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Keywords:

  • Atomic charge;
  • Intracellular chemical reaction;
  • Joint effect;
  • Quantitative structure–activity relationship;
  • Mixture

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Environmental contaminants are usually encountered as mixtures, and many of these mixtures yield synergistic or antagonistic effects attributable to an intracellular chemical reaction that pose a potential threat on ecological systems. However, how atomic charges of individual chemicals determine their intracellular chemical reactions, and then determine the joint effects for mixtures containing reactive toxicants, is not well understood. To address this issue, the joint effects between cyanogenic toxicants and aldehydes on Photobacterium phosphoreum were observed in the present study. Their toxicological joint effects differed from one another. This difference is inherently related to the two atomic charges of the individual chemicals: the oxygen charge of -CHO (Oaldehyde toxicant) in aldehyde toxicants and the carbon-atom charge of a carbon chain in the cyanogenic toxicant (Ccyanogenic toxicant). Based on these two atomic charges, the following QSAR (quantitative structure–activity relationship) model was proposed: When (Oaldehyde toxicant − Ccyanogenic toxicant) > −0.125, the joint effect of equitoxic binary mixtures at median inhibition (TU, the sum of toxic units) can be calculated as TU = 1.00 ± 0.20; when (Oaldehyde toxicant − Ccyanogenic toxicant) ≤ −0.125, the joint effect can be calculated using equation image (n = 40, r = 0.887, SE = 0.195, F = 140, p < 0.001, q2Loo = 0.748; SE is the standard error of the regression, F is the F test statistic). The result provides insight into the relationship between the atomic charges and the joint effects for mixtures containing cyanogenic toxicants and aldehydes. This demonstrates that the essence of the joint effects resulting from intracellular chemical reactions depends on the atomic charges of individual chemicals. The present study provides a possible approach for the development of a QSAR model for mixtures containing reactive toxicants based on the atomic charges. Environ. Toxicol. Chem. 2012;31:270–278. © 2011 SETAC


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Because environmental contaminants are frequently encountered as mixtures rather than single chemicals, research on assessing the joint effects of mixtures has increased substantially 1. Based on the mode of actions of single chemicals, the joint toxic action can be classified as concentration addition (similar mode of action), independent action (dissimilar action), and interaction (synergistic and antagonistic effects) 2. Most current studies focus on mixtures with additive effects, and few works attempt to predict the toxicity of mixtures with synergistic or antagonistic effect 3. That synergistic or antagonistic effects readily occur among reactive toxicants is well known, and the occurrence of the synergistic and antagonistic effects might exert a negative influence on environmental risk assessment 4. Therefore, one must study the mechanism of the joint effects of mixtures, especially those mixtures with synergistic or antagonistic effects 5.

Intracellular chemical reaction, also known as chemical interaction 6, is one of the main causes of synergistic or antagonistic effects. For example, chemical interaction between chlorpyrifos and methyl mercury results in the formation of a chlorpyrifos-methyl mercury complex and thus yields a joint effect 7; atrazine and nitrite can react in vivo and result in the formation of N-nitrosoatrazine, leading to increased carcinogenicity 6. Although the processes of the reactions were known, developing quantitative structure–activity relationship (QSAR) models to assess their mixture toxicity was not enough, because the essence of the reaction remained unclear. It is also still uncertain what determines the reaction or which descriptor can be used to describe the reactivity of individual chemicals. Fortunately, employing atomic charge as chemical reactivity indices or as measures of weak intermolecular interactions is widely accepted 8. Atomic charge has been a widely used quantum-chemical parameter to describe the charge distribution around a molecule 9. Consequently, if the contribution of the atomic charge of individual chemicals to the toxicologically relevant interactions can be obtained, it will allow us to reveal the essence of the joint effect and propose a possible approach to predicting the joint effects for these toxic mixtures with synergistic or antagonistic effects.

Both cyanogenic toxicants and aldehydes are common pollutants in the environment. They are widely used as intermediates in the manufacture of dye, paint, acrylic fibers, and medicaments. Most possess excess toxicity and readily cause serious environmental hazards 10–13. For example, acrylonitrile is classified as the group B1 chemical for probable human carcinogen by the U.S. Environmental Protection Agency 14, 15; formaldehyde and acetaldehyde possess carcinogenic potential in experimental animals 16. In particular, their simultaneous applications are common, and these toxicants are often simultaneously detected in wastewater 17–19. For example, Li et al. 20 reported that the concentrations of cyanogenic toxicants and aldehydes in dying effluent were 0.026 and 0.016 mmol/L 20.

