This article is an openaccess article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Quantitative structureactivity relationship models were obtained by applying the Molecular Descriptor Family approach to eight ordnance compounds with different toxicity on five marine species (
The effects of marine environment sediment contamination with ordnance compounds received a special attention [
The marine sediment toxicity was previously studied by Carr and Nipper [
The main objective of the present research was to identify and to quantify the relationship between the structure of eight ordnance compounds and their marine toxicity by using the Molecular Descriptors Family on the StructureActivity Relationships approach.
The experimental toxicities of eight ordnance compounds on
Effective Concentration to 50% of the organism (EC_{50}), defined as the effective concentration of toxin in aqueous solution that produces a specific measurable effect in 50% of the test organisms within the stated study time (see
No Observed Effect Concentration (NOEC) defined as the highest concentration of toxicant to which organisms are exposed in a full or partial lifecycle test, that determine no observable adverse effects on the test organisms (the highest concentration of toxicant in which the values for the observed responses are not statistically different from the controls) (see
Lowest Observed Effect Concentration (LOEC) defined as the lowest concentration of toxicant to which organisms are exposed in a full or partial lifecycle test, which causes adverse effects on the test organisms (where the values for the observed responses are statistically significant different from the controls) (see
The experimental data (expressed as mg/L) were transformed in logarithmic scale and are presented in
The toxicities of the ordnance compounds on the investigated marine species were modelled by using the molecular descriptors family on the structureactivity relationships (MDF SARs) [
Step 1: Bi and tridimensional representation of the investigated ordnance compounds. This task was done by using a molecular modelling software, HyperChem;
Step 2: Preparation of the compounds for modelling, optimization of geometry and creation of the file with experimental data;
Step 3: Construction, generation, calculation and filtration of the molecular descriptors family. The information extracted from the compound’s structure was used in order to construct, generate, and calculate the molecular descriptors. The obtained descriptors were stored into a database. A biases algorithm was applied in order to delete identically recordings. Seven characteristics were considered in the construction of descriptors: Compound geometry or topology (the 7^{th} letter in the descriptor name); Atomic property (e.g. atomic relative mass, atomic partial charge, cardinality, atomic electro negativity, group electro negativity, number of directly bonded hydrogen’s – the 6^{th} letter); Interaction descriptor (the 5^{th} letter); Overlapping interaction models (the 4^{th} letter); Molecular fragmentation criterion (the 3^{rd} letter) [
Step 4: Search and identification of the most significant MDF SAR models with one molecular descriptor. The following criteria were used: squared correlation coefficient, standard error of estimated, statistical parameters of the regression model.
Step 5: Validation of the obtained models. A leaveoneout crossvalidation analysis was performed. The crossvalidation leaveoneout score, standard error of predict and Fisher parameter were calculated and interpreted [
Step 6: The analysis of the models. The stability of the model (the lowest the difference between squared correlation coefficient and leaveoneout crossvalidation score is, the stable de model was considered), and the predictive power was assessed. The toxicity of the ordnance compounds for which the experimental determinations were not available as values (see n.a. from
The MDF SAR monovariate models with estimated and predictive abilities on investigated endpoints for studied ordnance compounds were identified and are presented in
The analysis of the
The goodnessoffit of all models were close to the highest value (one): greater than 0.93 for EC_{50} (see
Therefore, more than eightyone percent of the activity of interest on studied ordnance compounds can be explained by the linear relationship with the variation of molecular descriptors generated strictly based on the information extracted from the ordnance compounds structure (see values of coefficient of determination – R^{2} from
