revised manuscript received July 20, 1995. Accepted July 26, 1995.@ ES950246H e- Abstract published inAdvanceACSAbstracts, September 1, 1995.