Consequently, Chen et al. 21–23 first assessed the joint effects (TU, the sum of toxic units) of binary equitoxic mixtures at median inhibition containing cyanogenic toxicants and aldehydes and found that these mixture can result in various joint effects (synergistic, additive, and antagonistic effects). Our previous study 24 further revealed that their joint effects result from their intracellular chemical interactions (Fig. 1).

thumbnail image

Figure 1. The intracellular chemical reaction between cyanogenic toxicants and aldehydes in Photobacterium phosphoreum24.

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Based on the intracellular chemical reaction, we proposed some QSAR models using the Hammett constant (σp) to describe the toxicity contribution of aldehydes and the charge of the carbon atom in the carbon chain of cyanogenic toxicants (C*) to describe the toxicity contribution of cyanogenic toxicants 25. One QSAR model is shown as follows

  • equation image(1)

However, this model is invalid for mixtures containing aliphatic aldehydes because it was derived from mixtures containing aromatic aldehydes. A difference in σp exists between aliphatic aldehydes and aromatic aldehydes: the σp of aliphatic aldehydes was obtained from the pKa of acetic acid, whereas the σp of aromatic aldehydes was derived from that of benzoic acid. Several similar models have been proposed, but they are still imperfect for application to any given mixture containing cyanogenic toxicants and aldehydes 24–27 because of a lack of understanding of the essence of intracellular chemical reactions.

The purpose of the present study is to further reveal the essence of intracellular chemical reaction between cyanogenic toxicants and aldehydes in Photobacterium phosphoreum and find out the essential atomic charges that can be used to describe the joint effects, to reveal the relationship between these atomic charges and the joint effects and propose a QSAR model using atomic charges, and to interpret the toxicological mechanism for mixtures containing cyanogenic toxicants and aldehydes based on the QSAR model.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Materials

Malononitrile and acetonitrile were purchased from Sinopharm Chemical Reagent. Other chemicals were purchased from Sigma-Aldrich. All chemicals were of analytical reagent grade or better (purity ≧95%). The chemicals were prepared in a 3% NaCl solution. Mixtures were tested in equitoxic doses (identical fractions of median effective concentration [EC50]) based on observed single EC50 values.

Instrumentation

The toxicity test instrument (chemiluminescent immunoassay analyzer BH9507) was made by Beijing Hamamatsu. The freeze-dried marine bacterium Photobacterium phosphoreum (T3 mutation) was supplied by the Institute of Soil Science, Chinese Academy of Sciences (Nanjing, China). It was reconstituted and maintained on agar slants at 4°C. The bioluminescence assays were performed using diluted bacteria that had been cultured at 20°C in yeast-tryptone-salt-glycerol broth for 12 to 14 h 28.

Toxicity experiment

Toxicity was measured by quantifying the decrease in light emission from the bacteria as a result of exposure to a 3% NaCl solution of the test chemical for 15 min. The decrease in light emission was measured at least six different concentrations, and each concentration was tested in triplicate. Based on the decrease in light emission, EC50 was calculated using the Probit analysis and reported as -log EC50 with units of mol/L 29, 30. Binary equitoxic mixtures were prepared based on the obtained EC50 of single toxicants. The joint effect (TU) at the median inhibition of equitoxic binary mixture was calculated as follows

  • equation image(2)

where CA and CB are the concentrations of individual components in the mixtures at median inhibition and can be calculated according to the EC50 of the mixture. The EC50A and EC50B are the median effective inhibition concentrations of individual chemicals. The following criterion was applied to assess the joint effect 31: concentration additions are characterized by TU = 1.00 ± 0.20, where TU < 0.80 indicates synergetic effects and TU > 1.20 indicates antagonistic effects.

Statistical analysis

The atomic charges were calculated using Gaussian 03 software (Gaussian Company). Initial geometries were optimized by semi empirical method AM1, then optimized at the hybrid density functional theory using a B3LYP/6-311G** basis set. To ensure that the systems had no imaginary vibration frequencies, the frequency analysis was performed on the optimized geometries 32. Data analysis and linear regression were performed using IBM SPSS 18.0. Parameters, including r (the correlation coefficient), SE (the standard error), F (the F test statistic), and p (the significance level) were calculated to evaluate the correlation of the model 9, 33, 34. The test for self-correlation of variables is performed using the variance inflation factor 35. The application of the parameter q2Loo, derived from leave-one-out cross-validation method, was used to validate the robustness of the prediction model 36.