The stability of each model was investigated in a crossvalidation leaveoneout analysis. The values of the crossvalidation leaveoneout score sustained the validity of the models. The lowest crossvalidation leaveoneout score was of 0.7263. The values where higher than:
0.7500 in twentythree out of twentyfour cases;
0.8000 in twentytwo out of twentyfour cases;
0.8500 in fifteen out of twentyfour cases;
0.9000 in nine out of twentyfour cases.
The lowest value of the crossvalidation leaveoneout score was obtained by Eq_15 (see
The stability of the obtained models could be expressed by the difference between the determination coefficient and the crossvalidation leaveoneout score. The model from Eq_01 obtained the lowest value of 0.0011 while the model from Eq_11 obtained the highest value of 0.0923. The differences between coefficient of determination and leaveoneout crossvalidation score did not exceed 0.1, sustaining the absence of over fitted model and/or the absence of outliers. Therefore, it can be concluded that the lowest ability in identification and quantification the relationships between structures of the ordnance compounds and toxicity was obtained for juveniles’ survival of mysid when the NOEC was the investigated toxicity.
The obtained MDF SAR models are valid according with the criteria of Erikson
In the regard of the type of relationships between ordnance compounds structures and associated toxicities on investigated species it can say that:
The EC_{50} on the investigated endpoints (different species, see
The NOEC on the investigated endpoints (different species, see
The LOEC on the investigated endpoints (different species, see
The activities of ordnance compounds without reliable experimental data (expressed as values greater than a number, see
The predicted toxicities on different species calculated for studied ordnance compounds need to be validated. This can be done easily once the experimental toxicities are measure. The MDF SAR approach proved to be a useful method in characterization of ordnance compounds toxicities on investigated marine species, offering valid and reliable models. The limited number of the compounds investigated represents the main limitation of the study. The impossibility of validation the predicted toxicities (see
The MDF SAR approach proved its usefulness in characterization of the toxicity of ordnance compounds. The relationship between ordnance compounds structure and their toxicities revealed to be in the majority of the cases of geometrical nature and directly related with the partial charge for all three types of investigated toxicities.
The research was partly supported by UEFISCSU Romania through grants (ID1051/2007).
The authors are grateful for the help of PhD Marion Nipper from Texas A&M UniversityCorpus Christi, which provided experimental data.
Leaveoneout Analysis (2005) Virtual Library of Free Software. Available online:
SARs (2005) Virtual Library of Free Software. Available online;
2D structure of ordnance compounds.
Relationship between experimental and estimated EC_{50}: fertilization (Eq_01, left hand graphic), and embryological development of
Relationship between experimental and estimated EC_{50}: germination of
Relationship between experimental and estimated EC_{50}: larvae survival of
Relationship between experimental and estimated EC_{50}: germling length (Eq_07, left hand graphic), and germling cell number of
Relationship between experimental and estimated EC_{50}: survival of
Relationship between experimental and estimated NOEC: embryological development (Eq_11, left hand graphic), and germination of
Relationship between experimental and estimated NOEC: laid eggs/female of
Relationship between experimental and estimated NOEC: survival of
Relationship between experimental and estimated LOEC: fertilization (Eq_17, left hand graphic), and embryological development of
Relationship between experimental and estimated LOEC: germination of
Relationship between experimental and estimated LOEC: larvae survival of
Relationship between experimental and estimated LOEC: germling length and cell number (Eq_22, left hand graphic), and survival of
Ordnance compounds toxicity: experimental EC_{50}.
Specie  Endpoint  2,4DNT  2,6DNT  1,3DNB  2,4,6TNT  1,3,5TNB  PAc  Tetryl  RDX 