RESULTS AND DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Joint effects between cyanogenic toxicants, aldehydes

Before determining the joint effects between cyanogenic toxicants and aldehydes, the toxicity (EC50) of individual chemicals to Photobacterium phosphoreum was evaluated as -log EC50, as shown in Table 1. Based on these data, the joint effects (TU) between cyanogenic toxicants and aldehydes were determined, and the results are listed in Table 2. TU in the present study denotes the joint effects of equitoxic binary mixtures at median inhibition.

Table 1. Experimental results of the toxicity tests for single chemicals.
ClassificationNo.Single chemical-log (EC50)a
(mol/L)
  • a

    EC50 denotes the median effective concentration.

  • b

    Data from Lin et al. 2003 26.

  • c

    Data from Lin et al. 2004 27.

  • d

    Data from Lin et al. 2005 25.

  • *

    Denotes the chemical is a cyanogenic toxicant.

  • **

    Denotes the chemical is an aldehyde toxicant.

Cyanogenic toxicants1*Malononitrile2.55
Cyanogenic toxicants2*Glycolonitrile2.98b
Cyanogenic toxicants3*α-hydroxyisobutyronitrile3.61c
Cyanogenic toxicants4*Allyl cyanide2.06
Cyanogenic toxicants5*3-hydroxypropionitrile0.68
Cyanogenic toxicants6*Acetonitrile0.75
Aldehyde toxicants1**Formaldehyde3.17
Aldehyde toxicants2**Acetaldehyde2.36
Aldehyde toxicants3**Propanal2.72d
Aldehyde toxicants4**Butyraldehyde3.25
Aldehyde toxicants5**Valeraldehyde3.27
Aldehyde toxicants6**Heptanal3.98
Aldehyde toxicants7**Decanal4.47
Aldehyde toxicants8**Acrolein5.54
Aldehyde toxicants9**Benzaldehyde3.43
Aldehyde toxicants10**Nitrobenzaldehyde4.28
Aldehyde toxicants11**Terephthaldehyde4.07
Aldehyde toxicants12**p-chlorobenzaldehyde3.97
Aldehyde toxicants13**p-bromobenzaldehyde4.30
Aldehyde toxicants14**p-hydroxybenzaldehyde4.54
Aldehyde toxicants15**p-methyl benzaldehyde3.82
Aldehyde toxicants16**p-methoxybenzaldehyde4.03
Aldehyde toxicants17**p-dimethylaminobenzaldehyde5.40
Table 2. Results of joint effects between cyanogenic toxicants and aldehydes
No.Cyanogenic toxicantsAldehyde toxicantsTUaCcyanogenic toxicantOaldehyde toxicantOaldehyde toxicant —Ccyanogenic toxicant
  • a

    TU, the sum of toxic units, denotes the joint effects at median inhibition in equitoxic binary mixtures.

  • b

    Data from Lin et al. 2005 25.

  • c

    Data from Lin et al. 2003 26.

  • d

    Data from Lin et al. 2004 27.

  • *

    Denotes the chemical is a cyanogenic toxicant.

  • **

    Denotes the chemical is an aldehyde toxicant.

11*1**0.04−0.1261−0.2511−0.1250
21*2**0.12−0.1261−0.2732−0.1471
31*3**0.12b−0.1261−0.2757−0.1496
41*4**0.16−0.1261−0.2743−0.1482
51*5**0.40−0.1261−0.2706−0.1445
61*6**0.47−0.1261−0.2778−0.1517
71*7**0.88−0.1261−0.2856−0.1595
81*8**0.34−0.1261−0.2784−0.1523
91*9**0.63−0.1261−0.2866−0.1605
101*10**0.15−0.1261−0.2703−0.1442
111*11**0.26−0.1261−0.2766−0.1505
121*12**0.50−0.1261−0.2833−0.1572
131*13**0.46−0.1261−0.2844−0.1583
141*14**0.92−0.1261−0.2959−0.1698
151*15**1.11−0.1261−0.2904−0.1643
161*16**1.15−0.1261−0.2973−0.1712
171*17**1.17−0.1261−0.3090−0.1829
182*10**0.48c0.0580−0.2703−0.3283
192*11**0.30c0.0580−0.2766−0.3346
202*12**0.55c0.0580−0.2833−0.3413
212*13**0.69c0.0580−0.2844−0.3424
222*9**0.83c0.0580−0.2866−0.3446
232*14**1.02c0.0580−0.2959−0.3539
242*15**0.87c0.0580−0.2904−0.3484
252*17**1.85c0.0580−0.3090−0.3670
263*2**0.42d−0.0089−0.2732−0.2643
273*3**0.42d−0.0089−0.2757−0.2668
283*4**0.47d−0.0089−0.2743−0.2654
293*6**0.98d−0.0089−0.2778−0.2689
303*7**1.03d−0.0089−0.2856−0.2767
313*8**0.62d−0.0089−0.2784−0.2695
323*10**0.59d−0.0089−0.2703−0.2614
333*11**0.48d−0.0089−0.2766−0.2677
343*9**0.93d−0.0089−0.2866−0.2777
353*12**0.89d−0.0089−0.2833−0.2744
363*13**0.88d−0.0089−0.2844−0.2755
373*14**1.08d−0.0089−0.2959−0.2870
383*15**0.99d−0.0089−0.2904−0.2815
393*16**1.15d−0.0089−0.2973−0.2884
403*17**1.78d−0.0089−0.3090−0.3001
414*1**1.01−0.1780−0.2511−0.0731
424*2**1.08−0.1780−0.2732−0.0952
434*6**1.19−0.1780−0.2743−0.0963
444*7**0.93−0.1780−0.2706−0.0926
454*8**0.81−0.1780−0.2778−0.0998
464*9**1.12−0.1780−0.2866−0.1086
474*10**0.94−0.1780−0.2703−0.0923
484*11**1.04−0.1780−0.2766−0.0986
494*12**1.07−0.1780−0.2833−0.1053
504*14**1.17−0.1780−0.2959−0.1179
514*15**0.85−0.1780−0.2904−0.1124
524*16**1.19−0.1780−0.2973−0.1193
534*17**1.07−0.1780−0.3090−0.1310
545*1**1.04−0.1993−0.2511−0.0518
555*2**1.05−0.1993−0.2732−0.0739
565*4**0.80−0.1993−0.2743−0.0750
575*5**0.91−0.1993−0.2706−0.0713
585*6**0.89−0.1993−0.2778−0.0785
595*9**1.06−0.1993−0.2866−0.0873
605*10**0.95−0.1993−0.2703−0.0710
615*11**1.20−0.1993−0.2766−0.0773
625*12**0.94−0.1993−0.2833−0.0840
635*14**1.05−0.1993−0.2959−0.0966
645*15**0.95−0.1993−0.2904−0.0911
655*16**0.91−0.1993−0.2973−0.0980
665*17**0.89−0.1993−0.3090−0.1097
676*1**1.19−0.2475−0.2511−0.0036
686*4**1.18−0.2475−0.2743−0.0268
696*6**1.02−0.2475−0.2778−0.0303
706*7**0.83−0.2475−0.2856−0.0381
716*10**0.89−0.2475−0.2703−0.0228
726*11**1.09−0.2475−0.2766−0.0291
736*14**1.00−0.2475−0.2959−0.0484
746*15**1.03−0.2475−0.3090−0.0615
756*16**1.11−0.2475−0.2904−0.0429
766*17**0.93−0.2475−0.3090−0.0615

Table 2 shows that different joint effects (additive, synergistic, or antagonistic) occur for different mixtures, which indicates that joint effects may result from the intracellular chemical reactions between cyanogenic toxicants and aldehydes.

Intracellular chemical reactions

Processes of intracellular chemical reactions

As reported in our previous study 26, the intracellular chemical reactions between cyanogenic toxicants and aldehydes consist of two steps. In the first step, cyanogenic toxicants enter a cell and hydrolyze under the action of enzymes, which results in the formation of CN (cyanide ions) and other hydrolyzates, including organic acids, acetones, or aldehydes 13. The detailed description of the hydrolysis of various cyanogenic toxicants is shown in the Supplemental Data, Figure S1.

  • equation image(3)

Meanwhile, aldehydes toxicants also enter the cell. Some aldehydes reach the target sites, and the others are free within the cell. In the second step, cyanide ions around the enzymes collide with the free aldehydes within the cell. Then the intracellular chemical reactions between CN and the free aldehydes occur and result in the formation of a carbanion intermediate. This carbanion intermediate can be easily oxidized by O2 to the corresponding acid, which is the main reason that these mixtures yield various joint effects.

  • equation image(4)
Classifying mixtures based on cyanogenic hydrolyzates

The release of CN is important in the intracellular chemical reaction. If there is no CN separate from the cyanogenic toxicants in the first step, the intracellular chemical reaction cannot occur. Comparing Equation 3 with Equation 4 illustrates that the release of CN is related to the reactivity of aldehyde toxicants. When the reactivity of an aldehyde toxicant is higher than the hydrolyzate (aldehydes, acetones, or acids) of a cyanogenic toxicant, CN can separate from the hydrolyzate and react with the aldehyde toxicants, allowing both chemical reactions and joint effects to occur.