sea urchin  fertilization  1.8325  n.a.  2.4116  n.a.  1.9243  2.5428  0.4771  n.a. 
embryological development  1.7110  0.8261  1.9638  1.0792  0.1139  2.4487  −1.0969  n.a.  
germination  0.3979  0.8261  −0.0706  0.3979  −1.0969  2.6180  −0.1739  1.0792  
 
polychaete  survival and reproductive success  0.7559  0.3222  0.5682  0.2553  −0.2218  2.1903  −1.6990  1.4150 
 
redfish  larvae survival  1.6812  1.5315  1.6628  0.9138  0.1461  2.1038  0.2553  n.a. 
 
mysid  juveniles survival  0.7324  0.7482  0.8513  −0.0088  0.1139  1.1139  0.1139  1.6628 
 
macroalga  germling length  0.2304  0.4624  −0.3872  −0.1192  −1.3010  1.9731  −0.4685  0.9085 
germling cell number  0.3222  0.6232  −0.3468  0.1461  −1.2218  2.0719  −0.3979  0.9912  
survival  1.3222  1.1139  1.1761  0.8865  0.3222  2.4232  −1.2218  n.a. 
EC_{50} = Effective Concentration to 50% of the organism expressed as logarithmic scale;
2,4DNT = 2,4dinitrotoluene; 2,6DNT = 2,6dinitrotoluene;
1,3DNB = 1,3dinitrobenzene; 2,4,6TNT = 2,4,6trinitrotoluene;
1,3,5TNB = 1,3,5trinitrobenzene; PAc = 2,4,6trinitrophenol (picric acid);
Tetryl = 2,4,6trinitrophenylmethylnitramine;
RDX = hexahydro1,3,5trinitro1,3,5triazine (Royal Demolition Explosive); n.a. = not available (experimental data expressed as greater than – mg/L)
Ordnance compounds toxicity: experimental NOEC values.
Specie  Endpoint  2,4DNT  2,6DNT  1,3DNB  2,4,6TNT  1,3,5TNB  PAc  Tetryl  RDX 

sea urchin  fertilization  1.5911  1.3617  1.9243  2.0128  1.5441  2.2504  n.a.  1.8751 
embryological development  1.2553  n.a.  n.a.  0.3222  −0.6198  2.2504  −1.4437  1.8751  
germination  −0.0269  0.3424  −0.5229  0.2304  −1.3372  2.2279  −0.3010  0.9638  
 
polychaete  laid eggs/female  n.a.  n.a.  0.3802  0.1461  −0.4559  2.0334  −1.8239  1.0755 
 
redfish  larvae survival  1.5391  1.1367  1.4014  0.7993  −0.0044  1.9868  0.0792  1.8325 
 
mysid  survival  0.5563  0.6990  0.7160  −0.1871  −0.0177  0.9638  0.0414  1.6721 
 
macroalga  germling length and cell number  n.a.  n.a.  n.a.  n.a.  −1.5376  n.a.  −1.0088  n.a. 
survival  0.9777  1.1644  0.9868  0.7853  0.0792  2.2989  −1.5850  1.6902 
NOEC = No Observed Effect Concentration;
2,4DNT = 2,4dinitrotoluene; 2,6DNT = 2,6dinitrotoluene;
1,3DNB = 1,3dinitrobenzene; 2,4,6TNT = 2,4,6trinitrotoluene;
1,3,5TNB = 1,3,5trinitrobenzene; PAc = 2,4,6trinitrophenol (picric acid);
Tetryl = 2,4,6trinitrophenylmethylnitramine; RDX = hexahydro1,3,5trinitro1,3,5triazine (Royal Demolition Explosive);
n.a. = not available (experimental data expressed as greater than a value – mg/L)
Ordnance compounds toxicity: experimental LOEC values.
Specie  Endpoint  2,4DNT  2,6DNT  1,3DNB  2,4,6TNT  1,3,5TNB  PAc  Tetryl  RDX 

sea urchin  fertilization  1.8751  1.6532  2.0414  n.a.  1.6812  2.5465  −0.2218  n.a. 
embryological development  1.5911  0.6990  1.9243  0.9590  −0.3188  2.5465  −1.0809  n.a.  
germination  0.2553  0.6721  −0.1871  0.5315  −1.0315  2.5263  0.0000  1.1959  
 
polychaete  laid eggs/female  0.3802  0.2553  0.6435  0.4472  −0.2147  2.2967  −1.5850  1.3747 
 
redfish  larvae survival  1.8248  1.5051  1.6955  1.0334  0.3010  2.2718  0.4150  n.a. 
 
mysid  survival  0.8325  0.9912  0.9868  0.1271  0.2742  1.3139  0.3010  n.a. 
 