For example, the hydrolyzate of glycolonitrile is formic acid, and the reactivity of some aldehyde toxicants (terephthaldehyde, nitrobenzaldehyde, p-chlorobenzaldehyde, and p-bromobenzaldehyde) is stronger than formic acid. Therefore, these mixtures yield synergistic effects (nos. 18–21 in Table 2). We defined these mixtures containing glycolonitrile as group I.

The hydrolyzate of α-hydroxyisobutyronitrile is acetone, and the reactivity of some aldehyde toxicants (acetaldehyde, propanol, and butyraldehyde) is stronger than acetone. Thus, cyanogenic toxicants release CN, the intracellular chemical reaction proceeds readily, and synergistic effects occur (nos. 26–28 in Table 2). We defined these mixtures containing α-hydroxyisobutyronitrile as group II.

For allyl cyanide, 3-hydroxypropionitrile, and acetonitrile, the respective hydrolyzates are acrolein, acetaldehyde, and formaldehyde, and the reactivity of these hydrolyzates is the same as that of aldehyde toxicants (such as formaldehyde and acetaldehyde). No difference can be seen between the reactivity of cyanogenic hydrolyzates and aldehyde toxicants. Therefore, no CN can be released from cyanogenic toxicants, and the chemical reaction is impossible, leading to additive effects (nos. 41–76 in Table 2). We defined these mixtures containing allyl cyanide, 3-hydroxypropionitrile, and acetonitrile as group III.

For mixtures containing malononitrile, the hydrolysis of malononitrile contains two steps and yields two hydrolyzates besides CN: the intermediates cyanoaldehyde and the final formic acid. We defined these mixtures as group IV.

Role of atomic charges

Regardless of the group to which a mixture belongs, both cyanogenic hydrolyzates (aldehyde, acetone or acid) and aldehyde toxicants have a carbonyl group ([BOND]C[DOUBLE BOND]O), so their reactivity can be described using the oxygen-atom charge in [BOND]CHO or the carbonyl group. This indicates that the joint effects might be correlated with the data of Ohydrolyzate-Oaldehyde toxicant: the gap between Ohydrolyzate and Oaldehyde toxicant, Ohydrolyzate and Oaldehyde toxicant are the oxygen-atom charges in carbonyl group of cyanogenic toxicants and aldehydes.

  • equation image(5)

According to the relationship between cyanogenic toxicants and their hydrolyzates, the carbon atom closest to the −CN (cyano group) in the carbon chain of the cyanogenic toxicants is the origin of the oxygen atom in the carbonyl group of the cyanogenic hydrolyzates. Therefore, Ohydrolyzate might be correlated with Ccyanogenic toxicant (Ccyanogenic toxicant is the charge of the carbon atom closest to the −CN in the carbon chain of cyanogenic toxicants). The correlation can be described as follows

  • equation image(6)

The relationship between Ohydrolyzate and Ccyanogenic toxicant can be obtained according to the revealed process of cyanogenic hydrolysis. Detailed data are listed in Supplemental Data, Table S1.

  • equation image(7)

where r = 0.804, n = 14, SE = 0.0175, F = 21.9, p < 0.001

The significant correlation coefficient in Equation 7 (r = 0.804, p < 0.001) also demonstrates that either Ccyanogenic toxicant or Ohydrolyzate is a good descriptor to describe the reactivity of cyanogenic toxicants. Because Ohydrolyzate is derived from the intermediate products of cyanogenic toxicants and the structure of the intermediate hydrolyzate cannot be easily obtained, Ccyanogenic toxicant is therefore employed to substitute for Ohydrolyzate.

QSAR model for joint effects

Initial QSAR model. Combining Equations 5 and 6, we obtain Equation 8. Then the relationships between TU and the gap (Oaldehyde toxicantCcyanogenic toxicant) (the gap between Oaldehyde toxicant and Ccyanogenic toxicant) can be shown in Figure 2.

  • equation image(8)
thumbnail image

Figure 2. The relationship between TU (the sum of toxic units) and the gap between Oaldehyde toxicant and Ccyanogenic toxicant. (equation image) denotes mixtures containing glycolonitrile and various aldehydes, (▴) α-hydroxy-isobutyronitrile and aldehydes, (▪) malononitrile and aldehydes, (★) allyl cyanide and aldehydes, (▾) 3-hydroxypropionitrile and aldehydes, (♦) acetonitrile and aldehydes. [Color figure can be seen in the online version of this article, available at wileyonlinelibrary.com]

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Figure 2 shows, for each cyanogenic toxicant, a good relationship between TU and the gap (Oaldehyde toxicantCcyanogenic toxicant). The mixtures can be divided into four different sets according to the relationship. Group I and Group II are mixtures containing glycolonitrile and α-hydroxyisobutyronitrile, whose corresponding hydrolyzates are formic acid and acetone. The reactivity of some aldehyde toxicants (such as formaldehyde and acetaldehyde) is higher than that for these hydrolyzates (formic acid and acetone). Therefore, in the corresponding mixtures (an aldehyde toxicant of formaldehyde or acetaldehyde and a cyanogenic toxicant of glycolonitrile or α-hydroxy-isobutyronitril), the cyanogenic toxicants easily hydrolyze and release CN, allowing chemical reactions to proceed and synergetic effects to occur (nos. 18–21, 26–28 in Table 2). For other aldehyde toxicants (such as p-methylbenzaldehyde, p-hydroxy-benzaldehyde, and p-dimethylaminobenzaldehyde), only additive or antagonistic effects occur because their reactivity with CN is less than that of cyanogenic hydrolyzates (nos. 23–25, 37–40 in Table 2).

Group III are mixtures containing allyl cyanide, 3-hydroxypropionitrile, and acetonitrile, and only additive effects occur for these mixtures because the reactivity of aldehyde toxicants is less than their hydrolyzates, leading to a hindrance of the intracellular chemical reactions (nos. 41–76 in Table 2).

Group IV are mixtures containing malononitrile. The group is located at a special position because its two-step hydrolysis yields intermediates cyanoaldehyde and formic acid.

To further reveal the relationship between the joint effects and the gaps of reactivity between cyanogenic hydrolyzates and aldehyde toxicants, these toxicants are listed in Figure 3 based on their reactivity.

thumbnail image

Figure 3. The relationship between the joint effects and the gaps of reactivity between cyanogenic hydrolyzates and aldehyde toxicants. [Color figure can be seen in the online version of this article, available at wileyonlinelibrary.com]

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Figure 3 shows that malononitrile is located at a special position. This is because malononitrile has two hydrolyzates besides CN: the intermediate cyanoacetaldehyde and the final formic acid. Considering the initial hydrolyzate (cyanoacetaldehyde), malononitrile should be classified into group III. Considering the other hydrolyzate (formic acid), malononitrile should be classified into group I. However, because of both hydrolyzates, malononitrile can be listed in neither group (group III or group I). We listed it as group IV. Therefore, the gap between malononitrile and formaldehyde (formaldehyde is the most active aldehyde in these aldehyde toxicants) is defined as a criterion to classify these mixtures, that is, OformaldehydeCmalononitrile = −0.125. Then an initial QSAR model can be proposed as follows

  • equation image(9)

The joint effects for group III can be described using the first formula in Equation 9 (n = 36). For groups I, II, and IV, the second formula is available (n = 40). To further reveal the relationship between TU and the atomic charges in groups I, II, and IV, Equation 10 is obtained by combining Equations 5, 6, and 7.

  • equation image(10)

The relationship between TU and (Oaldehyde toxicant + 0.189 × Ccyanogenic toxicant + 0.300) can be developed using regression analysis of data from groups I, II, and IV, and the results are shown in both Figure 4 and Equation 11.

  • equation image(11)
thumbnail image

Figure 4. The correlation between TU (the sum of toxic units) and (Oaldehyde toxicant + 0.189 × Ccyanogenic toxicant + 0.300).

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The value of r (0.332) shows a poor correlation. Figure 4 indicates that the outlier of mixtures containing malononitrile causes this poor correlation. The outlier is attributable to the difference of hydrolysis between malononitrile and other cyanogenic toxicants. Malononitrile hydrolysis is divided into two steps and yields two CN and two hydrolyzates, whereas other cyanogenic toxicants only yield one CN and one hydrolyzate. The deletion of the mixtures containing malononitrile from Equation 11 yields Equation 12.

  • equation image(12)

where n = 23, r = 0.857, SE = 0.209, F = 57.9, p < 0.001, q2Loo = 0.660

The significant correlation (r = 0.857) indicates the developed model is successful in describing the relationship between the joint effects and the atomic charges of mixtures containing cyanogenic toxicants and aldehydes. Therefore, a QSAR model for the joint effects according to Oaldehyde toxicant and Ccyanogenic toxicant can be proposed as follows:

  • equation image(13)

where n = 23, r = 0.857, SE = 0.209, F = 57.9, p < 0.001, q2Loo = 0.660.

Intervention analysis of the outliers

The QSAR model (Eqn. 13) has two outliers. One is the mixture containing allyl cyanide and p-dimethylaminobenzaldehyde (DMAB); the other is mixtures containing malononitrile.