macroalga  germling length and number  cell −0.3188  0.0792  −0.6778  −0.6778  −1.3372  1.9638  −0.6021  0.6990 
 
survival  1.2788  1.4713  1.2923  1.0645  0.3802  2.5786  −1.2518  n.a. 
LOEC = Lowest Observed Effect Concentration;
2,4DNT = 2,4dinitrotoluene; 2,6DNT = 2,6dinitrotoluene;
1,3DNB = 1,3dinitrobenzene; 2,4,6TNT = 2,4,6trinitrotoluene;
1,3,5TNB = 1,3,5trinitrobenzene; PAc = 2,4,6trinitrophenol (picric acid);
Tetryl = 2,4,6trinitrophenylmethylnitramine; RDX = hexahydro1,3,5trinitro1,3,5triazine (Royal Demolition Explosive)
n.a. = not available (experimental data expressed as greater than a value – mg/L)
MDF SAR monovariate models: EC_{50}.
sea urchin
 

Endpoint  fertilization  embryological development  germination 
MDF SAR Equation  Ŷ = − 0.16 – 0.37·X  Ŷ = −7.09 – 1.09·X  Ŷ = −1.50 + 6.28·10^{−2}·X 
(Eq_no)  Eq_01  Eq_02  Eq_03 
Correlation coefficient (r)  0.9997  0.9650  0.9435 
95% confidence interval for r  [0.9885–0.9999]  [0.6193–0.9973]  [0.5477–0.9942] 
Standard error of estimated (s)  0.02  0.35  0.39 
Fisher parameter (pvalue)  5674 (p = 5.16·10^{−6})  68 (p = 4.32·10^{−4})  49 (p = 4.32·10^{−4}) 
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.9984  0.8460  0.8333 
Sample size  5  7  8 
Descriptor (X)  LIMmwQt  lNPmfQt  aIDmjQg 
Dominant Atomic Property  Partial charge ( 
Partial charge ( 
Partial charge ( 
• Interaction via  Bonds ( 
Bonds ( 
Space ( 
• Interaction Model  Q^{2}/d  Q^{2}/d^{2}  (Q·d)^{−1} 
• Structure on Activity Scale  Logarithmic  Logarithmic  Inversed 
 
MDF SAR Equation  Ŷ = −1.73 + 16.91·X  Ŷ = 0.28 − 1.31·X  Ŷ = 3.93 − 0.80·X 
Eq  Eq_04  Eq_05  Eq_06 
Correlation coefficient (r)  0.9655  0.9531  0.9787 
95% confidence interval  [0.7000–0.9965]  [0.5186–0.9963]  [0.7511–0.9983] 
Standard error of estimated (s)  0.32  0.25  0.10 
Fisher parameter (pvalue)  82 (p = 1.00·10^{−4})  50 (p = 8.92·10^{−4})  114 (p = 1.25·10^{−4}) 
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.8852  0.8412  0.9267 
Sample size  8  7  7 
MDF Descriptor  anDRJQt  LHDmjQg  imMrtCg 
Dominant Atomic Property  Partial charge ( 
Partial charge ( 
Cardinality ( 
• Interaction via  Bonds ( 
Space ( 
Space ( 
• Interaction Model  Q·d  (Q·d)^{−1}  C^{2}/d^{4} 
• Structure on Activity Scale  Inversed  Logarithmic  Inversed 
 
MDF SAR Equation  Ŷ = −6.13 − 1.88·X  Ŷ = −6.02 − 1.87·X  Ŷ = −0.79 − 102.72·X 
Eq  Eq_07  Eq_08  Eq_09 
Correlation coefficient (r)  0.9445  0.9359  0.9835 
95% confidence interval  [0.7170–0.9901]  [0.6790–0.9885]  [0.8884–0.9976] 
Standard error of estimated (s)  0.35  0.38  0.22 
Fisher parameter (pvalue)  50 (p = 4.09·10^{−4})  42 (p = 6.28·10^{−4})  148 (p = 6.65·10^{−5}) 
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.8045  0.7933  0.9503 
Sample size  8  8  7 
Descriptor (X)  LIDmjQg  LIDmjQg  IAPmtQt 
Dominant Atomic Property  Partial charge ( 
Partial charge ( 
Partial charge ( 
• Interaction via  Space ( 
Space ( 
Bonds ( 
• Interaction Model  (Q·d) ^{−1}  (Q·d) ^{−1}  Q^{2}·d^{−4} 
• Structure on Activity Scale  Logarithm  Logarithm  Identity 
d = distance
MDF SAR monovariate models: NOEC.
sea urchin
 

Endpoint  fertilization  embryological development  germination 
MDF SAR Equation  Ŷ = 1.42 + 0.17·X  Ŷ = −1.27 + 1.27·10^{−3}·X  Ŷ = −1.74 + 6.08·10^{−2}·X 
(Eq_no)  Eq_10  Eq_11  Eq_12 
Correlation coefficient (r)  0.9739  0.9859  0.9355 
95% confidence interval for r  [0.8283–0.9962]  [0.8721–0.9985]  [0.6772–0.9885] 
Standard error of estimated (s)  0.08  0.27  0.41 
Fisher parameter (pvalue)  92 (p = 2.09·10^{−4})  139 (p = 2.97·10^{−4})  42 (p = 6.38·10^{−4}) 
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.9101  0.9417  0.8105 
Sample size  7  6  8 
Descriptor (X)  ASPmwQg  asmrfQt  aIDmjQg 
Dominant Atomic Property  Partial charge ( 
Partial charge ( 
Partial charge ( 
• Interaction via  Space ( 
Bonds ( 
Space ( 
• Interaction Model  Q^{2}·d^{−1}  Q^{2}·d^{−2}  (Q·d) ^{−1} 
• Structure on Activity Scale  Absolute  Inversed  Inversed 
 
MDF SAR Equation  Ŷ = −10.25 − 1.42·X  Ŷ = 9.35·10^{−2} − 1.37·X  Ŷ = 19.24 + 668.36·X 
Eq  Eq_13  Eq_14  Eq_15 
Correlation coefficient (r)  0.9754  0.9542  0.9048 
95% confidence interval  [0.7861–0.9974]  [0.7616–0.9919]  [0.5521–0.9828] 
Standard error of estimated (s)  0.32  0.24  0.28 
Fisher parameter (pvalue)  78 (p = 8.98·10^{−4})  61 (p = 2.33·10^{−4})  27 (p = 2.01·10^{−3}) 
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.9060  0.8394  0.7263 
Sample size  6  8  8 
MDF Descriptor  LsmrfQg  LHDmjQg  iBPMwEt 
Dominant Atomic Property  Partial charge ( 
Partial charge ( 
Electronegativity ( 
• Interaction via  Space ( 
Space ( 
Bonds ( 
• Interaction Model  Q^{2}·d^{−2}  Q^{2}·d^{−2}  E^{2}·d^{−1} 
• Structure on Activity Scale  Logarithm  Logarithm  Inversed 


MDF SAR Equation  Ŷ = 3.71 − 1.28·X  
Eq  Eq_16  
Correlation coefficient (r)  0.9578  
95% confidence interval  [0.7786–0.9925]  
Standard error of estimated (s)  0.36  
Fisher parameter (pvalue)  67 (p = 1.83·10^{−4})  
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.8532  
Sample size  8  
Descriptor (X)  LnDRJQt  
Dominant Atomic Property  Partial charge ( 

• Interaction via  Bonds ( 

• Interaction Model  Q·d  
• Structure on Activity Scale  Logarithm 
d = distance
MDF SAR monovariate models: LOEC.
sea urchin
 

Endpoint  fertilization  embryological development  germination 
MDF SAR Equation  Ŷ = 0.57 − 47.56·X  Ŷ = −7.62 −1.14·X  Ŷ = −1.43 + 6.02·10^{−2}·X 
(Eq_no)  Eq_17  Eq_18  Eq_19 
Correlation coefficient (r)  0.9993  0.9653  0.9357 
95% confidence interval for r  [0.9932–0.9999]  [0.7771–0.9950]  [0.6781–0.9885] 
Standard error of estimated (s)  0.04  0.36  0.40 
Fisher parameter (pvalue)  2781 (p = 7.74·10−^{7})  68 (p = 4.22·10−^{4})  42 (p = 6.33·10−^{4}) 
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.9962  0.8753  0.8140 
Sample size  6  7  8 
Descriptor (X)  IAPmfQt  lNPmfQt  aIDmjQg 
Dominant Atomic Property  Partial charge ( 
Partial charge ( 
Partial charge ( 
• Interaction via  Bonds ( 
Bonds ( 
Space ( 
• Interaction Model  Q^{2}·d^{−2}  Q^{2}·d^{−2}  Q^{2}·d^{−2} 
• Structure on Activity Scale  Identity  Logarithm  Inversed 
 