The hydrolyzate of allyl cyanide is acrolein. Acrolein is the smallest unsaturated aldehyde, and its reactivity is stronger than formaldehyde 37. Based on the deduced criterion in the present study, only when the reactivity of the aldehyde toxicant is higher than that of the hydrolyzate of the cyanogenic toxicant, chemical reaction thus proceeds and results in joint effects. Obviously, the occurrence of chemical reaction between allyl cyanide and DMAB is impossible. Consequently, this mixture yields an additive effect. This conclusion is in agreement with our experimental data (no. 53 in Table 2).

However, Figure 3 shows that DMAB is the last in the homologous series of aldehyde toxicants and possesses far less reactivity than any other aldehyde toxicants because the value of Oaldehyde of DMAB is the least of all aldehyde toxicants (−0.309, no. 53 in Table 2). Furthermore, the hydrolyzate of allyl cyanide is acrolein. As the smallest unsaturated aldehyde, the reactivity of acrolein is stronger than that of formaldehyde. The gap of allyl cyanide and DMAB (ODMABCallyl cyanide) is so large that the mixture containing the two special chemicals does not obey this criterion, and the mixture is listed as an outlier.

Mixtures containing malononitrile are outliers of the prediction model (Eqn. 13) because malononitrile has two −CN, whereas other cyanogenic toxicants have only one. Malononitrile has two hydrolyzates as well as two Ohydrolyzate. The average Ohydrolyzate (the oxygen charge of the intermediate cyanoacetaldehyde in the first hydrolysis step and that of formic acid in the second hydrolysis step) was used to obtain Equation 13; thus, the unknown validity of Ohydrolyzate leads to the malononitrile outlier. If the Ohydrolyzate-validity (Ohydrolyzate-validity represents the validated value of Ohydrolyzate) can be found, mixtures containing malononitrile will cease to be outliers. Therefore, the relationships between Ohydrolyzate-validity and r were studied, and the results are shown in Figure 5.

thumbnail image

Figure 5. The relationship between the correlation coefficient and the validity of Ohydrolyzate of malononitrile. [Color figure can be seen in the online version of this article, available at wileyonlinelibrary.com]

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Figure 5 shows that the relationship between Ohydrolyzate-validity and r presents a single-peaked curve. The best fit is obtained for equation image = −0.310 and r = 0.887 (the correlation between TU and (Oaldehyde toxicant + 0.189 × Ccyanogenic toxicant + 0.300) after adjustment at the best fitted point can be found in the Supplemental Data, Fig. S2). This phenomenon can be used to explain the malononitrile outlier and its hydrolysis mechanism. When the malononitrile hydrolysis is dominated by the first step, the value of equation image (the oxygen charge of intermediate cyanoacetaldehyde in the first step) is −0.218 and the corresponding r of the QSAR model is only 0.139, which is not statistically significant according to the principle of QSAR validation 9. When the malononitrile hydrolysis is dominated by the second step, the value of equation image (the oxygen charge of final formic acid in the second step) is −0.286, and the corresponding r is only 0.553. The best fit is obtained for equation image = −0.310 and r = 0.887. The value of equation image is less than equation image and equation image. Consequently, the hydrolysis is not dominated by either the first or the second step but by both steps.

In conclusion, a QSAR model can be successfully proposed using the adjusted Ccyanogenic toxicant (0.0529) of malononitrile derived from equation image based on the formula (equation image)

  • equation image(14)

where n = 40, r = 0.887, variance inflation factor = 1.001, SE = 0.195, F = 140, p < 0.001, q2Loo = 0.748.

The r value of the QSAR model is 0.887, indicating a good goodness-of-fit. The variance inflation factor is 1.001, indicating no self-correlation between variables. The q2Loo of the QSAR is as high as 0.748, implying a good robustness of the model. The difference between r2 and q2Loo (r2 − q2Loo = 0.038) does not exceed 0.3, indicating no overfitting in the model. F = 140 and p < 0.001 indicate that the results are statistically significant at the significance level. Furthermore, the result of external validation demonstrates that the QSAR model has good predictive capability (see the result in the Supplemental Data, Table S2 and Fig. S3).

Discussion of the QSAR model

The QSAR model (Eqn. 14) provides a mechanism interpretation for the mixture toxicity between cyanogenic toxicants and aldehydes. It can be shown from the model that the charge of the carbon atom closest to −CN (Ccyanogenic toxicant) can be employed to describe the reactivity of cyanogenic toxicant in mixtures. This indicates that the charge of the carbon atom determines the capability of the cyanogenic hydrolysis and then the hydrolysis determines the contribution of the cyanogenic toxicants in mixture toxicity. For aldehyde toxicants, the charge of oxygen atom in −CHO (Oaldehyde toxicant) can be employed to describe the contribution of aldehydes in mixtures toxicity. That is, the charge determines the reactivity of aldehydes with cyanogenic toxicants. The Ccyanogenic toxicant and Oaldehyde toxicant determine the reaction between cyanogenic toxicants and aldehydes and then can be used to determine their joint effects.