MDF SAR Equation  Ŷ = −1.69 + 16.60·X  Ŷ = 0.39 − 1.30·X  Ŷ = 4.22 − 0.83·X 
Eq  Eq_20  Eq_21  Eq_22 
Correlation coefficient (r)  0.9612  0.9694  0.9897 
95% confidence interval  [0.7949–0.9931]  [0.8012–0.9956]  [0.9290–0.9985] 
Standard error of estimated (s)  0.34  0.20  0.07 
Fisher parameter (pvalue)  73 (p = 1.42·10^{−4})  78 (p = 3.09·10^{−4})  239 (p = 2.06·10^{−5}) 
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.8763  0.8844  0.9585 
Sample size  8  7  7 
MDF Descriptor  anDRJQt  LHDmjQg  imMrtCg 
Dominant Atomic Property  Partial charge ( 
Partial charge ( 
Cardinality ( 
• Interaction via  Bonds ( 
Space ( 
Space ( 
• Interaction Model  Q·d  Q^{2}·d^{−2}  Q^{2}·d^{−4} 
• Structure on Activity Scale  Inversed  Logarithm  Inversed 
 
MDF SAR Equation  Ŷ = −2.02 + 5.99·10^{−2}·X  Ŷ = 3.69 + 0.11·X  
Eq  Eq_23  Eq_24  
Correlation coefficient (r)  0.9504  0.9764  
95% confidence interval  [0.7439–0.9912]  [0.8436–0.9966]  
Standard error of estimated (s)  0.35  0.28  
Fisher parameter (pvalue)  56 (p = 2.94·10^{−4})  102 (p = 1.62·10^{−4})  
Crossvalidation leaveoneout score (r_{cvloo}^{2})  0.8686  0.9091  
Sample size  8  7  
Descriptor (X)  aIDmjQg  iIDdPQg  
Dominant Atomic Property  Partial charge (Q)  Partial charge (Q)  
• Interaction via  Space (geometry)  Space (geometry)  
• Interaction Model  Q^{2}·d^{−2}  Q^{2}  
• Structure on Activity Scale  Inversed  Inversed 
d = distance
Predicted activities of ordnance compounds by using the MDF SAR monovariate models.
Activity  Specie  Toxicity  Compound  Eq_  X  

Fertilization  
EC_{50}  2,6DNT  01  −4.9295  1.6618 
EC_{50}  2,4,6TNT  01  −6.6904  2.3116  
EC_{50}  RDX  01  −5.8418  1.9984  
LOEC  RDX  17  −0.0398  2.4593  
 
Embryological development  
EC_{50}  RDX  02  −7.9917  1.6018 
NOEC  2,6DNT  11  6355.74  6.8112  
1,3DNB  11  2900.88  2.4159  
LOEC  RDX  18  −5.8418  1.9984  
 
Fertilization  
NOEC  Tetryl  10  333.40  56.8491 
 
Larvae survival  
EC_{50}  RDX  05  −1.0141  1.6124 
LOEC  RDX  21  −1.0141  1.7153  
 
Juveniles survival  
EC_{50}  RDX  06  4.6574  0.1832 
 
Survival  
LOEC  RDX  22  4.6574  0.3365 
 
Laid eggs/female  
NOEC  2,4DNT  13  −7.2544  0.0519 
2,6DNT  13  −8.5506  1.8932  
 
Survival  
EC_{50}  RDX  09  −0.0562  4.9762 
LOEC  RDX  24  32.7066  −0.1848 
X = value of the molecular descriptors used by MDF SAR equation – see
2,6DNT = 2,6dinitrotoluene; 2,4,6TNT = 2,4,6trinitrotoluene; RDX = hexahydro1,3,5trinitro1,3,5triazine;
Ŷ_{Pred} = predicted activity