Because the two atomic charges (Ccyanogenic toxicant and Oaldehyde toxicant) determine the reaction and joint effects between individual toxicants (cyanogenic toxicants and aldehydes), the atomic charge–based QSAR model should be a general model. In our previous studies, several QSAR models were developed using the Hammett constant (σp) to describe the contribution of aldehydes and the charge of the carbon atom in the carbon chain of cyanogenic toxicants (C*) to describe the contribution of cyanogenic toxicants (Table 3).

Table 3. The comparison of this model with our previous modelsa
No.ModelnApplicability domainOutlier
  • a

    TU = toxic units.

  • b

    Data from Lin et al. 2003 26.

  • c

    Data from Lin et al. 2004 27.

  • d

    Data from Lin et al. 2005 25.

  • e

    The adjusted Ccyanogenic toxicant of malononitrile (0.0529) is employed to develop the QSAR (Quantitative structure activity relationship) model. Aliphatic and aromatic aldehydes are involved.

1bTU = 0.788–0.882σp8Malononitrile and aromatic aldehydesAliphatic aldehydes
2bTU = 0.0015–4.876σp6Malononitrile and aliphatic aldehydesAromatic aldehydes
3cTU = 0.978–0.720σp9α-Hydroxyisobutyronitrile and aromatic aldehydesAliphatic aldehydes
4cTU = 0.316–4.386σp6α-Hydroxyisobutyronitrile and aliphatic aldehydesAromatic aldehydes
5bTU = 0.0824–0.237C6Cyanogenic toxicants and acetaldehydeMalononitrile
6cTU = -0.161–7.721C7Cyanogenic toxicants and p-nitrobenzaldehyde 
7dTU = 0.367–0.811σp-6.704C40Cyanogenic toxicants and aromatic aldehydesAliphatic aldehydes
8The model in the present study75Cyanogenic toxicants and aldehydese 

These previous models can only be applied to mixtures containing individual cyanogenic toxicant and various aldehydes (nos. 1–4 in Table 3), or mixtures containing various cyanogenic toxicants and individual aldehyde (nos. 5–6 in Table 3). Another model, no. 7 in Table 3 (or Eqn. 1), can be applied to various cyanogenic toxicants and various aromatic aldehydes, but the model cannot be applied to aliphatic aldehydes because the employed descriptor (σp) of aromatic aldehydes is inherently different from that of aliphatic aldehydes.

CONCLUSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

In the present study, the joint effects between cyanogenic toxicants and aldehydes on Photobacterium phosphoreum were observed. Atomic charges can be employed as descriptors to describe joint effects in binary mixtures containing cyanogenic toxicants and aldehydes. A mechanism-based QSAR model can thus be obtained to predict the joint effects for these binary mixtures. Because the two atomic charges (Ccyanogenic toxicant and Oaldehyde toxicant) determine the reaction and joint effects between individual toxicants (cyanogenic toxicants and aldehydes), the developed QSAR model is more general than previous models. The result provides an insight into the relationship between the atomic charges and the joint effects for mixtures containing cyanogenic toxicants and aldehydes. This demonstrates that the essence of the joint effects resulting from intracellular chemical reactions depends on the atomic charges of individual chemicals. The present study provides a possible approach for the development of a QSAR model for mixtures containing reactive toxicants based on the atomic charges.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

This work was funded by the Foundation of the State Key Laboratory of Pollution Control and Resource Reuse, China (PCRRK09003, PCRRY11003), the National Natural Science Foundation of China (20977067, 201177092), New Century Excellent Talents in University (20100472), Specialized Research Fund for the Doctoral Program of Higher Education (20100072110034985), the Fundamental Research Funds for the Central Universities (0400219181), the R&D Special Fund for Public Welfare Industry (201109048) and the General Administration of Quality Supervision, Inspection and Quarantine (AQSIQ) of P R C (201110250). We are grateful for their financial support.

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  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS AND DISCUSSION
  6. CONCLUSION
  7. SUPPLEMENTAL DATA
  8. Acknowledgements
  9. REFERENCES
  10. Supporting Information

Additional supporting information may be found in the online version of this article.

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etc_1701_sm_SupplDataTabS1.doc463KSupplemental Data Table S1

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